O

D

PPh

F

Ath

T

ur reference: YSSRE 1529 P-authorquery-v11

AUTHOR QUERY FORM

Journal: YSSRE Please e-mail or fax your responses and any corrections to:

Article Number: 1529

E-mail: corrections.esch@elsevier.sps.co.in

Fax: +31 2048 52799

ear Author,

lease check your proof carefully and mark all corrections at the appropriate place in the proof (e.g., by using on-screen annotation in theDF file) or compile them in a separate list. Note: if you opt to annotate the file with software other than Adobe Reader then please also

ighlight the appropriate place in the PDF file. To ensure fast publication of your paper please return your corrections within 48 hours.

or correction or revision of any artwork, please consult http://www.elsevier.com/artworkinstructions.

ny queries or remarks that have arisen during the processing of your manuscript are listed below and highlighted by flags ine proof. Click on the ‘Q’ link to go to the location in the proof.

Location inarticle

Query / Remark: click on the Q link to goPlease insert your reply or correction at the corresponding line in the proof

Q1 Please confirm that given names and surnames have been identified correctly.

Q2 Please check and approve the insertion of section heading ‘Introduction’.

Q3 References ‘Jimerson et al. (2003), DeLuca and Rosenbaum (2000), and Youniss andSmollar (1986)’ have been changed to ‘Jimerson et al. (2000), DeLuca and Rosenbaum(2004), and Youniss and Smollar (1985)’ as per list. Please check.

Q4 References ‘Cairns et al. (2003), Vaquera and Kao (2006), and Kandel (1978)’ are cited intext but not listed. Please check.

Q5 This section comprises references that occur in the reference list but not in the body of thetext. Please position each reference in the text or, alternatively, delete it. Any reference notdealt with will be retained in this section.

Q6 Please specify the significance of footnote ‘ 6¼’ cited in the table, as a corresponding footnotetext has not been provided.

hank you for your assistance.

Please check this box if you have nocorrections to make to the PDF file

YSSRE 1529 No. of Pages 1, Model 3G

27 May 2013

Highlights

� Closeness of friendships is measured through both affect and shared activities. � Holding many close friendships in schooldecreases a student’s risk of dropping out. � Distant friendships with at-risk students increase a student’s risk of droppingout. � The importance of friends’ characteristics is influenced most by shared activities.

1

3 D4 f

5

6

7 W8 D

910

1 2a

13 A14 R15 R16 A17 A

18 K19 D20 P21 S22

2 324252627282930313233343536

37

38

39 1

40

41 f42 K43 f44 f45 o46 c47

48 r49 t50 a51 i52 c53 d54 o55 e

0h

Q1

Q2

Q3

Social Science Research xxx (2013) xxx–xxx

YSSRE 1529 No. of Pages 16, Model 3G

28 May 2013

ropping out of high school: Effects of close and distantriendships

illiam Carbonaro ⇑, Joseph Workmanepartment of Sociology, University of Notre Dame, United States

r t i c l e i n f o

rticle history:eceived 8 June 2012evised 13 May 2013ccepted 13 May 2013vailable online xxxx

eywords:ropouteer effectsocial identity

a b s t r a c t

Prior research highlights the role of friends in influencing whether a student completeshigh school. Students who drop out tend to have fewer friends, as well as friends whoare less oriented toward school success. We distinguish between close and distantfriendships by developing a theoretical framework which predicts close and distant friendslikely have distinct effects on dropping out. Close friendships provide valuable emotionalsupport, and forging numerous close friendships at school should decrease one’s risk ofdropping out. In contrast, the characteristics of distant friends help shape students’ socialidentities and beliefs about ‘‘what’s normative.’’ Our analyses of the Add Health data setconfirm our expectations. Students with more close friendships are less likely to dropout, but close friends’ characteristics are unrelated to dropping out. Distant relationships(as measured by affect and regularity of interaction) with friends who have a high riskof dropping out significantly increase a student’s own risk of dropping out.

� 2013 Published by Elsevier Inc.

. Introduction

Contents lists available at SciVerse ScienceDirect

Social Science Research

journal homepage: www.elsevier .com/locate /ssresearch

Prior research indicates that a student’s risk of dropping out is affected by the number friends s/he has, as well as his/herriends’ characteristics (Carbonaro, 1998; Jimerson et al., 2000; Ream and Rumberger, 2008; Risi et al., 2003; Staff and

reager, 2008). These studies suggest that friendship ties are important (above and beyond students’ own characteristics)

or educational attainment, but they share an important limitation: they fail to examine whether different types ofriendships matter equally for student outcomes. Adolescents typically have a few close friends, as well as a larger ‘‘clique’’f more distant friendship ties (Steinberg, 1996). Surprisingly, almost no research has examined whether the number andharacteristics of these different types of friendships are important for students outcomes.

In this paper, we examine how close and distant friendship ties affect a student’s risk of dropping out. Prior theory andesearch suggests that the number of close friendships provides valuable emotional support for students, and should helphem stay in school and graduate. However, we argue that a student’s social identity and beliefs about ‘‘what’s normative’’re likely shaped by characteristics of students’ distant friends. These distant friends, who are less familiar to students, aremportant because they serve as ‘‘prototypes’’ regarding ‘‘what’s normative’’ for a student’s peer group. Our findings areonsistent with our expectations. Students with more close friends are less likely to drop out. However, students who haveistant friendships with students who have a higher risk of dropping out are more likely to drop out themselves (net of theirwn characteristics). In contrast, close friendships with students who have a high risk of dropping out are either weakly orntirely unrelated to a students’ own risk of dropping out.

049-089X/$ - see front matter � 2013 Published by Elsevier Inc.ttp://dx.doi.org/10.1016/j.ssresearch.2013.05.003

⇑ Corresponding author. Address: Department of Sociology, 810 Flanner, Notre Dame, IN 46656, United States.E-mail address: wcarbona@nd.edu (W. Carbonaro).

Please cite this article in press as: Carbonaro, W., Workman, J. Dropping out of high school: Effects of close and distant friendships. SocialSci. Res. (2013), http://dx.doi.org/10.1016/j.ssresearch.2013.05.003

56

57

58

59

60

61

62

63

64

65

66

67

68

69

70

71

72

73

74

75

76

77

78

79

80

81

82

83

84

85

86

87

88

89

90

91

92

93

94

95

96

97

98

99

100

101

102

103

104

105

106

2 W. Carbonaro, J. Workman / Social Science Research xxx (2013) xxx–xxx

YSSRE 1529 No. of Pages 16, Model 3G

28 May 2013

1.1. Friendships, peers, and dropping out of high school

Prior studies of friendships, peers, and dropouts can be divided into two categories: (1) studies that examine the impor-tance of a student’s social integration with their peers for dropping out, and (2) studies that examine whether a student’sfriends’ characteristics are related to his/her risk of dropping out. The first group of studies finds that students who are moresocially integrated in high school are less likely to drop out. Students who are rejected by their peers and socially isolated intheir school are more likely to drop out of high school (DeLuca and Rosenbaum, 2004; Farmer et al., 2003; Jimerson et al.,2000; Risi et al., 2003; Staff and Kreager, 2008). Staff and Kreager (2008) found that more popular students (as measuredby the number of schoolmates who named them as a friend) were less likely to drop out of high school. South et al.(2007) also found that students who are less likely to drop out have denser friendship networks, and also tend to be morecentrally situated within their friendship network.

The second group of studies focuses on how friends’ characteristics affect a student’s risk of dropping out. Sincehomophily is common in student friendship networks (see Kindermann, 2007; Kubitschek and Hallinan, 1998; Berndtand Keefe, 1995), at-risk students typically associate with other at-risk students. Some evidence suggests that these associ-ations worsen outcomes for at-risk students. For example, students with peers who act disruptively become more disruptivethemselves over time (Berndt and Keefe, 1995). Battin-Pearson et al. (2000) also found that associating with deviant peershad negative effects on students’ grades and their chances of dropping out (net of grades). In addition, at-risk students aremore likely to have friends who are dropouts (Ellenbogen and Chamberland, 1997), and these friendships increase thechances of dropping out of high school by twelfth grade (Carbonaro, 1998; Ream and Rumberger, 2008). Students who havefriends with lower grades, and whose friends participate in fewer extracurricular activities are also more likely to drop out(South et al., 2007). Finally, students’ educational expectations are related to their peers’ expectations, (e.g., Sewell and Haus-er, 1980), and students with friends who value education more highly are less likely to drop out (Ream and Rumberger,2008).

Overall, prior research on friendships and dropping out suggests that both the number and characteristics of one’s friendsare related to a student’s risk of dropping out. While these studies reveal the potential importance of student friendships fordropping out, research in this area has some important limitations. For example, prior studies have examined a fairly limitedrange of friends’ characteristics, and additional research that includes a broader range of friends’ characteristics is needed tobetter understand how dropping out is related to friendship ties.

We believe the most important limitation is that prior researchers have treated all friendships as equivalent in their ef-fects on students’ outcomes. Measures such as ‘‘average friends’ GPA’’ (e.g., Staff and Kreager, 2008) and ‘‘number of friendswho are dropouts’’ (Carbonaro, 1998; Ream and Rumberger, 2008) assume that equal weight should be given to each friend(and his/her characteristics) when estimating their effect on dropping out. However, there are many reasons to believe thatsome friendships are more influential than others (see Giordano, 2003). Friendships vary along several important dimen-sions: e.g., quantity of time spent together; number and type of shared activities; strength of emotional bond (‘‘bestfriends’’); etc. We use the terms ‘‘close’’ and ‘‘distant’’ to denote the ends of a continuum along which friendships are rankedon these dimensions.1 By classifying friendships as either close or distant, we can examine whether different kinds of friend-ships have varying effects on students’ behaviors, attitudes, and ultimately, their risk of dropping out of high school.

1.2. Theoretical frameworks for understanding the role of friends in dropping out

Why would a student’s friendship ties affect his/her decision to drop out of high school? Adolescence is a time when fit-ting in with one’s peer group is especially important (Coleman, 1961; Newman and Newman, 1976; Steinberg, 1996). Indeed,

some scholars have claimed that peer influences outweigh the effects of families in shaping numerous important adolescentoutcomes (Harris, 2006, 2009; Steinberg, 1996). We identify two competing perspectives on how friends’ characteristicsaffect students’ outcomes: the first emphasizes the importance of close friendships, while the second highlights the signif-icance of more distant friendship ties.

Giordano (2003) offers three reasons why adolescents may be affected by the characteristics of their most intimatefriendship ties. First, more frequent communication and interaction with close friends offers more opportunities forinfluence. Second, students may be more easily influenced by those who are similar to themselves (presumably, their closefriends). Finally, since adolescents value these friendships more than distant relationships with peers, they will engage inacts of conformity to preserve these close friendships. Hallinan and Williams (1991) also argued that close friends will bemore influential than casual ones because adolescents view close friends as more trustworthy (also see Youniss and Smollar,1985). Thus, when judging how to behave or which expectations to internalize, adolescents see their closest friends as themost reliable guides available.

1

It is important to note that our use of the terms ‘‘close’’ and ‘‘distant’’ friendships are similar to Granovetter’s (1973, 1983) usage of ‘‘strong’’ and ‘‘weak’’ties. However, we decided against using the ‘‘strong-weak’’ terminology for a couple of important reasons. First, it is questionable whether friends can properlybe labeled ‘‘weak’’ ties. Second, and more importantly, the terms ‘‘strong’’ and ‘‘weak’’ ties evoke a specific theoretical argument about how social ties matter foroutcomes. Our theoretical argument regarding how close and distant friendship ties matter for dropping out draws upon a very different theoretical frameworkthan Granovetter’s, and we wanted to avoid unnecessarily confusing readers on this important point.

Please cite this article in press as: Carbonaro, W., Workman, J. Dropping out of high school: Effects of close and distant friendships. SocialSci. Res. (2013), http://dx.doi.org/10.1016/j.ssresearch.2013.05.003

107

108 K109 a110 g111 g112 2113 p114 i115 s116

117 t118 t119 u120 t121 d122 b123 c124 t125 t126 t127

128 m129 o130 r131 (132 a133 t134 m135 m136 t137

138 d139 M140 s141 s142 1143 e144 s145 a146 e147 e148 f

149 1

150

151 (152 f153 u154 s155 e156 a157 b158

159 t160 e

n

W. Carbonaro, J. Workman / Social Science Research xxx (2013) xxx–xxx 3

YSSRE 1529 No. of Pages 16, Model 3G

28 May 2013

In contrast, some scholars emphasize the influence of more distant members of a student’s social network. Akerlof andranton (2002, 2010) argue that casual friends and acquaintances help define the social categories within a school that shapestudent’s identity. Social categories have ‘‘norms and ideals’’ to which students must adhere in order to gain acceptance byroup members. Similarly, in her review of research on adolescent relationships, Giordano (2003) notes ‘‘adolescents learn areat deal about themselves, their social worth, and the broader cultural world beyond the confines of close friendships’’ (p.67). Giordano notes students’ ‘‘wider circle of friends’’ typically greatly outnumbers students’ close friends and have theotential to offer a considerable evaluative force. Akerlof and Kranton’s framework overlaps heavily with identity and social

dentity theory (see Turner et al., 1987; Hogg et al., 1995; Stets and Burke, 2000), both of which highlight the primacy ofocial groups in shaping behavior.

Harris (2006) synthesized research from the fields of neuroscience, behavioral genetics, and social psychology to devise a

heoretical framework that simultaneously considered the effects of close and distant peers on adolescents. Harris argues hat students’ social interactions with their close friends are governed by a ‘‘relationship system’’ that relies on brain mod-les that recognize and account for human individuality, such as the cognitive capacity for facial recognition. As Harris notes,he relationship system’s ‘‘purpose is to make fine distinctions among individuals’’ (p. 181). While Harris recognizes that stu-ents want to maintain these intimate relationships, she argues that close friends do not serve as normative guides forehavior because they are seen as unique individuals rather than group members. Similarly, Call and Mortimer (2001) con-lude that close friendships provide an ‘‘arena of comfort’’ that allows adolescents to experiment with new roles and iden-ities, and forge an independent sense of self. Thus, students with more close friendship ties have greater emotional supporto draw upon when they experience adversity, but they may also feel less constrained in conforming to the expectations ofheir closest friends.

In contrast, Harris (2006) argues that a ‘‘socialization system’’ governs how we (as individuals) become and behave asembers of groups. Unlike the relationship system, the socialization system relies on social categories to help us make sense

f the world (Harris, 2006). When we interact with casual friends, acquaintances, and strangers, we rely upon social catego-ies that tell us who they are, but also provide us with valuable information about who we are and how we should behaveTurner et al., 1987; Fiske, 2004). This cognitive system promotes a tendency to underestimate differences within groups,nd to overestimate differences between groups (Smith, 2002). Thus, if a student labels him/herself a ‘‘jock,’’ s/he tendso think that all ‘‘jocks’’ are more similar than they are, and sees greater differences between ‘‘jocks’’ and other groups (‘‘nor-

als,’’ ‘‘nerds,’’ ‘‘burnouts,’’ etc.). This limitation gives the socialization system its power to induce conformity. Since infor-ation about casual friends is scarce, individuals use ‘‘prototypes’’ (representations of a group’s defining attributes) to fill in

he missing information and make sense of their behavior (Turner et al., 1987; Stets and Burke, 2000; Harris, 2006).In our view, Harris’s synthesis of the literature predicts that close and distant friendships will have different effects on

ropping out. The relationship system highlights the importance of close friends as a source of support (also see Call andortimer, 2001). Thus, the number of close friends should matter for students, and having more close friends should help

tudents find support and encouragement to stay in school because it is in their self-interest to maintain these important

ocial ties. In contrast, Harris’s socialization system, as well as social identity theory (e.g., Turner et al., 1987; Hogg et al.,995; Stets and Burke, 2000), suggests that the characteristics (not the number) of distant friends will have a greater influ-nce on students’ behavior than close friends. If one’s best friend skips school, gets a low grade in a class, or drops out ofchool entirely, there is no expectation that this friend’s decision should guide one’s own behavior because these behaviorsre attributed to traits specific to the individual (e.g., their personality, family situation, etc.). However, when distant friendsngage in these behaviors, a student infers (via the socialization system) that such behaviors are permissible and possiblyven normative for members of his/her group. In short, the characteristics of distant friends help set the normative climateor behaviors and beliefs that shape a student’s risk of dropping out.

.3. Close and distant friendship ties in prior research

Research suggests that both close and distant friendship ties matter for students’ academic outcomes. Vaquera and Kao2008) found that students with more reciprocated friendships (where each member of the dyad reported the other to be ariend) had a stronger sense of ‘‘school belonging’’ and higher grades. These findings are consistent with our prediction basedpon Harris’s relationship system: those with more close friendships experience more success in school. However, this re-earch is limited in examining only the number of friendships that students have. We argue that it is critically important toxamine both the nature of the friendship and the characteristics of students’ friends – their behaviors, beliefs, etc. – as wells the number of friends students have. The type of relationship – close or distant – should shape how influential it will be,ut the friend’s characteristics – e.g., whether s/he is a high or low achiever – determines the norms being endorsed.2

Steinberg (1996) found that students with more academically oriented cliques and crowds performed better in school

han students with less academically oriented peers. The same held true for deviance: students in cliques and crowds thatngaged in more deviance were more deviant themselves (Steinberg, 1996). ‘‘Best friends’’ did not significantly affect student

2 Carbonaro (1999) emphasized this point in his critique of research on Coleman’s theory of ‘‘intergenerational closure.’’ Studies that examine only theumber of ‘‘closed’’ ties will not capture key elements of the normative environment – which lies at the core of Coleman’s argument.

Please cite this article in press as: Carbonaro, W., Workman, J. Dropping out of high school: Effects of close and distant friendships. SocialSci. Res. (2013), http://dx.doi.org/10.1016/j.ssresearch.2013.05.003

161

162

163

164

165

166

167

168

169

170

171

172

173

174

175

176

177

178

179

180

181

182

183

184

185

186

187

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

206

207

208

209

4 W. Carbonaro, J. Workman / Social Science Research xxx (2013) xxx–xxx

YSSRE 1529 No. of Pages 16, Model 3G

28 May 2013

outcomes in Steinberg’s research. These findings point to the importance of distant peer networks in establishing a norma-tive environment within the school.

To our knowledge, no studies have examined the relative importance of close and distant friendship ties on dropping outof high school. High school dropout or completion is a particularly important process by which to examine the effects ofclose and distant friendships. First, whether a student completes a high school degree has important implications for his/her occupational opportunities later in life. Second, the decision to drop out of high school can be seen as the summationof many other factors that often serve as dependent variables in studies of peer influence, including GPA, college expecta-tions, and deviance. Finally, a student’s risk of dropping out should be particularly sensitive to the normative environmentestablished by friends in the school because acts of deviance that are related to dropping out, as well as decisions about edu-

cational attainment are shaped by expectations regarding ‘‘what’s normative’’ for one’s group.

1.4. Research questions: close and distant friendship ties and dropping out

We will examine two main research questions in our analyses. Both research questions examine whether ‘‘close’’ and‘‘distant’’ friends have distinct effects on a student’s risk of dropping out. We operationalize the social distance betweenfriends by focusing on (1) the affective attachment within each friendship dyad and (2) the frequency of interaction betweenfriends. We first focus on affect, or subjective emotional attachment within a friendship. Within each friendship dyad, it ispossible to examine how each member of the pairing rates the other. Reciprocated friendships (where both students con-sider the other a friend) are the closest emotional bonds between friends. Unrequited friendships (where the student deemsa peer a friend, but the peer does not reciprocate) are less emotionally intense because the peer is more guarded in theirthoughts and actions, but the student is still emotionally invested in the relationship. Our first research question is: do num-ber and the characteristics of reciprocated and unrequited friends differ in importance for a student’s own chances of drop-ping out? We predict that students with more close friendship ties (reciprocated) should be less likely to drop out. However,we expect that the characteristics of distant friends (to whom students are less attached) will have the strongest effect on astudent’s risk of dropping out.

Our second measure of social distance (i.e., closeness of friendships) focuses on the amount of shared social interactionbetween friends. The more time friends spend interacting with one another, the more information is gathered and retainedin the ‘‘relationship system.’’ The less time friends spend together, the more individuals will rely on the socialization systemto interpret their friends’ beliefs and behaviors and use social categories to fill in missing information about these distantfriends. Thus, our second research question is: does the number of activities a student shares with a friend affect the impor-tance of that friend’s characteristics for dropping out? We predict that friends with whom a student spends more time willbe less influential for a student’s risk of dropping out.

2. Data

In order to address our research questions, we analyzed data from the National Longitudinal Study of Adolescent Health(Add Health). A random sample of 80 high schools and 52 middle schools was selected to participate in the study. Theschools were stratified on region of the country, urbanicity, schools size, school type, and ethnic composition. In the fallof 1994, the entire student body of each school was given an in-school survey. Approximately, 80% of eligible students par-ticipated in the initial survey, totaling 90,118 students ranging in grade from 7 to 12. Students were asked a variety of ques-tions regarding their experiences in school and their daily lives outside of school. In addition, students were asked tonominate other students in the school as their friends. This unique feature of the Add Health data allows researchers to con-struct the social networks within schools.3

A subsample of students was selected to participate in the in-home waves of data collection in subsequent years. The firstwave of in-home interviews was conducted in the spring of 1995, which is the end of the school year in which the studybegan. In the 6-year follow-up, conducted between August 2001 and April 2002, respondents were asked about any educa-tional degrees that they had attained. The timing of the survey should allow adequate time for all Add Health respondents tofinish high school (assuming no grade retention). In addition, the Adolescent Health and Academic Achievement (AHAA)transcript study collected transcript information from respondents’ secondary schools. The sample for our study consistsof the 10,388 students who had valid information on degree attainment and participated in the initial in-school survey.In the analyses presented we used the characteristics of students and their friends, gathered during the 1994–1995 schoolyear, to predict whether a student completed a high school degree. For further description of the Add Health database see

4

Harris et al. (2009).

3 Schools that had less than 50% of eligible students participate in the in-school survey are excluded from the analyses presented in this paper. Low levels ofparticipation are likely to lead to inaccurate representations of the friendship networks of students who attend these schools. This restriction leads to 250students in eight schools being excluded from the sample.

4 It should be noted that our sample is representative of the population of students from the mid-1990s, but recent demographic changes in the USpopulation make our sample not entirely representative of today’s school age population. In particular, the percentage of Latino/a youth in our sample doesrepresent the growing proportion of Latino youth in the past decade very well. It would be useful to replicate our findings with more recent data.

Please cite this article in press as: Carbonaro, W., Workman, J. Dropping out of high school: Effects of close and distant friendships. SocialSci. Res. (2013), http://dx.doi.org/10.1016/j.ssresearch.2013.05.003

210 2

211

212 w213 a214 d215 W216 r217 d

218 2

219

220 a221 (222 t223 i224 e225 o226 t227 w228 s229 (230 i231 e232 o233

234 m235 i236 b237 a238 p239 c240 b

241 2

242

243 s244 d245 c246 o247 p248 a249 s250

251 c252 s253 o254 r255 t256 g257 l

d

wor

W. Carbonaro, J. Workman / Social Science Research xxx (2013) xxx–xxx 5

YSSRE 1529 No. of Pages 16, Model 3G

28 May 2013

.1. Dropout

In the 6-year follow up survey (conducted in 2001–2002), respondents were asked to indicate any educational degreeshich they had attained. Students who reported having attained no high school degree as well as those reporting receivingGeneral Equivalency Degree (GED) were classified as dropouts in this study.5 In total, 669 students reported receiving no

egree and 656 students reported receiving a GED. Thus, 1325 students were classified as dropouts, or 12.8% of our sample.hen a self-report of degree attainment was not available we used transcript reports to assess school completion.6 Students

eporting that they were still attending high school were not included in the analyses as it remains unclear whether these stu-ents will drop out or complete school.

.2. Student characteristics

During the in-school survey (fall 1994) students were asked about a number of important achievement-related char-cteristics that can be used to predict high school dropout or completion. These include: student grade point averageGPA), college expectations, deviance, academic engagement, attachment to school, and number of extracurricular activi-ies. We constructed a self-reported measure of grade point average that includes the student’s letter grade in mathemat-

cs, English, history, and science classes from the previous semester. The Cronbach’s alpha for this scale is .787. For college xpectations, responses were clustered at the high end of the scale: 48% of students selected the highest response categoryf ‘‘certain to graduate from college.’’ We used this as a cut point to create a dichotomous variable that indicates whetherhe student reported ‘‘certainty’’ in graduating from college. We measure deviance using a composite variable that equallyeights how frequently the respondent: gets drunk on alcohol, smokes cigarettes, lies to his/her parents or guardians,

kips school, and gets into physical fights. The Cronbach’s alpha for this scale is .678. Finally, following South et al.2007), we created a scale of academic engagement that equally weights how frequently the student has trouble complet-ng homework and paying attention during class (reverse coded) (alpha = .818) and a scale of attachment to school thatqually weights how much the student feels like a part of his or her school, is close to people at school, and likes his

r her school (alpha = .760).

A unique feature of the Add Health dataset is that each student was asked to nominate up to five male and five fe-ale friends. On average students nominated 5.43 friends. However, 14% of students did not make any friendship nom-

nations. Given that nearly the entire student body of each school participated in the survey, friendship nominations cane matched to the friends’ surveys to gather information about the characteristics of students’ friends. Thus, the char-cteristics of students’ friends are reported by the friends themselves. This is important as individuals tend to over-re-ort the similarity between themselves and their friends (Mouw, 2006). For each of the achievement-relatedharacteristics described above (GPA, deviance, etc.), we estimated the average level among those nominated as friendsy the focal student.

.3. Close and distant friendship ties

A central focus of this paper is to examine the influence of different types of friends on whether a student completes highchool. Many studies that examine friendships and friends’ characteristics use data that rely upon are reports by the respon-ents themselves rather than their peers. These studies largely examine the effects of students’ perceptions of their friends’haracteristics rather than the effects of students’ friends’ observed characteristics. Prior research suggests that individualsver-report their similarity with their friends (see Mouw, 2006). While some information about friends can reliably be re-

orted by respondents (e.g., number of friends, number of friends as dropouts, etc.), bias in attitudinal measures is likelycute. Thus, one major advantage of the Add Health data is that friends’ characteristics are reported by the friends them-elves, not the respondent.

First, we examined the effect of the characteristics of friends depending on mutual affect. We divided friendships into twoategories. Reciprocated friends are peers who were both nominated as a friend by the focal student and nominated the focaltudent as a friend. Unrequited friends were nominated by the focal student as a friend but did not reciprocate. For the sakef parsimony when examining the characteristics of these different types of friends, we used a summary measure of friends’isk of dropping out of school. This summary measure was created by estimating a logistic regression, which examined howhe six achievement-related characteristics described above are related to school completion while not controlling for back-round or school characteristics. Thus, for students who had valid degree attainment information (i.e. members of the ana-ytic sample), we observed how the students’ GPA, number of extracurricular activities, attachment to school, engagement,

5 We chose to label GED recipients as ‘‘dropouts’’ because we are interested in students who left high school before receiving a traditional degree. Theecision to return and receive a GED is a separate process that occurs after dropping out.6 When comparing self-reported to transcript indicated degree attainment we found a large number of discrepancies in reports. Upon further examination,e found the self-reports to be more reliable as 80% of the cases with a discrepancy between the transcript and self-report were missing the year of graduation

n the transcript. Previous studies analyzing the Add Health dataset (including Cavanaugh et al. (2006) and Staff and Kreager (2008)) have used student self-eports for measuring school completion.

Please cite this article in press as: Carbonaro, W., Workman, J. Dropping out of high school: Effects of close and distant friendships. SocialSci. Res. (2013), http://dx.doi.org/10.1016/j.ssresearch.2013.05.003

258

259

260

261

262

263

264

265

266

267

268

269

270

271

272

273

274

275

276

277

278

279

280

281

282

283

284

285

286

287

288

289

290

291

292

293

294

295

6 W. Carbonaro, J. Workman / Social Science Research xxx (2013) xxx–xxx

YSSRE 1529 No. of Pages 16, Model 3G

28 May 2013

deviance, and whether the student had high college expectations in the initial wave of data collection were related toeventual degree attainment. For each student who participated in the first wave of data collection, we generated his/her riskof dropout by taking each of their observed achievement-related characteristics and multiplying by the characteristic’sassociation with dropout (the coefficient from the logistic regression). Thus, the risk of dropout measure is equivalent tothe predicted probability of drop out for each of a student’s friends. We then took the average of this measure for the friendswith whom the student had reciprocated and unrequited friendships.

We also measured the closeness of a friendship by the number of activities a student shares with a given friend. Duringthe nomination process students were asked whether they had participated in any of five activities with each friend duringthe previous week. Students were asked whether they had: gone to the friend’s house, met after school to hang out or gosomewhere, spent time over the weekend, talked about a problem, and talked on the telephone. We classified distant friend-ships as those where a nomination of friendship was made but two or fewer of the above activities were reported. Closefriendships are those where the student reported participating in three or more activities with a friend.7 In cases of recipro-cated friendships, both members of the friendship were asked about participation in these activities. For measuring the close-ness of the relationship, we used the information reported by the focal student rather than by his or her friend. For assessing thecharacteristics of friends with whom students have close and distant friendships, we again used the summary measure of afriend’s risk of dropping out.

2.4. Control variables

In our analyses, we controlled for a number of important demographic characteristics. These included: race, gender, par-ents’ highest level of education, parents’ occupation, and whether the student was born in the United States. Since the AddHealth sample included such a wide range of grades, we control for the student’s grade level in the base year. To control forstudent academic ability, we included Peabody Picture Vocabulary Test scores (PPVT). Finally, we controlled for school sector(public or private), whether the student’s school is located in a rural, suburban, or urban location, the region of the country inwhich the school is located, and the size of the student body.8

2.5. Analytic techniques

We used logistic regression to predict whether a student dropped out of high school based upon the characteristics ofthe individual student and the characteristics of his/her friends. All predictors used in the analyses come from the in-school wave of data collection conducted in the fall of 1994. The one exception is an individual’s PPVT score, whichwas measured in the first wave of in-home data collection (spring 1995). In order to account for the structure of the data,whereby students are nested within schools, we present clustered standard errors (StataCorp, 2007). Following Winshipand Radbill (1994), we did not adjust for oversampling of specific demographic groups in our regressions but instead in-cluded the stratifiers (i.e., variables indicating the stratification criteria by which students were selected) as controls in ourmodels.9

We used Stata’s ICE platform for multiple imputation of missing values on covariates in the analyses (Royston,2005).10 For missing values measuring attributes of individuals in the analytic sample, five datasets were constructedand analyzed simultaneously. Missing values for students’ friends were imputed using a single imputation prediction beforethe measures of the average characteristics of one’s friends were created.11 The dependent variable of dropout was used asa covariate in imputing values for individual characteristics but no values of missing dropout were imputed (von Hippel,2007).

7 While we think that this cut-point (5 to 3 vs. 2 to 0 activities) reasonably distinguishes between more and less intense interactions between friends, onecould argue for different cut-points that define whether a friend is ‘‘close’’ or ‘‘distant.’’ We performed numerous analyses (results not shown) with differentcut-points for shared activities to examine how sensitive our results were to this decision. We briefly describe these findings in ‘‘results’’ section of the paper.

8 We also ran fixed effect models that eliminated all between school variance in dropping out. These models controlled for any confounding between schoolfactors that might explain our findings. These models produced findings that were nearly substantively identical to the results presented in the paper. Giventhat our main variables of interest focus on within school variance in friendship ties, it is not surprising that the fixed effects models had little impact on theresults.

9 We ran additional analyses to check whether the key stratifying variables (e.g., race-ethnicity) interacted with our main independent variables. We foundno significant interactions. We also ran our models with and without weights, and found no substantive differences in either the size or significance of our keyindependent variables.

10 We did not impute information for individuals where the question merely did not apply to the individual. For instance we did not impute a course grade ina science class if a student did not report taking a science course the previous semester. This leads to two instances where cases were dropped from the sample.First, 13 students did not report taking a science, English, math, or history course and thus could have no GPA measure constructed. Also, 404 students reportednot living with a mother/father, or adult guardian and thus could not have parental characteristics constructed. Finally, we exclude 215 individuals who hadmissing information on more than two-thirds of the variables included in the analyses.

11 Although we used multiple imputation techniques to account for missing values on covariates, the sample size changes between the models presented inTables 2–4. After imputation, we still did not have complete information on students’ friends as there were instances where a student nominated a friend in theschool who did not participate in the in-school survey. As we drew finer distinctions between different types of friendships, the number of friends in eachcategory decreased making it more likely that all of one type of friend had missing information.

Please cite this article in press as: Carbonaro, W., Workman, J. Dropping out of high school: Effects of close and distant friendships. SocialSci. Res. (2013), http://dx.doi.org/10.1016/j.ssresearch.2013.05.003

296 3. Results

297 3.1. Differences in peer characteristics among dropouts and high school graduates

298 Table 1 presents the descriptive statistics for the covariates used in the analyses by dropout status. We ran independent299 sample t-tests for each pair of means in the table, and noted the means that are not statistically significant at alpha = .05.300 Significant differences were observed for almost all of the means presented in Table 1. High school graduates have higher301 GPAs, report lower levels of deviance, and are more likely than dropouts to report being ‘‘certain’’ that they will receive a302 college degree (55% vs. 34%). These findings are consistent with prior studies on dropouts (Rumberger, 1987). We also see303 important differences among students’ friendship networks. The friends of dropouts have significantly lower grade point304 averages than the friends of those who completed high school. On average, dropouts have friends who earn GPA’s one-quar-305 ter of a letter grade below the friends of high school completers. In addition, the friends of students who dropped out report306 higher levels of deviant behavior. The difference in friends’ deviant behavior for dropouts and completers is approximately307 one-third of a standard deviation. Finally, fewer students who dropped out of high school have a lower proportion of friends308 who are certain they will graduate from college (.55 vs. .45). Also, students who eventually drop out from school are more309 likely to have friends who are dropouts. Of all friends of dropouts, 23% were students who also eventually dropped out from

Table 1Descriptive statistics by high school completion status.

Variable Completers (N = 9063) Drop outs (N = 1325) SD Min Max

Student’s ownGPA 2.89 2.25 0.79 1.00 4.00Deviance 1.04 1.63 1.05 0.00 6.00College certainty 0.55 0.34 0.50 0.00 1.00Number of extracurricular activities 2.50 1.74 2.13 0.00 10.00Attachment 3.61 3.33 0.97 1.00 5.00Engagement 3.24 2.91 1.25 1.00 5.00PPVT score 54.43 39.06 28.84 0.00 100.00

Friends’GPA 2.88 2.63 0.49 1.00 4.00Deviance 1.10 1.30 0.63 0.00 6.00College certainty 0.55 0.45 0.27 0.00 1.00Number of extracurricular activities 2.60 2.20 1.24 0.00 10.00Attachment 3.68 3.57 0.55 1.00 5.00Engagement 3.24 3.09 0.64 1.00 5.00Drop out risk 1.07 1.35 0.78 0.13 7.53Number of friends 5.54 4.73 3.37 0.00 10.00Social isolate 0.13 0.21 0.35 0.00 1.00Percentage of drop out friends 0.09 0.23 0.26 0.00 1.00

Nl

Q6

W. Carbonaro, J. Workman / Social Science Research xxx (2013) xxx–xxx 7

YSSRE 1529 No. of Pages 16, Model 3G

28 May 2013

Reciprocated friends’ dropout risk 0.86 1.00 0.86 0.12 7.53Unrequited friends’ dropout risk 1.04 1.28 0.86 0.13 6.34Strong tie dropout risk 1.27 1.52 0.72 0.12 6.81Weak tie dropout risk 1.20 1.54 0.69 0.13 7.53Number of reciprocated friends 1.89 1.24 1.76 0.00 9.00Number of Unrequited friends– 3.65 3.49 2.74 0.00 10.00Number of strong ties 1.53 1.29 1.80 0.00 10.00Number of weak ties 4.00 3.44 2.96 0.00 10.00No reciprocated friends 0.16 0.21 0.37 0.00 1.00No unrequited friends> 0.04 0.04 0.20 0.00 1.00No strong ties> 0.26 0.27 0.44 0.00 1.00

No weak ties> 0.05 0.05 0.21 0.00 1.00

ControlsParental dropout 0.103 0.227 0.323 0 1Parental college grad 0.469 0.263 0.500 0 1Black 0.182 0.172 0.385 0 1Latino 0.052 0.083 0.230 0 1Asian 0.075 0.035 0.254 0 1Native American 0.008 0.024 0.101 0 1Other race 0.012 0.008 0.108 0 1Multiple race 0.172 0.238 0.385 0 1Female 0.552 0.499 0.498 0 1Grade 9.722 9.160 1.161 7 12Born in US 0.911 0.922 0.282 0 1

ote: For each difference in the point estimates for completers and dropouts, a t-test was run to see the difference was statistically significant at the .05evel. Almost all of the differences were significant; only variables denoted with a ‘‘>’’ were not significantly different at .05.

Please cite this article in press as: Carbonaro, W., Workman, J. Dropping out of high school: Effects of close and distant friendships. SocialSci. Res. (2013), http://dx.doi.org/10.1016/j.ssresearch.2013.05.003

310

311

312

313

314

315

316

317

318

319

320

321

322

323

324

325

326

327

328

Q4

8 W. Carbonaro, J. Workman / Social Science Research xxx (2013) xxx–xxx

YSSRE 1529 No. of Pages 16, Model 3G

28 May 2013

school. In comparison, only 9% of the friends of students who completed high school dropped out. This corroborates previousresearch which found at-risk students tend to associate with other at-risk students (Cairns et al., 2003). However, it is impor-tant to emphasize that future dropouts are not clustered into small friendship groups composed only of disengaged studentsbut are more integrated into the school social network: three-quarters of the friends of dropouts finished high school.

Students who eventually drop out of high school experience more social isolation in the school. Dropouts nominated 0.8fewer friends than did students who completed school. Consistent with prior research (Farmer et al., 2003; Jimerson et al.,2000; Risi et al., 2003), high school dropouts are almost twice as likely (21% vs. 13%) as completers to be social isolates (whodid not nominate any friends in the school).

3.2. The importance of friendship characteristics

Our first multivariate models serve as a ‘‘conventional’’ analysis that examines whether a student’s friends’ characteristicsaffect his/her chances of dropping out, net of a student’s own characteristics. Model 1 in Table 2 shows the association be-tween the characteristics of a student’s friends and his/her likelihood of dropping out while controlling for the student’s owncharacteristics and characteristics of the school the student attends. Similar to prior research, we do not distinguish differenttypes of friendships in these models. This provides a baseline for comparison with our subsequent models.

Table 2Logistic regression of student dropout on average of friends’ characteristics.

Model 1 Model 2

b S.E. b S.E.

Student’s ownGPA �0.664*** 0.053 �0.668*** 0.053Deviance 0.315*** 0.039 0.316*** 0.040College certainty �0.226** 0.082 �0.243** 0.082Number of extracurricular activities �0.075*** 0.021 �0.082*** 0.021Attachment �0.029 0.037 �0.036 0.038Engagement 0.007 0.035 0.005 0.035PPVT score �0.012*** 0.002 �0.013*** 0.002

Friends’GPA �0.210** 0.077Deviance 0.048 0.046College certainty �0.553*** 0.147Number of extracurricular activities �0.069 0.036Attachment 0.005 0.070Engagement �0.091 0.052Dropout risk 0.256*** 0.051Number of friends �0.029* 0.012 �0.032** 0.012Social isolate 0.305** 0.116 0.522*** 0.129

ControlsParental drop out 0.272* 0.113 0.276* 0.113Parental college graduate �0.253** 0.085 �0.266** 0.086Black �0.229* 0.115 �0.237* 0.111Latino 0.016 0.116 0.035 0.116Asian �0.100 0.177 �0.142 0.177Native American 0.313 0.315 0.322 0.308Other race �0.537 0.331 �0.564 0.331Multiple race 0.011 0.113 0.019 0.113Female �0.112 0.077 �0.119 0.078Grade �0.346*** 0.031 �0.340*** 0.030Born in the US 0.231 0.120 0.215 0.118Intercept 4.492*** 0.665 2.987*** 0.519N 10,388 10,388

Note: Analyses include controls for parental occupation, the size of the student body, school sector, urban/suburban/rural location of the school, andgeographic region of the country.* p < .05.** p < .01.*** p < .001.

The characteristics of a student’s friends are related to his/her chances of dropping out (net of his/her own characteris-tics). Students whose friends have a high GPA are significantly less likely to drop out of high school. In addition, the propor-tion of a student’s friends who are ‘‘certain’’ they will graduate from college is negatively associated with the risk of droppingout. Greater deviant activity by one’s friends was positively related to dropping out, although the coefficient was not signif-icant at .05. The size of a student’s friendship network is also an important predictor of student drop out: students who have

Please cite this article in press as: Carbonaro, W., Workman, J. Dropping out of high school: Effects of close and distant friendships. SocialSci. Res. (2013), http://dx.doi.org/10.1016/j.ssresearch.2013.05.003

329 more friends at school are less likely to drop out. Finally, we find a significant, positive association between social isolation330 and dropping out, which is consistent with prior research (e.g., DeLuca and Rosenbaum, 2004).12

331 Model 2 of Table 1 introduces friends’ dropout risk as a summary measure taking into account the six achievement-re-332 lated characteristics shown in Model 1. As described earlier, the risk of drop out measure was created by summing the prod-333 uct of a friend’s observed characteristic (such as GPA) and the characteristic’s association with drop out (coefficient from334 logistic regression). Not surprisingly, the risk of drop out among a student’s friends is strongly and positively related to335 the student’s own likelihood of dropping out. The effect of being a social isolate remains significant in Model 2. Students336 who are socially isolated in school are more likely to drop out.

337 3.3. Affective intensity of friendship ties

338 The next set of analyses examines whether the level of emotional closeness of friendships affect a student’s risk of drop-339 ping out. In these analyses, we examined two kinds of friendships: reciprocated friendships, where both students identified340 each other as a friend and unrequited friendships, where the student listed another student as a friend, but the other student341 did not reciprocate. We argue that reciprocated friendships represent a stronger affective tie, while unrequited friendships342 are a weaker type of relationship. We predict that the characteristics of distant friendships have the largest effect on a stu-343 dent’s risk for dropping out.344 Model 1 in Table 3 includes measures of the average drop out risk of students’ reciprocated and unrequited friends. In345 addition to the characteristics of students’ friends, we are also interested in the size of students’ friendship networks. The346 model includes measures of the size of the friendship network (number of friends) for both types of relationships. Finally,347 we include a dummy variable adjustment for those students who do not have friendships of each type, which also serves348 as a measure of social isolation. The inclusion of these variables allows us to examine whether students who lack friendships349 of a certain type (reciprocated/unrequited) have an increased probability of dropping out of high school.350 The results in Model 1 of Table 3 indicate that the characteristics of friends with whom students share less of an emo-351 tional relationship are especially important for students’ chances of dropping out, but the characteristics of friends who352 share a strong emotional bond are not. The drop out risk for a student’s reciprocated friends is not significantly related to353 whether the student completes school (although the coefficient is positive). In contrast, a student’s risk of dropping out is354 significantly related to the risk of dropping out among their unrequited friends. We ran a Wald test to examine the likelihood355 that the reciprocated and unrequited friendship coefficients were significantly different from in each other in the population.356 The chi-squared probability was .016, which indicates we can reject the null hypothesis (that the two coefficient are equal) at357 alpha = .05.358 Overall, the findings indicate that unrequited friends’ risk of dropping out increases a student’s own chances of dropping359 out (above and beyond the student’s own characteristics), but reciprocated friends with a high risk of drop out do not affect a360 students’ risk of dropping out. To better understand the magnitude of these relationships, we plotted predicted probabilities361 of drop out by friends’ dropout risk for both reciprocated and unrequited relationships (see Fig. 1). As the figure shows, an362 increase in the risk of dropout for a student’s unrequited friends from .01 to .30 nearly doubles a student’s own chances of363 dropping out (from .06 to .11). In contrast, the same increase in the risk of dropout among a student’s reciprocated friends364 does not lead to a substantial increase in the student’s own chances of dropping out.365 The size of one’s friendship network is also related to the risk of dropping out. However, for network size, strong emo-366 tional bonds are more influential than less emotional ones. The number of reciprocated friendship ties is positively related367 to high school graduation. The size of a student’s less emotional friendship network is not as strongly related to dropping368 out; the coefficient for the number of unrequited friendships is not statistically significant. This finding is consistent with369 other studies that suggest students who have more close friendships in school are less likely to dropout (South et al.,370 2007; Staff and Kreager, 2008; Vaquera and Kao, 2006). If students are coming to school because they enjoy being with their371 friends, we would expect that additional close friendships would help keep students in school. Since more distant friends do372 not have the same affective ‘‘pull’’ for students, it is not surprising that larger numbers of less emotional friendships are not373 strongly related to dropping out. Consistent with the findings presented earlier, social isolates, students who did not make374 any friendship nominations to other students in the school, are more likely to drop out of school. However, students who lack375 any reciprocated friendships are not more or less likely to complete school than other students. Finally, having a friendship376 network that consists only of reciprocated ties (thus lacking unrequited ties) is not significantly related to school dropout.

377 3.4. Intensity of friendship ties: close and distant ties based on degree of shared interactions

378 The next set of analyses examines a second operationalization of the closeness of students’ friendships: whether the ef-379 fects of students’ friends vary based on how regularly students interact with each other. Students who spend more time with380 each other are considered close friendships, while those who spend little time with each other are considered distant friends.

12 For social isolates, mean values were imputed on friends’ achievement-related characteristics so the observations are not excluded from the analysisthrough list-wise deletion. Allison (2002) asserts that such an adjustment is entirely appropriate when values do not exist (p. 87). Since students withoutfriends in a school (by definition) have no valid value for measures of friends’ characteristics, mean substitution with dummy variable adjustment isappropriate in this case.

W. Carbonaro, J. Workman / Social Science Research xxx (2013) xxx–xxx 9

YSSRE 1529 No. of Pages 16, Model 3G

28 May 2013

Please cite this article in press as: Carbonaro, W., Workman, J. Dropping out of high school: Effects of close and distant friendships. SocialSci. Res. (2013), http://dx.doi.org/10.1016/j.ssresearch.2013.05.003

Table 3Logistic regression of student dropout on characteristics of close and distant tie friends.

Model 1 Model 2 Model 3

b S.E. b S.E. b S.E.

Student’s ownGPA �0.677*** 0.058 �0.692*** 0.059 �0.687*** 0.058Deviance 0.310*** 0.041 0.299*** 0.039 0.301*** 0.039College Certainty �0.260** 0.086 �0.264** 0.086 �0.262** 0.086Number of Extracurricular Activities �0.073*** 0.021 �0.076*** 0.022 �0.075*** 0.022Attachment �0.019 0.039 �0.024 0.039 �0.022 0.040Engagement �0.005 0.035 �0.005 0.035 �0.005 0.035PPVT score �0.012*** 0.002 �0.012*** 0.002 �0.012*** 0.002

Dropout risk ofReciprocated Friends 0.075 0.045 0.015 0.067Unrequited Friends 0.219*** 0.041 0.054 0.072Close friends 0.025 0.047 0.002 0.063Distant friends 0.295*** 0.047 0.252** 0.077

***

10 W. Carbonaro, J. Workman / Social Science Research xxx (2013) xxx–xxx

YSSRE 1529 No. of Pages 16, Model 3G

28 May 2013

Number of reciprocated friends �0.182 0.037Number of unrequited friends �0.001 0.015Number of close friends �0.003 0.034Number of distant friends �0.036* 0.015Number of friendsa �0.028 0.015Social isolate 0.412* 0.172 0.304* 0.134 0.381 0.217No reciprocated friends �0.079 0.139 0.182 0.151No unrequited friends 0.316 0.194 �0.054 0.199No close friends 0.063 0.114 �0.035 0.080No weak friends 0.264 0.165 0.301 0.174

ControlsParental drop out 0.273* 0.116 0.279* 0.117 0.277* 0.117Parental college graduate �0.280** 0.095 �0.285** 0.096 �0.283** 0.095Black �0.322** 0.110 �0.280* 0.111 �0.288** 0.110Latino 0.007 0.119 0.008 0.117 0.011 0.117Asian �0.130 0.177 �0.104 0.179 �0.113 0.179Native American 0.280 0.320 0.293 0.313 0.293 0.313Other race �0.630 0.339 �0.579 0.332 �0.594 0.335Multiple race �0.019 0.115 �0.001 0.115 �0.006 0.114Female �0.089 0.077 �0.126 0.077 �0.114 0.077Grade �0.320*** 0.031 �0.328*** 0.031 �0.326*** 0.031Intercept 3.045*** 0.567 2.937*** 0.587 2.884*** 0.603N 9454 9454 9454

Note: Analyses include controls for parental occupation, the size of the student body, school sector, urban/suburban/rural location of the

school, and geographic region of the country.

a

A model estimating separate coefficients for a student’s number of reciprocated friends, unrequited friends, close friends, and distantfriends encountered collinearity. For the ‘combined model’ presented in Model 3 of Table 3 we instead use the student’s total number offriends.* p < .05.** p < .01.*** p < .001.

Fig. 1. Effect of reciprocated and unrequited friends’ characteristics on predicted probability of drop out.

Please cite this article in press as: Carbonaro, W., Workman, J. Dropping out of high school: Effects of close and distant friendships. SocialSci. Res. (2013), http://dx.doi.org/10.1016/j.ssresearch.2013.05.003

381 M382 a383 f384

385 c386 p387 o388 a389 t390

391 e392 s393 T394

395 s396 s397 o398 s399

400 o

401 3

402

403 e404 t405 t406

407 d408 c409 d410 b

Fig. 2. Effect of close and distant friends’ characteristics on predicted probability of drop out.

TO

OGNa

W. Carbonaro, J. Workman / Social Science Research xxx (2013) xxx–xxx 11

YSSRE 1529 No. of Pages 16, Model 3G

28 May 2013

odel 2 of Table 3 shows how these different friendship configurations are related to a student’s risk of dropping out (net ofstudent’s own characteristics). As with Model 1, Model 2 includes the average probability of dropping out for each type of

riendship as well as measures of the number of friends and an adjustment for those who lack any friendships of each type.Our findings indicate that the characteristics of more distant friends are more influential on whether or not a student

ompletes school. The risk of drop out among distant friends is significantly and positively related to a student’s risk of drop-ing out. However, the risk of dropping out of close friends is not significantly related to a student’s own probability of droput. We examined the likelihood that the coefficients for the dropout risk of close and distant friends were equal by runningWald test. The results indicated that we can reject the null hypothesis at alpha = .001, and consequently, it is highly likely

hat the coefficients are different in magnitude.Recall that ‘‘distant’’ friends are those with two or fewer shared activities. We ran additional models that separately

xamined friends with two, one, and zero shared activities (results not shown). Each of these indicators showed a positive,ignificant relationship with dropping out, which is consistent with the ‘‘two or fewer activities’’ measure used in model two.hese additional analyses indicate that ‘‘two or fewer’’ activities is an empirically important cut-point in friendship distance.

Fig. 2 translates the coefficients in Model 2 into predicted probabilities to help interpret the magnitude of the relation-hips described above. The figure shows that an increase in the risk of dropout from .01 to .30 for a student’s distant friend-hips more than doubles their own chances of dropping out (from .06 to .13). However, the same increase in the risk of droput among students’ close friends does not lead to a substantial increase in the student’s own probability of dropping out of

chool.

In terms of network size, the number of close friendships is not significantly related to a student’s chances of droppingut. However, the coefficient for number of distant friends is marginally significant and negative.

.5. The full model

Models 1 and 2 in Table 3 examine our two measures of friendship ties (affect and shared interactions) separately. How-ver, it is likely that these means of classifying friendships are related to one another. Students will likely prefer to spendime with companions who also value the friendship (as compared to unrequited friends). In addition, the perceived emo-ional bond among members of a friendship is likely to be influenced by the amount of interaction.

Table 4 indicates how the affective and shared-interaction dimensions of student friendships are related. Overall, stu-ents’ social networks are mostly composed of less intimate friendships. On average, students have half as many recipro-ated friendship ties (1.816) as unrequited friendship ties (3.627). In addition, students have more than twice as manyistant friendship ties (3.951) as close friendships (1.493) (based on their shared activities). When we look at the overlapetween our two measures, 41% of students’ reciprocated friendships were also classified as ‘‘close’’ friendships and 59%

able 4verlap in the number of different types of friendships.

Total Number of close friendships Number of distant friendships

Number of reciprocated ties 1.816 (100%) 0.750 (41%) 1.067 (59%)Number of unrequited ties 3.627 (100%) 0.743 (21%) 2.884 (79%)

Total 5.444 1.493 3.951

dds ratio = (.59/.41)/(.79/.21) = 2.70.amma = .335.ote: The calculations are based upon 9454 individuals with 51,468 friendships. The gamma coefficient is calculated based upon the number of concordantnd discordant pairs of observations. The unit of analysis in calculating the gamma coefficient is the relationship tie.

Please cite this article in press as: Carbonaro, W., Workman, J. Dropping out of high school: Effects of close and distant friendships. SocialSci. Res. (2013), http://dx.doi.org/10.1016/j.ssresearch.2013.05.003

411

412

413

414

415

416

417

418

419

420

421

422

423

424

425

426

427

428

429

430

431

432

433

434

435

436

437

438

439

440

441

442

443

444

445

446

447

12 W. Carbonaro, J. Workman / Social Science Research xxx (2013) xxx–xxx

YSSRE 1529 No. of Pages 16, Model 3G

28 May 2013

Table 5Supplemental analyses predicting students’ acne, coordination, and sickness using the average attributes of reciprocated, unrequited, close, and distant friends.

Acne Coordination Sickness

Model 1 Model 2 Model 1 Model 2 Model 1 Model 2

Average attribute ofReciprocated friends 0.065��� 0.058��� 0.059���

(0.018) (0.015) (0.018)Unrequited friends 0.028 0.014 0.041��

(0.021) (0.021) (0.016)Close friends 0.066�� 0.047�� 0.043�

(0.020) (0.018) (0.018)Distant friends 0.030 0.026 0.047�

(0.021) (0.024) (0.018)

were classified as ‘‘distant’’ based upon the number of shared activities. Thus, reciprocated ties are slightly less likely to beclose ties rather than distant ties. In contrast, among unrequited friendships, only 21% were classified as ‘‘close’’ while 79%were classified as ‘‘distant.’’ Unrequited ties are four times less likely to be close rather than distant friendship ties. We cal-culated an odds ratio to compare the odds of distant friendships among reciprocated and unreciprocated ties, and found thatdistant ties are 2.6 times more likely to be unrequited ties than reciprocated ties.13 In short, students are more likely to engagein shared activities and spend more time with their reciprocated friends than their unrequited friends. While there is overlapbetween our two dimensions of student friendships, there is also substantial independence between them.

Since students are more likely to spend more time with their reciprocated friends, it is important to examine a ‘‘full mod-el’’ (Model 3 of Table 3) with both dimensions of friendships ties in the same regression. In this model, the dropout risk ofunrequited friendship ties is no longer significantly related to a student’s own risk of dropping out. However, students withdistant friends who have a higher dropper risk remain significantly more likely to drop out. While the magnitude of the coef-ficient for the dropout risk of ‘‘unrequited’’ friends drops substantially in model three, the ‘‘distant’’ friend dropout risk coef-ficient only decreases by 15%. The dropout risk of one’s close friends is completely unrelated to one’s own risk of droppingout in Model 3. A Wald test comparing the ‘‘close’’ and ‘‘distant’’ friend coefficients is significant at alpha = .01, which indi-cates that the coefficients are likely to differ in magnitude. In short, our full model shows that shared interaction rather than‘‘affect’’ is the most important friendship dimension in predicting a student’s chances of dropping out.

3.6. Potential impact of selection bias on findings

Any study of peer effects must consider the process by which students self-select into peer groups, and how self-selectionmay undermine claims regarding causality (Mouw, 2006). Fortunately, the longitudinal design of Add Health allows us toobserve student friendship ties in wave one, well before most students drop out (measured at wave three). Despite theadvantage of proper time ordering in the data, selection bias remains a concern since some students may possess an under-lying trait that explains both their choices in friends and their decision to drop out of high school. While we cannot eliminatethis possibility, we offer several reasons why a causal interpretation of our findings is plausible.

First, prior research with longitudinal data on friendships, networks, and academic performance suggests that students’outcomes (e.g., grades) become more like their friends over time (Steinberg, 1996). Studies of disruptive behavior in schooland peers reach a similar conclusion (e.g., Berndt and Keefe, 1995; Kandel, 1978). Thus, while we should be cautious aboutinferring causality from our findings, these studies suggest that such an interpretation is quite plausible. Second, the self-selection argument (driven by the preference for homophily) would predict that closer friends’ characteristics are strongerpredictors of a student’s risk of dropping because there is more self-selection in those relationships. However, our findingssuggest the opposite, and it seems much less likely that this pattern is consistent with a ‘‘self-selection’’ explanation.

Finally, we devised some supplementary analyses (see Table 5) that examined how vulnerable our analyses might be toselection bias. We examined three student characteristics in which we expected some similarity between students and theirfriends but did not expect friends to have a causal influence on the student’s attributes. These included how often the stu-dent: ‘felt really sick’; had skin problems, such as itching or pimples, in the past month; and the extent to which the studentfeels he or she is well-coordinated. Since we expect homophily to underlie the friend-ego relationship on these outcomes,close friends’ characteristics should be more strongly related to the students’ characteristics than their distant friends’characteristics.

Note: Models also include controls for student achievement characteristics, size of friendship network, and demographic controls (modeling corresponds tothat of Table 3). Standard errors in parentheses.

13 The gamma coefficient is used to assess the direction and strength of relationship between two ordinal level variables. The gamma coefficient of .335 fortable four indicates that there is a moderate positive association between the two measures friendship ties, which means that unrequited ties are more likely tobe distant ties.

Please cite this article in press as: Carbonaro, W., Workman, J. Dropping out of high school: Effects of close and distant friendships. SocialSci. Res. (2013), http://dx.doi.org/10.1016/j.ssresearch.2013.05.003

448

449 c450 c451 d452

453 c454 a455 fi456 s457 s458 r

459 4

460

461 s462 2463 f464 i465 a466

467 w468 f469 a470 c471 c472 a473 i474 d475 t476 c477 o478 w479 a480

481 m482 t483 1484 o485 t486 H487 e488 s489

490 n491 t492 e493 s494 n495 s496 f497 f498

499 e500 l501 i502 m503 p504 d505 l

W. Carbonaro, J. Workman / Social Science Research xxx (2013) xxx–xxx 13

YSSRE 1529 No. of Pages 16, Model 3G

28 May 2013

We constructed measures that assessed the average illness, skin problems, and coordination among a student’s recipro-ated and unrequited friends. In addition, we constructed measures that assessed the average illness, skin problems, andoordination among a student’s close and distant friends. We ran the same models as those presented in Table 3, but withifferent outcomes and friends’ characteristics.

The results (displayed in Table 5) indicate that for coordination and skin problems, a student’s reciprocated friends’ andlose friends’ characteristics had positive, significant associations with the students’ own characteristics. However, the char-cteristics of their unrequited or distant friends were not significantly related to their own characteristics. For sickness, wend that the sickness of both reciprocated and unrequited friends is positively and significantly related to the student’s ownickness. In addition, the sickness of both close and distant friends is positively and significantly related to the student’s ownickness. Thus, the pattern in Table 5, which we assume is largely driven by self-selection, is markedly different from theesults of our analyses of dropping out.

. Discussion

Prior research finds that students with more academically oriented and successful friends are more likely to finish highchool, net of a student’s own characteristics (e.g., Battin-Pearson et al., 2000; Cairns et al., 1989; Ream and Rumberger,

008; Staff and Kreager, 2008). The main contribution of our study is our analytical distinction between close and distant

riendships, combined with information about the number and characteristics of these friendships. Our analyses captured var-ation in the number of friendships, the kinds of relationships (intensity of the friendship) and kinds of friends (a friend’sttributes) a student has.

Our results consistently show that students with more close friendship ties have a lower risk of dropping out. However,e also found that the characteristics of students’ distant friends are more influential than the characteristics of their close

riends. The risk of dropping out for students’ unrequited friends – the more distant friendship type in our analysis – hadstrong association with a student’s own risk of dropping out. In contrast, the risk of dropping out for a student’s recipro-

ated friends – a student’s closest friendship – was not significantly related to a student’s risk of dropping out. This finding isonsistent with social identity theory and Harris’s framework: friends about whom students have less intimate informationre more likely to serve as normative models that define which behaviors are expected and/or permissible. We also found an

nverse relationship between how often students and friends interact and the risk of dropping out. A student’s own risk of ropping out is not significantly related to the dropout risk for friends with whom students interact most regularly. In con-rast, friends that students interact with least regularly have the largest impact on a student’s risk of dropping out. In ourombined model, we attempted to account for the degree of overlap between our two ways of categorizing the closenessf friendships. We found that friends with whom students shared fewer interactions were more influential than friendsho constituted unrequited relationships for the student. While these findings may strike some as counterintuitive, they

re entirely consistent with the predictions generated by our theoretical framework.Overall, our findings suggest that prior research on friends and dropping out has not adequately accounted for which peers

atter most in the process of dropping out. This is an important empirical contribution with significant theoretical implica-ions because it addresses the underlying issue of why peers matter. Coleman (1988) and others (Hallinan and Williams,991; South et al., 2007; Vaquera and Kao, 2008) argue that the density and the strength of friendships matter becausef the availability and trust in peers who can serve as models for behavior. Our findings support a different theoretical modelhat focuses on the importance of distant social relationships and a different theory about how socialization processes work.arris’s (2006) synthesis of insights from cognitive psychology and social identity theory (Hogg et al., 1995) provides a pow-rful framework for interpreting our results. While sociologists were correct to highlight the importance of socialization fortudents, our findings suggest a rethinking of where and how socialization occurs.

Our findings also suggest that future research should focus on three important features of student friendships: theumber of friendships, the closeness/intensity of the friendship, and the characteristics of students’ friends. Prior effortso measure the effects of ‘‘social capital’’ and/or ‘‘peer effects’’ (e.g., Carbonaro, 1998; Morgan and Todd, 2009; Southt al., 2007; Vaquera and Kao, 2008) have been incomplete because they have only measured one or two of these dimen-ions. Since our models capture all three dimensions of student friendships, we are able to tell a more theoreticallyuanced story of how students’ friends affect their chances of dropping out of high school. We acknowledge that our mea-ures of ‘‘close’’ and ‘‘distant’’ ties have limitations. Accurately measuring the quality social ties is a major challenge, anduture researchers should focus on how to better capture the affective character, and degree of shared interaction amongriends.

Consistent with our theory and findings, we argue that distant friendships likely play an important role in this process bystablishing the normative environment for students. Students can easily devise unique explanations for the actions and be-iefs their close friends because they know them so well. Students view their close friends’ actions as an outgrowth of theirndividual circumstances and personality, rather than what’s normative for their group. However, students have less infor-

ation about their more distant friends and consequently they rely on social categories to interpret their behaviors. We sus-ect that dropouts rarely experience ‘‘peer pressure,’’ as conventionally understood: friends who actively urge students toropout and/or punish them for non-compliance are likely rare. Rather, distant friends implicitly endorse the behaviors that

ead to dropping out as normatively acceptable, and dropouts within this group make the failure to finish high school a

Please cite this article in press as: Carbonaro, W., Workman, J. Dropping out of high school: Effects of close and distant friendships. SocialSci. Res. (2013), http://dx.doi.org/10.1016/j.ssresearch.2013.05.003

506

507

508

509

510

511

512

513

514

515

516

517

518

519

520

521

522

523

524

525

526

527

528

529

530531532533534535536537538539540541542543544545546547548549550551552553554555556557558559560561562563564565566567568

Q5

14 W. Carbonaro, J. Workman / Social Science Research xxx (2013) xxx–xxx

YSSRE 1529 No. of Pages 16, Model 3G

28 May 2013

seemingly viable option for students ‘‘like us.’’ As Harris (2006) notes, the socialization system typically works ‘‘under theradar’’ and most individuals do not recognize how peers affect their own behavior.

Future research that describes how the process of dropping out unfolds over time would be extremely helpful in evalu-ating the role that friends and peers play in events and choices that lead students to leave high school. Since the networkdata in Add Health is only measured in the first wave, we cannot reach any conclusions about how changes in students’ net-works affect their risk of dropping out. For example, how stable are students’ close and distant friendship networks? Do closefriends become distant, and vice versa? And which friends (close or distant) become non-friends in later waves? It is possiblethat these changes are consequential for students’ risk of dropping out. Also, does a close or distant friendship with a studentwho eventually drops out have an effect on a student’s own chances of dropping out? Observing a close or distant friendleave school may have a different effect than having friendship ties with students who are simply ‘‘at-risk’’ for droppingout. By understanding how specific events and choices lead students to leave high school, future researchers should betterable to understand how different types of friendships affect a student’s chances of finishing high school.

5. Uncited references

Ross et al. (1977) and US Department of Education, National Center for Educational Statistics (2004).

Acknowledgments

This research uses data from Add Health, a program project designed by J. Richard Udry, Peter S. Bearman, and KathleenMullan Harris, and funded by a Grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health andHuman Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is

due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Persons interested in obtaining data filesfrom Add Health should contact Add Health, Carolina Population Center, 123W. Franklin Street, Chapel Hill, NC 27516-2524(Add Health@unc.edu). No direct support was received from Grant P01-HD31921 for this analysis. An earlier version of thispaper was presented at 2009 Annual Meetings of the American Educational Research Association. The authors would like tothank Guillermo Montt, Carolyn Riehl, and Elizabeth Covay for helpful feedback on this paper.

References

Akerlof, George, Kranton, Rachel, 2002. Identity and schooling: some lessons for the economics of education. Journal of Economic Literature XL, 1167–1201.Akerlof, George, Kranton, Rachel, 2010. Identity Economics: How Our Identities Shape Our Work, Wages, and Well-being. Princeton University Press,

Princeton, New Jersey.Allison, Paul, 2002. Missing Data. Sage Publications, Thousand Oaks, California.Battin-Pearson, Sara, Newcomb, Michael, Abbott, Robert, Hill, Karl, Catalano, Richard, David Hawkins, J., 2000. Predictors of early high school dropout: a test

of five theories. Journal of Educational Psychology 92, 568–582.Berndt, Thomas, Keefe, Keunho, 1995. Friends influence on adolescents adjustment to school. Child Development 66, 1312–1329.Call, Kathleen, Mortimer, Jeylan, 2001. Arenas of Comfort in Adolescence: A Study of Adjustment in Context. Laurence Erlbaum Associates, Mahwah, New

Jersey.Cairns, Robert, Cairns, Beverly, Neckerman, Holly, 1989. Early school dropout – configurations and determinants. Child Development 60, 1437–1452.Carbonaro, William, 1998. A little help from my friend’s parents: intergenerational closure and educational outcomes. Sociology of Education 71, 295–313.Carbonaro, William, 1999. Opening the debate on closure and schooling outcomes: comment on Morgan and Sorensen. American Sociological Review 64,

682–686.Cavanaugh, Shannon, Schiller, Kathryn, Riegle-Crumb, Catherine, 2006. Marital transitions, parenting, and schooling: exploring the link between family–

structure. Sociology of Education 79, 329–354.Coleman, James, 1961. The Adolescent Society. The Free Press of Glencoe, Oxford, England.Coleman, James, 1988. Social capital in the creation of human capital. American Journal of Sociology 94, S95–S120.DeLuca, Stephanie, Rosenbaum, James, 2004. Are dropout decisions related to safety concerns, social isolation, and teacher disparagement? In: Orfield, G.

(Ed.), Dropouts in America: Confronting the Graduation Rate Crisis. Harvard Education Press, Cambridge, Massachusetts.Ellenbogen, Stephen, Chamberland, Claire, 1997. The peer relations of dropouts: a comparative study of at-risk and not at-risk youths. Journal of

Adolescence 20 (4), 355–367.Farmer, Thomas, Estell, David, Leung, Man-Chi, Trott, Hollister, Bishop, Jennifer, Cairns, Beverly, 2003. Individual characteristics, early adolescent peer

affiliations, and school dropout: an examination of aggressive and popular group types. Journal of School Psychology 41, 217–232.Fiske, Susan, 2004. Social Beings: Core Motives in Social Psychology. Wiley, New York.Giordano, Peggy, 2003. Relationships in adolescence. Annual Review of Sociology 29, 257–281.Granovetter, Mark, 1973. The strength of weak ties. American Journal of Sociology 78, 1360–1380.Granovetter, Mark, 1983. The strength of weak ties: a network theory revisited. Sociological Theory 1, 201–233.Hallinan, Maureen, Williams, Richard, 1991. Students’ characteristics and the peer-influence process. Sociology of Education 63, 122–132.Harris, Judith, 2006. No Two Alike. W.W. Norton & Company, New York.Harris, Judith, 2009. The Nurture Assumption: Why Children Turn Out the Way They Do. Touchstone, New York, New York.Harris, Kathleen, Halpern, Carolyn, Whitsel, Eric, Hussey, Jon, Tabor, Joyce, Entzel, Pamela, Richard Udry, J., 2009. The National Longitudinal Study of

Adolescent Health: Research Design [WWW document]. <http://www.cpc.unc.edu/projects/Add Health/design>.Hogg, Michael, Terry, Deborah, White, Katherine, 1995. A tale of two theories: a critical comparison of identity theory with social identity theory. Social

Psychology Quarterly 58, 255–269.Jimerson, Shane, Byron Egeland, L., Sroufe, Alan, Carlson, Betty, 2000. A prospective longitudinal study of high school dropouts examining multiple

predictors across development. Journal of School Psychology 38, 525–549.Kindermann, Thomas, 2007. Effects of naturally existing peer groups on changes in academic engagement in a cohort of sixth graders. Child Development

78, 1186–1203.Kubitschek, Warren, Hallinan, Maureen, 1998. Tracking and students’ friendships. Social Psychology Quarterly 61, 1–15.

Please cite this article in press as: Carbonaro, W., Workman, J. Dropping out of high school: Effects of close and distant friendships. SocialSci. Res. (2013), http://dx.doi.org/10.1016/j.ssresearch.2013.05.003

569 Morgan, Stephen, Todd, Jennifer, 2009. Intergenerational closure and academic achievement in high school: a new evaluation of Coleman’s conjecture.570 Sociology of Education 82, 267–286.571 Mouw, Ted, 2006. Estimating the causal effect of social capital: a review of recent research. Annual Review of Sociology 32, 79–102.572 Newman, Philip, Newman, Barbara, 1976. Early adolescence and its conflict: group identity versus alienation. Adolescence 11, 261–274.573 Ream, Robert, Rumberger, Russell, 2008. Student engagement, peer social capital, and school dropout among Mexican American and non-Latino white574 students. Sociology of Education 81, 109–139.575 Risi, Susan, Gerhardstein, Rebecca, Kistner, Janet, 2003. Children’s classroom peer relationships and subsequent educational outcomes. Journal of Clinical576 and Adolescent Psychology 32, 351–361.577 Ross, Lee, Greene, David, House, Pamela, 1977. The false consensus effect: an egocentric bias in social perception and attribution processes. Journal of578 Experimental Social Psychology 13, 279–301.579 Royston, Patrick., 2005. Multiple imputation of missing values: update. Stata Journal 5, 188–204.580 Rumberger, Russell, 1987. High school dropouts: a review of issues and evidence. Review of Education Research 57, 101–121.581 Sewell, William, Hauser, Robert, 1980. The Wisconsin longitudinal study of social and psychological factors in aspirations and achievements. In: Kerckhoff,582 Alan C. (Ed.), Research in the Sociology of Education and Socialization. JAI, Greenwich, CT, pp. 59–100.583 Smith, J. David, 2002. Exemplar theory’s predicted typicality gradient can be tested and disconfirmed. Psychological Research 13, 437–442.584 South, Scott, Haynie, Dana, Bose, Sunita, 2007. Student mobility and school dropout. Social Science Research 36, 68–94.585 Staff, Jeremy, Kreager, Derek, 2008. Too cool for school? Peer status and high school dropout. Social Forces 87, 445–471.586 StataCorp, 2007. Stata Statistical Software: Release 10. StataCorp LP, College Station, TX.587 Steinberg, Laurence., 1996. Beyond the Classroom: Why School Reform Has Failed and What Parents Need To Do. Simon & Schuster, New York.588 Stets, Jan, Burke, Peter, 2000. Identity theory and social identity theory. Social Psychology Quarterly 63, 224–237.589 Turner, John, Hogg, Michael, Oakes, P.J., Reicher, S.D., Wetherell, M.S., 1987. Rediscovering the Social Group: A Self-categorization Theory. Blackwell, Oxford,590 England.591 US Department of Education, National Center for Educational Statistics. 2004. The Condition of Education 2004, NCES 2004-025. US Government Printing592 Office, Washington, DC.593 Youniss, James., Smollar, Jacqueline., 1985. Adolescent Relationships with Mothers, Fathers, and Friends. University of Chicago Press, Chicago.594 Vaquera, Elizabeth, Kao, Grace, 2008. Do you like me as much as i like you? Friendship reciprocity and its effects on school outcomes among adolescents.595 Social Science Research 37, 55–72.596 von Hippel, Paul., 2007. Regression with missing Y’s: an improved strategy for analyzing multiply imputed data. Sociological Methodology 37, 83–117.597 Winship, Christopher, Radbill, Larry, 1994. Sampling weights and regression analysis. Sociological Methods & Research 23, 230–257.

598

W. Carbonaro, J. Workman / Social Science Research xxx (2013) xxx–xxx 15

YSSRE 1529 No. of Pages 16, Model 3G

28 May 2013

Please cite this article in press as: Carbonaro, W., Workman, J. Dropping out of high school: Effects of close and distant friendships. SocialSci. Res. (2013), http://dx.doi.org/10.1016/j.ssresearch.2013.05.003