Simplicity and complexity in the effects of parental structure on high school graduation

Demography, Vol. 30, No.4, November 1993

Simplicity and Complexity in the Effects ofParental Structure on High School Graduation*

Roger A. WojtkiewiczDepartment of Sociology126 StubbsLouisiana State UniversityBaton Rouge, LA 70803-5411

As more and more children experience nonintact families because of nonmarital birthor parental marital disruption, researchers have paid more attention to whethernonintact family experiences have negative effects on later life. This study uses datafrom the National Longitudinal Survey of Youth to consider how experiences ofparental structure affect chances of high school graduation. The study shows that thenegative effects of parental structure are simpler than theoretical notions mightsuggest.

Research on the effects of parental structure during childhood and adolescence oneducational attainment has grown more complex over time, both in issues considered and indata used. This study uses parental history data from the National Longitudinal Survey ofYouth to consider the effects of parental structure on high school graduation. The study usesmeasures that capture the complexity of parental structure experiences, but it also considerswhether this added complexity is necessary.

BACKGROUNDThe Occupational Change in a Generation surveys (Blau and Duncan 1967; Featherman

and Hauser 1978) used a simple measure of parental structure. These surveys asked "Wereyou living with both your parents most of the time up to age l6?" Analysis of these datashowed that experiences with broken families or disrupted marriages had an adverse effecton years of school completed.

Recent research has examined the nature of these adverse effects in greater detail.Some research has considered the effects of different types of nonintact families such asnever married, divorced, or widowed (McLanahan 1985) or stepparent (Astone andMcLanahan 1991; Li and Wojtkiewicz 1992; Sandefur, McLanahan, and Wojtkiewicz1992). Other research has examined the effects of years/spent in nonintact families (Krein1986; Krein and Beller 1988; Li and Wojtkiewicz 1992). Research also has considered the

*1 appreciate the helpful advice on this paper from the editor, anonymous reviewers, Yoshinori Kamo,Nicholas Zill, Robert Hauser, Robert Mare, Yu Xie, and Sara McLanahan. This research was funded by the"Small Grants for Visitors Program," Institute for Research on Poverty, University of Wisconsin-Madison, underGrant 144-Z327 87ASPE041A from the U.S. Department of Health and Human Services.

Copyright © 1993 Population Association of America

701

702 Demography, Vol. 30, No.4, November 1993

effects of the timing, number, and kind of change in parental structure (Haveman, Wolfe,and Spaulding 1991; Li and Wojtkiewicz 1992; Sandefur et al. 1992). Each of these studiessupports the basic finding that nonintact family experiences diminish educationalattainment.

This recent research was possible only because better data became available. Some ofthese studies used longitudinal data from the Panel Study of Income Dynamics (Haveman etal. 1991; McLanahan 1985), National Longitudinal Surveys (Krein 1986; Krein and Beller1988; Sandefur et al. 1992), and High School and Beyond (Astone and McLanahan 1991).Life history data from the National Survey of Families and Households have also been used(Li and Wojtkiewicz 1992).

Two of these surveys, the National Survey of Families and Households and theNational Longitudinal Survey of Youth, include retrospective life history data on youths'experiences with parental structure from birth to age 19. These data allow for modeling ofparental structure experiences in greater detail than has been done so far. Such modeling isthe purpose of the present study. This study, however, deals with an overriding question: Isadded complexity necessary in the measurement of parental structure? Does more highlydetailed information add to our understanding of the effects of parental structure oneducational attainment?

THEORETICAL MODEL

The simplest model for the effects of parental structure on educational attainment is onethat asks whether family disruption occurred. Theory suggests, however, that the impact ofparental structure should vary depending on the nature of the experience. The effects shouldbe contingent on the types of parental structure experienced, the amount of time spent inparental structures, the age at which parental structures are experienced, and the kind ofchange in parental structure which is experienced. In addition, the effect of parentalstructure experiences might depend on family type at birth. That is, the effects may dependon whether a person started out at birth with mother and father or with mother only.

Type of Parental Structure

Children in families other than mother-father may receive less encouragement,supervision, and control than those in mother-father families (Astone and McLanahan1991). The effect of living in a nonintact family, however, depends on the type of family.Living in a single-parent family should have a more negative effect than living in astepparent family. Absent parents play only a limited role in their children's daily lives(Furstenberg and Nord 1985; Seltzer 1991). Less time is available for encouragement,supervision, and control in single-parent families, not only because there is only one parentbut also because household management falls on one person rather than on two (Krein andBeller 1988). Less time for supervision and control may mean that children associate moreoften with peers who are less supportive of educational attainment (Demo and Acock 1988;Dornbusch et aI. 1985). In addition, parent-child relations are weaker in single-parentfamilies (Hetherington 1987; Wallerstein, Corbin, and Lewis 1988).

Stepparents have weaker relationships with stepchildren than do biological parents; theresult is less encouragement, supervision, and control (Amato 1987; Furstenberg 1987; Zill1988). A stepparent, however, provides some parenting, so the negative effect of livingwith a stepparent is less than that of living with mother only. Living with only grandparents

Simplicity and Complexity 703

or other relatives should have the most negative effect on educational attainment becauseboth biological parents are missing in these situations.

Type of family also will affect educational attainment because of income differences.Mother-only families have the lowest income (Garfinkel and McLanahan 1986; U.S. Bureauof the Census 1991). Father-only families have higher income, but still have only oneearner. Stepparent families have two potential earners but may have obligations to otherhouseholds, which diminish the income available within the household.

Amount of Time Spent

The amount of encouragement, supervision, and access to economic resources that achild receives adds up over time. The more of these advantages children receive, the highertheir educational attainment. Because nonintact families offer less of these things than dointact families, children who spend more time in nonintact families should have lowereducational attainment.

Age at Which Effects Are Experienced

The effects of living in nonintact families may depend on the age at which the effectsare experienced. Younger children spend most of their time with parents, whereas olderchildren spend much of their time with teachers and peers (Krein 1986; Krein and Beller1988). Thus parental absence may be more negative for younger than for older children. Inaddition, younger children are less able than older children to cope with parental maritaldisruption (Chase-Lansdale and Hetherington 1990).

On the other hand, living in nonintact families at older ages may have a greater effecton educational attainment than at younger ages. Control and supervision of adolescents aredifficult in intact families but may be even more difficult in nonintact families (Amato 1987;Dornbusch et al. 1985). In addition, years spent in nonintact families during adolescence arecloser in time to the high school years; thus the effect is increased (Hetherington, Cox, andCox 1982).

Change in Parental Structure

Possibly, diminished educational attainment is caused not by the state of being in anonintact family but by the stress of changing from one type to another (McLanahan 1985).The most frequent changes are from mother-father to" "mother only, from mother-only tomother-stepfather, and from mother-stepfather to mother only. The first and the thirdchanges involve a loss of a parent; the second involves the addition of a parent. Whencompared to no change at all, each change should have a negative effect on educationalattainment. Stress is associated with change, and leads to diminished parenting, which intum leads to diminished educational attainment. The stress of losing a parent, however.should be greater than the stress due to adding a parent. Thus the negative effect oneducational attainment of change from two-parent to one-parent families should be greaterthan the effect of change from one-parent to two-parent families.

704

Family Type at Birth

Demography, Vol. 30, No.4, November 1993

Children enter into mother-only or mother-stepfather families in two ways. First, theycan be born into a mother-father family and then move into a mother-only family with thedisruption of their parents' marriage. Second, they can be born into a mother-only family,never living with their biological father. The meaning of parental structure experiences maybe different for those born into mother-only families than for those born into mother-fatherfamilies.

The difference is that for those born into mother-father families, the father is involvedmore deeply in the children's lives than for those born into mother-only families (Seltzer1991). This involvement includes both parenting and financial contributions. Althoughdivorced fathers are much less involved than married fathers, they are more involved thanabsent, unmarried fathers. Thus, in family situations where the father is not coresident, thenegative effects should be less for those who were born into mother-father families than forthose born into mother-only families.

DATA AND METHODS

Data

The National Longitudinal Survey of Youth (NLSY) began in 1979, when 12,686 menand women age 14 through 21 were interviewed. The sample has been reinterviewedannually since that time. The NLSY is a national probability sample with overrepresentationof blacks, Hispanics, and economically disadvantaged non-Hispanic whites. The originalsample also included a subsample of persons serving in the military.

The primary purpose of the NLSY was to collect data on the labor force experiences ofyouths as they moved into adulthood and to collect data on factors with potential effects onlabor market attachment. The NLSY, however, also serves as a more general social surveybecause of the variety of information that it contains.

The NLSY has maintained an excellent response rate through the years of the survey.Excluding the military samples, 90.2% of the respondents interviewed in 1979 werereinterviewed in 1988.

The sample size for the present analysis is 8,381. Of the 12,686 respondents in theoriginal sample in 1979, I excluded 3,885 who either were missing in later waves orbelonged to the military or to the socioeconomically disadvantaged white samples. Iretained the disadvantaged black and Hispanic samples. The 253 respondents with missingdata on the parental structure variables were excluded, as were 144 with missing data on theeducational attainment variable. I also excluded 23 respondents who had moved out of theirparents' household before age 16.

In the 1988 wave, the survey collected data on each respondent's childhood livingarrangements from birth to age 19. The survey asked respondents whether they lived withtheir biological mother, biological father, stepmother, stepfather, adoptive mother, oradoptive father in any of those years. If the respondent was not living with one of thoseparents, the survey asked respondents whether they lived with grandparents, with otherrelatives, with foster parents, with friends, in a children's home, in a detention center, inanother institution, with other persons, or on their own.

The parental history data was used to create the following typology at each age:mother-father, mother only, mother-stepfather, father only, father-stepmother, grandparentsonly, other relatives only, adoptive parents, foster parents, friends, children's home, groupcare home, detention center, other institution, other person, mixed, and none. Somerespondents reported living in two or more types of living situations in one year, probably


because they moved from one type to another. These respondents were included in the"mixed" category.

The present analysis uses information on the living arrangements of children only frombirth to age 15. After age 15, the proportion of youths who are living on their ownincreases. This proportion is never large, but in an analysis not shown here I found thatmore than half of those who ever lived on their own did not graduate from high school.Living on one's own might be viewed most appropriately as a living arrangement that isassociated with dropping out of high school rather than a living arrangement that causesschool exit. In order to avoid problems with the endogeneity of living on one's own, Ilimited the maximum age considered to age 15. I also eliminated the few respondents wholived on their own before age 16.

Regression Analysis

I used logistic regression to measure the relationship between family structure andeducational attainment. The data on living arrangements were employed to create a numberof different measures of children's parental structure experiences. I will discuss the variousparental structure variables as they arise in the discussion of the analysis.

The dependent variable is whether the respondent had completed 12 years of schoolingby age 20. Control variables include birth cohort, sex/gender, race/ethnicity, number ofsiblings, and parental education. Parental education is the education of the parent with moreyears of education.

The present analysis does not include a measure for parental income. Only data oncurrent family income were available in the NLSY. For the present analysis, an appropriatemeasure of family income would be income during childhood. This information is notavailable, however. As a result, the effects of parental structure in the present analysiscapture the effects of parental income.

Meaning of Parental Structure Effects

Parental structure coefficients in this study and in earlier studies are like"reduced-form" coefficients in path analysis (Duncan 1975). That is, the coefficientscapture both direct and indirect effects of parental structure on educational attainment. Theindirect effects are due to the influence of parental structure on parenting practices and onfamily income, which then influence educational attainment. The direct effects are due tothe immediate influence of parental structure on educational attainment, unmitigated byintermediate variables.

Parental structure, however, theoretically does not have direct effects on educationalattainment. It is a variable like race/ethnicity, which has theoretical meaning only because itrepresents a "bundle" of effects of other unmeasured variables (Michael and Tuma 1985).If we had complete measurement of other variables such as parenting practices and familyincome, there would be no residual effect of parental structure. It is not the physicalpresence of parents that matters, but what they do and what they bring into the household.The measure of physical presence has an effect only because it captures these other effects.

Thus the present study does not differ from earlier work that also viewed parentalstructure as capturing a bundle of effects of unmeasured variables. The bundle of effects inthis study, however, is bigger than would be the case if family income or some aspect ofparenting practices could be controlled.


RESULTSI consider two kinds of parental structure variables: duration and transition. I use these

variables to investigate the effects of the five dimensions of parental structure discussedabove: type, amount of time, age, change, and family type at birth.

Table 1 shows the unweighted frequencies for ever-experienced type of parentalstructure, ever-experienced transition, and type at birth. Each category contains 75respondents or more. Thus, even though some of the situations do not occur often, there areenough cases to allow estimation of coefficients for each of the categories.

Duration

Duration variables measure the number of years spent in particular types of parentalstructure. In this part of the analysis and in the remainder, the "other" category includesfoster parents, friends, children's home, group care home, detention center, otherinstitution, other person, mixed, and none. Youths living with adoptive parents arecombined with those living with mother-father.

Model 2.1 in Table 2 shows the effects of years spent in parental structure typesbetween birth and age 15 on chances of high school graduation. The analysis shows thatyears spent with mother only, mother-stepfather, father only, and grandparents only, as wellas in other types, reduce the chances of graduating from high school.

Table 2 also shows the effects for control variables. These coefficients do not changemuch from model to model as different parental structure variables are used. Thus, althoughthe control variables always are included in the models, the coefficients for these variablesare not shown in the remainder of the tables.

Table 1. Unweighted Frequencies for Parental Structure Variables

Variable

Ever Experienced Parental Structure TypeMother onlyMother-stepfatherFather onlyFather-stepmotherGrandparents onlyOther relatives onlyOther

Ever Experienced Parental Structure TransitionMother-father to mother onlyMother only to mother-stepfatherMother-stepfather to mother onlyOther change

Parental Structure Type at BirthMother-father, no disruptionMother-father, disruptionMother onlyOther

Total

Frequency

1,94169525215421088

286

1,233447

95925

5,7601,693

640288

8,381


Table 2. Logistic Regression for the Effects of Years in Parental Structure Type on HighSchool Graduation

Model 2.1 Model 2.2Log Odds Log Odds

Variable Coefficient SE Coefficient SE

Birth Cohort1957 -.063 .128 -.064 .1281958 -.107 .126 -.112 .1261959 -.097 .125 -.098 .1251960 - .141 .118 -.145 .1181961 -.124 .118 - .132 .1181962 .005 .118 .004 .1181963 - .126 .117 - .131 .1171964 Contrast Contrast

Sex/GenderMale Contrast ContrastFemale .426** .059 .426** .059

RacelEthnicityWhite Contrast ContrastBlack .067 .078 .070 .077Hispanic - .491** .081 - .490** .081Other -.292** .141 - .301** .141

Number of Siblings1 .271** .106 .270** .1062 Contrast Contrast3 or more - .399** .068 -.401** .068

Parental Education0-11 -.974** .070 -.972** .07012 Contrast Contrast13-15 .571** .129 .559** .128~16 1.435** .163 1.433** .163Missing -1.461** .134 -1.472** .133

Year in Parental StructureMother-father Contrast ContrastMother only - .037** .007Mother-stepfather - .036** .011Father only - .102** .025Father-stepmother -.034 .029Grandparents only -.051** .016Other relatives only -.034 .035Not mother-father -.040** .005Other -.082** .017· - .085** .017

Intercept 2.264 2.266N 8,381 8,381-2 Log-L 7229.37 7236.13DF 8,356 8,361Difference in -2 Log-L 6.76Difference in DF 5

BIC -38.4

* p<.l0** p<.05.


Model 2.1 allows the effects of duration to differ for each type of parental structure. Isthis complexity necessary, or would a simpler model describe the data just as well? Model2.2 constrains the effects of the six most common nonintact types to be equal. According tothis model, a year in anyone of these types of nonintact family, no matter which one, willhave the same effect on high school graduation. This model is much simpler than Model2.1. The difference in -2 log-likelihood between Model 2.1 and Model 2.2 is notsignificantly large; this finding shows that the less complex model fits as well as the modelin which all of the coefficients were allowed to be different.

I provide information on three levels of significance. The difference in -2log-likelihood between models is distributed chi-square. I use asterisks to show whether thedifference is significant at the .10 and .05 levels. I also show the BIC statistic (Raftery1986), which takes into account the fact that small differences may be significant primarilybecause of large sample sizes. A test using the BIC statistic is more demanding than achi-square test. A positive BIC indicates that the model with more parameters fits the databetter than the model with fewer parameters. A negative BIC means that adding parametersdoes not improve the fit of the model. The formula for BIC in the logistic regressionsituation is as follows:

BIC =(difference in -2 log-likelihood)-(DF for difference)(log N).The most important finding from the first two models is that one coefficient describes

the effects of the six most common types of nonintact parental structure. In particular, theeffects of mother only and of mother-stepfather, the two most frequent situations, do notdiffer significantly. This finding means that a year in a mother-stepfather family is asnegative for educational attainment as a year in a mother-only family.

The duration variables can be used in considering whether the effects of parentalstructure depend on age at experience and on family type at birth. Table 3 shows two sets ofsix models. In each model of the first set, years in a parental structure type are notrepresented by one variable; instead, three variables represent years spent from birth to age5, ages 6 through 10, and ages 11 through 15. These add up to the overall duration variableso that the model with three variables is nested within the model with one variable.

For years spent with mother only and years spent with father only, the model withage-specific variables fits better at the .10 level of significance than the model with onevariable. Years spent with mother only is also significant at the .05 level. The BIC testshows that none of the age specific variables improves model fit.

For years spent with mother only, the fit improves because of the stronger effect foryears spent between ages 11 and 15. For years spent with father only, the fit improvesbecause the effects for years spent between ages 0 and 5 and between ages, 11 and 15 aresignificantly negative, but the effect for years spent between ages 6 and 10 does not differsignificantly from zero.

The duration variables also can be used to consider the effects of family type at birth.In order to determine whether the effects of parental structure experiences depend on familytype at birth, I first created dummy variables for three types: mother-father at birth and laterdisruption, mother only at birth, and other family type at birth. Then I interacted each ofthese family-type-at-birth variables with the duration variables. The idea is that the effect oftime spent in a particular type of parental structure might depend on the family situation atbirth. If family type at birth matters, then the model with three variables describing theeffect of a particular type of parental structure will fit the data better than the model with onevariable.

The bottom panel of Table 3 shows the results from six logistic regressions. In eachmodel, I allowed one parental structure variable to differ across family type at birth. Abetter-fitting model did not result from any of the models using three variables to capturedifferential effects across family type at birth. This finding means that the effects of years


Table 3. Logistic Regressions for the Effects of Number of Years in Parental StructureType on High School Graduation, Given Age at Experience of

Type and Given Type at Birth

Difference from Age at Experience of

Parental Model 2.1 Parental Structure

Model Structure -2 Log-L DF -2 Log-L DF BIC 0-5 6-10 11-15

2.1 Baseline 7229.37 8,3563.1 M 7222.63 8,354 6.74** 2 -11.3 .002 -.021 -.089**3.2 MSF 7228.46 8,354 0.91 2 -17.13.3 F 7224.51 8,354 4.86* 2 -13.2 - .141* .069 -.229**3.4 FSM 7228.78 8,354 0.59 2 -17.53.5 GRA 7229.33 8,354 0.04 2 -18.03.6 REL 7229.26 8,354 0.11 2 -17.9

Difference from Parental Structure

Parental Model 2.1 Type at Birth

Model Structure -2 Log-L DF -2 Log-L DF BIC M-F MOnly Other

3.7 M 7229.33 8,354 0.04 2 -18.03.8 MSF 7225.54 8,354 3.83 2 -14.23.9 F 7228.56 8,354 0.81 2 -17.33.10 FSM 7227.58 8,354 1.79 2 -16.33.11 GRA 7228.03 8,354 1.34 2 -16.73.12 REL 7228.66 8,354 0.71 2 -17.3

M:mother only; MSF:mother-stepfather; F:father only; FSM:father-stepmother; GRA:grand-parents only; REL:other relatives only.

* p<.l0** p<.05

spent with mother only and with mother-stepfather are the same, no matter how one startedout at birth.

The effects for duration in Model 2.1 are less straightforward than they might seem.The underlying assumption is that the effects of years spent in parental structure typesincrease linearly. Is this assumption legitimate? To answer this question we first need amodel that contains a weaker assumption about the effects of parental structure.

Model 4.1 in Table 4 includes variables for each parental structure type, as in Model2.1, but these variables denote whether a respondent ever lived in a particular parentalstructure type. The coefficients in this model represent the average effect of living in aparticular type. Only the coefficients for years spent with mother only, with father only, andin some "other" type differ significantly from zero. . -:

Table 5 shows six models. In each model, three coefficients are estimated to capturethe effects of years spent in types of parental structure. Each coefficient indicates the effectof a dummy variable which represents a different length of time spent in that particular type.If the effect of duration in parental structure type is linear, then the coefficients shouldbecome increasingly negative as one goes from 1-5 years to 6-10 years to 11-16 years. Inaddition, the use of three variables instead of one to describe parental structure experiencesshould significantly improve the fit of the model. The model with three variables describingparental structure type is nested within the model with one variable because the sum of thethree variables equals the one variable.


Table 4. Logistic Regression for the Effects of Ever Lived in Parental Structure Type onHigh School Graduation

Model 4.1

Variable

Ever in Parental StructureNever in nonintact familyMother onlyMother-stepfatherFather onlyFather-stepmotherGrandparents onlyOther relatives onlyOther

N-2 Log-LDF

Log OddsCoefficient

Contrast-.406**-.075- .332*-.047-.207- .178- .687**8,381

7233.028,356

SE

.070

.105

.171

.218

.168

.242

.143

Note: Modelalso includes variables for birth cohort, sex/gender, race/ethnic, number of siblings.and parental education.

* p<.l0 .** p<.05

Model fit is improved significantly by using three variables to describe the effects ofyears spent with mother-stepfather and years spent with father only. The mother-stepfathereffect, however, is significant only at the .10 level. The model with three variables for yearsspent with mother only does not fit better than the model with one variable.

These models provide information for interpreting the significant linear effects inModel 2.1. The linear effect for years in mother-only families is significant because itcaptures the negative effect for any experience of a mother-only family. The significantlinear effects for living with mother-stepfather or with father only may be so because of the

Table 5. Logistic Regressions for the Nonlinear Effects of Years Lived in ParentalStructure Type on High School Graduation

Difference from Number of Years in

Parental Model 4.1 Parental Structure

Model Structure -2 Log-L DF -2 Log-L DF BIC 1-5 6-10 11-16

4.1 Baseline 7233.02 8,3565.1 M 7232.13 8,354 0.89 2 -17.25.2 MSF 7228.00 8,354 5.02* 2 -13.0 -.039 .153 - .377**5.3 F 7227.02 8,354 6.00** 2 -12.1 - .115 -.446 -1.274**5.4 FSM 7232.25 8,354 0.77 2 -17.35.5 GRA 7228.70 8,354 4.32 2 -13.75.6 REL 7232.77 8,354 0.25 2 -17.8

M:mother only; MSF:mother-stepfather; F:father only; FSM:father-stepmother; GRA:grand-parents only; REL:other relatives only.

* p<.l0** p<.05

Simplicityand Complexity 711

strong negative effects for those who live in these types for long durations. It is also true,however, that those who lived in parental structure types for long durations entered thosetypes at early ages.

Transition

To this point the analysis has focused on durations, or time spent in parental structuretypes. In the second part of the analysis I examine parental structure experiences from adifferent perspective: I consider transitions from one type of parental structure in one year toa different type in the next year. The eight types that I have used in the first part of theanalysis allow for a large number of possible transitions; the analysis reported here focuseson the three that occur most frequently. These are moves from mother-father to mother only,from mother only to mother-stepfather, and from mother-stepfather to mother only. The firsttransition is a disruption of a two-parent family, as is the third. The second transitioninvolves family reconstitution.

Model 6.1 in Table 6 shows that among those who experienced a transition frommother-father to mother only, the chances of graduating from high school are lower thanamong those who experienced no change. The effects of the other two transitions are notsignificant.

Model 6.1 tests whether the effect of each kind of change is different from zero. Thismodel does not test whether the coefficients differ significantly from each other. Model 6.2does so by constraining to be equal the effects of change from mother-father to mother only,from mother only to mother-stepfather, and from mother-stepfather to mother only. Thisconstraint does not result in a significant reduction in the fit of the model. The combined

Table 6. Logistic Regression for the Effects of Parental Structure Transitions on HighSchool Graduation

Model 6.1 Model 6.2

Log Odds Log OddsVariable Coefficient SE Coefficient SE

Parental Structure TransitionNo change Contrast ContrastMother-father to mother only - .331** .082Mother only to mother-stepfather -.064 .135Mother-stepfather to mother only .282 .299Any change - .306** .074Other change -.567** .085 - .555** .085

N 8,381 8,381-2 Log-L 7255.20 7257.76DF 8,359 8,361Difference in -2 Log-L 2.56Difference in DF 2BIC -15.5

Note: Models also include variables for birth cohort, sex/gender, race/ethnic, number of siblings,and parental education.

* p<.l0** p<.05


effect is significantly negative; this finding means that experiencing anyone of the threechanges reduces the chances of high school graduation.

The effects of transitions in parental structure may not be additive. That is, the effectof one transition may depend on whether other changes have been experienced. Thus it maynot be appropriate to examine transitions separately because they are related so closely. Inaddition, family type at birth may be important. For example, a transition from mother onlyto mother-stepfather may have a different meaning for those who were born intomother-only families than for to those who were born into mother-father families.

Model 7.1 in Table 7 takes into account the relationship between transitions andbetween transitions and family type at birth. This model contains seven combinations oftransitions and family type at birth. For those who were born into mother-father families,the model includes categories for those who experienced one, two, or three transitions. Forthose who were born into mother-only families, there are categories for those whoexperienced no transitions, one, or two. The model also contains a category for those whoexperienced other combinations of transitions. This definition of transitions is similar to thatin Martinson and Wu (1992).

Before drawing any conclusions about strength and significance of the effects of thesetransition combinations, we must determine whether this complexity is necessary. Model7.2 constrains the first six changes in Model 7.1 to be equal. There is no significantdifference in fit between Models 7.1 and 7.2. Model 7.2 shows that the combined effect issignificantly negative. Thus, although some change has a negative effect on high school

Table 7. Logistic Regression for the Effects of Parental Structure TransitionCombinations on High School Graduation

Model 7.1 Model 7.2

Log Odds Log OddsVariable Coefficient SE Coefficient SE

Parental Structure TransitionNo change Contrast ContrastMF birth, MF to M - .488** .095MF birth, MF to M, M to MSF -.392** .174MF birth, MF to M, M to MSF, MSF to M .268 .574M birth, no change - .655** .135M birth, M to MSF -.339 .227M birth, M to MSF, MSF to M -.540 .499Any Change - .489** .074Other changes - .713** .083 -.711** .083

N 8,381 8,381-2 Log-L 7219.87 7224.33DF 8,356 8,361Difference in -2 Log-L 4.46Difference in DF 5BIC -40.7

Note: Models also include variables for birth cohort, sex/gender, race/ethnic, number of siblings,and parental education.

MF:mother-father; M:mother only; MSF:mother-stepfather.* p<.10

** p<.05


graduation, the specific pattern of change does not make a difference, at least between thecombinations considered in Model 7.1.

Combined Model

In the analysis above, I estimated the effects of transitions without including theduration variables in the model. It may be that the transition variables captured the sameeffects for parental structure as did the duration variables. Likewise, in the analysis ofduration effects, I did not consider the effects of transitions. In order to assess the uniqueeffects of duration and transition, the model in Table 8 includes both types of variables aswell as variables for parental structure at birth. To facilitate interpretation, I includedvariables only for the most common experiences of nonintact parental structure.

Table 8. Logistic Regressions for the Effects of Parental Structure Type at Birth,Parental Structure Transitions, and Years in Parental Structure

Type on High School Graduation

Model 8.1

Log-OddsVariable Coefficient SE

Parental Structure Type at BirthMother-father ContrastMother only at birth - .486** .210Other -.205 .198

Parental Structure TransitionNo change ContrastMother-father to mother only - .470** .126Mother only to mother-stepfather .424** .179Other change -.139 .116

Year in Parental StructureMother-father ContrastMother only -.003 .014Mother-stepfather -.036** .017Other -.045** .015

Parental Education0-11 -.976** .07012 Contrast13-15 .572** .12816 or more 1.443** .163Missing -'-1.441** .134

Intercept 2.315

N 8,381-2 Log-L 7217.07DF 8,356

Note: Model also includes variables for birth cohort, sex/gender, race/ethnic, and number ofsiblings.

* p<.lO.** p<.05.


Model 8.1 shows significant negative effects on high school graduation for being borninto a mother-only family as well as for a transition from living with mother-father to livingwith mother only. These two negative effects are almost equal. The transition from livingwith mother only to living with mother-stepfather has a significant positive effect. Yearsspent in mother-stepfather families, however, have a negative effect. There is no significanteffect for years spent in mother-only families.

The transitions and the years spent in types of parental structure happen not in isolationbut in combination. Table 9 presents the predicted high school graduation rates based on theresults of Model 8.1. The baseline group consists of those born in 1964, male, non-Hispanicwhite, with two siblings, and, most important, having lived with mother-father from birth toage 15. About 91% of the baseline group graduated from high school. Each of the nonintactfamily groups had lower graduation rates; the lowest rates were for those who lived withmother only at some time but never with mother-stepfather. Those who lived withmother-stepfather for a long duration also had a low high school graduation rate. Thosewhose mother remarried but who spent only five years with mother-stepfather had lowergraduation rates than the baseline group but higher rates than the other nonintact familygroups. Not much variation exists, however, between the various types of nonintactfamilies.

Table 9 also shows how parental education affects high school graduation rates. Only79% of those whose more highly educated parent is a high school dropout graduated fromhigh school; this rate is 12% less than the baseline group. Having at least one parent withsome college increased high school graduation rates to 95%, about 4% above the baselinegroup; having at least one college educated parent increased the high school graduation rateto 98%, about 7% above the baseline.

Thus the effect of living in a nonintact family is of the same magnitude as the effect ofhaving parents with at most a high school education rather than having parents with somecollege. Having parents who were high school dropouts has a much more negative effectthan experiencing a nonintact family.

Table 9. Predicted High School Graduation Rates Based on Model 8.1

Type Transition Years in Type Highest Percentat Parental High SchoolBirth MFtoM M to MSF MF M MSF Education ' Graduate

MF No No 16 0 0 High school 91.0MF Yes No 11 5 0 High school 86.2MF Yes Yes 6 5 5 High school 88.8

M No No 0 16 0 High school 85.6M No Yes 0 11 5 High school 88.5M No '4 0 5 11 High school 86.3

MF No No 16 0 0 Less than HS 79.2MF No No 16 0 0 Some college 94.7MF No No 16 0 0 College 97.7

Note: The values of the other variables used in the calculations are 1964 year of birth, male,non-Hispanic white, and two siblings; each of these is the excluded category in Model 8.1.

MF:mother-father; M:mother only; MSF:mother-stepfather.

Simplicity and Complexity

DISCUSSION

715

In the analysis reported here, I found that the relationship between high schoolgraduation and parental structure during childhood and adolescence is simpler than ourtheoretical notions might suggest. In considering duration in nonintact families, any yearspent in a nonintact family had a negative effect. The analysis also showed that the effectsof parental structure did not depend on family type at birth. Also, when transitions wereconsidered separately, the type of transition did not make a difference.

The more stringent BIC test did not find significance for any of the more complexmodels, although the less stringent chi-square test at the .05 level of significance uncoveredsome complexity in the effects of parental structure on chances of high school graduation.Years spent in mother-only families between the ages of 11 and 15 were much morenegative than years spent at younger ages. This finding for mother-only families is contraryto findings by Krein (1986) and Krein and Beller (1988) which found more negative effectsfor years spent at younger ages. The present research, however, uses high school graduationas the dependent variable, whereas Krein (1986) and Krein and Beller (1988) examinedyears of education.

Those who spent 11-16 years in father-only families suffered a much more negativeeffect than those who spent fewer years in that type. An experience of such long duration ina father-only family is rare, however. .

The combined analysis included the duration and transition variables in one model inorder to determine the unique effect of each. Being born into a mother-only family isnegative, as is the transition from mother-father to mother only. There is no additional effectfor the number of years spent in mother-only families. The transition from mother only tomother-stepfather was positive and canceled out most of the negative effect for either of thetwo types of transitions into mother-only families. Living in mother-stepfather families,however, still led to lower chances of high school graduation because there was a negativeeffect for each year spent in a mother-stepfather family.

The combined model suggests that the effects of experiences with mother-only familiesare event-dependent, whereas the effects of experiences with mother-stepfather families areduration-dependent. It does not matter how long one is in a mother-only family; the negativeeffect is due to moving into that family type. In contrast, the length of time one lives in amother-stepfather family determines the degree of negative effect.

The predicted high school graduation rates drawn from the combined model show littlevariation in the effects of different types of nonintact family experiences on high schoolgraduation. Thus the main finding of this study is that the type of nonintact family mattersless than having ever lived in a nonintact family. This finding does not mean that familyprocesses do not vary in different types of nonintact families. It means that this variationdoes not lead to variation in chances of high school graduation.

The main limitation of this study is that it could not examine what factors contribute tothe parental structure effects that I found. The NLSY collected data on parental history butdid not on family income or parenting practices. The parental structure effects capture avariety of characteristics of family situations. Thus, although this study has much to sayabout how different parental situations lead to lower chances of high school graduation, itsays little about the underlying nature of these situations.

Income is an important factor that was not controlled. It is likely that much of thenegative effect of living in mother-only families is due to low income. The negative effectof living in mother-stepfather families is less likely to be the result of low income, althoughit may be due to less access to income. If income was controlled, the advantage of living inmother-stepfather families in relation to mother-only families probably would diminish.

One implication of this study for other research on the effects of parental structure on


life course status, whether education, fertility, marriage, or divorce, is that complexmeasures of parental structure must be justified. The present study has shown that morecomplex measures of parental structure have explanatory power in a few instances, but thatin other instances more complex measures do not contribute to a fuller explanation.

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Simplicity and complexity in the effects of parental structure on high school graduation

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