Synchronization between statistics, research hypotheses and research aims

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Dr. Geshina A Mat Saat 7 April 2015

Synchronization between statistics, research hypotheses and research aims

USM/GMS.biostats2015 1

Biostatistics Sharing Session@PPSK

School of Health Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan

OBJECTIVES

• Link Bloom’s Revised Taxonomy with why, what, how, when

• To explain the relationship between research aims, research hypotheses & statistics in order to get the research method ‘right the first time’

• Synchronization between statistics, research hypotheses and research aims via experiential learning

OUTCOMES

• Be able to understand & link Bloom’s Revised Taxonomy with why, what, how, when

• Get the research method ‘right the first time’

• Able to synchronize between statistics, research hypotheses and research aims via eexperiential learning


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PART ONE: BLOOM’S REVISED TAXONOMY


Introduction: Why Bloom’s Revised Taxonomy?

• Graduate students are expected to: – improve their general intellectual skills

– attain proficiency in one or more academic disciplines of

their choice

– develop interpersonal and leadership skills needed for productive careers and effective citizenship

– other than the above, develop professional, research, and scholarship skills


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• To what degree have students attained desired educational goals? – in other words, what are the evidences?

• Many universities around the world makes use of Bloom’s Revised Taxonomy to determine & measure desired educational goals.

• Therefore it is to the graduate student’s benefit to learn and understand how to use Bloom’s Revised Taxonomy in the research process and writing.



• Bloom's taxonomy refers to a classification of the different objectives that educators set for students (learning objectives).

• It divides educational objectives into three domains: – Cognitive: Skills revolve around knowledge, comprehension, and

critical thinking on a particular topic.

– Affective: Skills describe the way people react emotionally and their ability to feel other living things' pain or joy. Affective objectives typically target the awareness and growth in attitudes, emotion, and feelings.

– Psychomotor: Skills describe the ability to physically manipulate a tool or instrument like a hand or a hammer. Psychomotor objectives usually focus on change and/or development in behavior and/or skills.

• Within the domains, learning at the higher levels is dependent on having attained prerequisite knowledge and skills at lower levels (Orlich et al, 2004)


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• Typically, the top three levels within a domain are used as guides to formulate postgraduate level objectives.

• This is to draw attention to a researcher’s cognitive acumen, affective development and psychomotor skills.

• The following table presents examples or appropriate objectives at the higher ends of the three domains for research.




(Adapted from Anderson et al, 2000)

Bloom’s Revised Taxonomy: Cognitive domain

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Category or 'level' Behavior descriptions Examples of experience, or demonstration and evidence to be measured

'Key words'

1. Receiving Open to experience, willing to hear

Listen to teacher or trainer, take interest in session or learning experience, take notes, turn up, make time for learning experience, participate passively

Ask, listen, focus, attend, take part, discuss, acknowledge, hear, be open to, retain, follow, concentrate, read, do, feel

2. Responding React and participate actively

Participate actively in group discussion, active participation in activity, interest in outcomes, enthusiasm for action, question and probe ideas, suggest interpretation

React, respond, seek clarification, interpret, clarify, provide other references and examples, contribute, question, present, cite, become animated or excited, help team, write, perform

3. Valuing Attach values and express personal opinions

Decide worth and relevance of ideas, experiences; accept or commit to particular stance or action

Argue, challenge, debate, refute, confront, justify, persuade, criticize,

4. Organizing or Conceptualizing Values

Reconcile internal conflicts; develop value system

Qualify and quantify personal views, state personal position and reasons, state beliefs

Build, develop, formulate, defend, modify, relate, prioritize, reconcile, contrast, arrange, compare

5. Internalizing Values

Adopt belief system and philosophy

Self-reliant; behave consistently with personal value set

Act, display, influence, solve, practice,

Source: www.d.umn.edu/vcaa/assessment/bloomoverviw.docx

Bloom’s Revised Taxonomy: Affective domain


Category or 'level' Behavior descriptions Examples of activity or demonstration and evidence to be measured

'Key words'

1. Imitation Copy action of another; observe and replicate

Watch teacher or trainer and repeat action, process or activity

Copy, follow, replicate, repeat, adhere, attempt, reproduce, organize, sketch, duplicate

2. Manipulation Reproduce activity from instruction or memory

Carry out task from written or verbal instruction

Re-create, build, perform, execute, implement, acquire, conduct, operate

3. Precision Execute skill reliably, independent of help, activity is quick, smooth, and accurate

Perform a task or activity with expertise and to high quality without assistance or instruction; able to demonstrate an activity to other learners

Demonstrate, complete, show, perfect, calibrate, control, achieve, accomplish, master, refine

4. Articulation Adapt and integrate expertise to satisfy a new context or task

Relate and combine associated activities to develop methods to meet varying, novel requirements

Solve, adapt, combine, coordinate, revise, integrate, adapt, develop, formulate, modify, master

5. Naturalization Instinctive, effortless, unconscious mastery of activity and related skills at strategic level

Define aim, approach and strategy for use of activities to meet strategic need

Construct, compose, create, design, specify, manage, invent, project-manage, originate

Based on RH Dave's version of the Psychomotor Domain (Developing and Writing Behavioral Objectives, 1970). The theory was first presented at a Berlin conference 1967, hence you may see Dave's model attributed to 1967 or 1970). Source: www.d.umn.edu/vcaa/assessment/bloomoverviw.docx

Bloom’s Revised Taxonomy: Psychomotor domain

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Objective Cognitive domain

Affective domain

Psychomotor domain

1 To construct a Standard Operation Procedure for nursing practices in ward hygiene management.

Construct Organization Articulation

2 To distinguish organizational ethics in five departments within Hospital ‘A’

Analysing Valuing Naturalization

3 To create a model linking patient support system and improved health status

Creating Internalising values

Precision

Bloom’s Revised Taxonomy and Research Objectives


• Application of Bloom’s Taxonomy in research provides indicators of professional, research, and scholarship skills.


INTR

OD

UC

TIO

N Statement of the problem

Significance of the study Aims (Direction) Objectives Hypothesis

LITE

RAT

UR

E R

EVIE

W Determine what has already been

written on a topic

Construct an overview of key concepts

Identify major relationships or patterns

Identify strengths and weaknesses

Identify any gaps in the research

Identify any conflicting evidence

Construct a solid background to a research paper’s investigation

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Methodology chapter: why, what, how, when


(Adapted from: Saunders et al, 2007)

Ch

apte

r su

b-h

ead

ings



DIS

CU

SSIO

N What was done

What was found

What do the findings mean? To the best of your knowledge, why do you think that is? What accounts for these results?

Why are the findings significant/important/useful? How can they be used, and who can use them? What went wrong?

How do the limitations of your study affect the results?

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PART TWO: RELATIONSHIP BETWEEN RESEARCH AIMS,

RESEARCH HYPOTHESES & STATISTICS


The relationship between practical problems and research problems

Practical problem

Research question

Research problem

Research answer


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The relationship between research aims, research hypotheses & statistics

Research Aim

Research Hypotheses

Statistics


The relationship between research aims, research hypotheses & statistics

• The development of the research aim, including a supportive hypothesis and objectives, is a necessary key step in producing relevant results to be used in evidence-based practice.

• A well-defined and specific research aim is more likely to help guide in making decisions about study design and population and subsequently what data will be collected and analysed (Brian, 2006).

• A good research question (O’Leary, 2004): – Defines the investigation – Sets boundaries – Provides direction


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Research Aim

• An aim identifies the purpose and focus of the investigation.

• In other words, the aim answers the question ‘What is the point of the study?’

• The aim typically involves the word: investigate, investigation, explore, or analyse or other verbs.

• Examples: – Brewin et al (1999) investigated the ability of a diagnosis of

acute stress disorder and its component symptoms to PTSD.

– The aim of Tan et al’s (2014) research was to explore and evaluate previous work focusing on the relationship and links between regulation and PM.


Research Aim

• Objectives specify the components of how the aim will be met: – Deconstruct a research aim into operationalised study

components – what you will do to achieve the aim.

– Primary (or main or general) and secondary objectives (or specific) translate directly into primary and secondary hypotheses which may be measured.

– Prioritise and limit objectives to avoid too many hypotheses and outcomes – what can you actually do given the time & resource limitations.

– Presented in active language, e.g. ‘to quantify’, ‘to determine’


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Hypothesis

• A hypothesis (plural hypotheses) is a precise testable statement of what the researcher predict will be the outcome of the study.

• This usually involves proposing a possible relationship between two variables: the independent variable (what the researcher changes) and the dependant variable (what the research measures).

• The hypotheses can be expressed in the following ways: – The null hypothesis states that there is no relationship between

the two variables being studied (one variable does not affect the other). It states results are due to chance and are not significant in terms of supporting the idea being investigated.

– The alternative hypothesis states that there is a relationship between the two variables being studied (one variable has an effect on the other). It states that results are not due to chance and that they are significant in terms of supporting the theory being investigated.


Adapted from: McLeod (2014)

A good hypothesis is short, clear and should include the operationalized variables being investigated.

• A one-tailed directional hypothesis predicts the nature of the

effect of the independent variable on the dependent variable. – E.g.: Children will recall less of what they ate then adults.

• A two-tailed non-directional hypothesis predicts that the

independent variable will have an effect on the dependent variable, but the direction of the effect is not specified. – E.g.: There will be a difference in how many food types are

correctly recalled by children and adults.


Hypothesis

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Freeman and Tyrer (1992) offer an example:

• Vague hypothesis: ‘Does psychotherapy help patients with anorexia nervosa?’

• Precisely formulated question: Does psychotherapy, in the form of cognitive therapy, when given for ten weeks, lead to significantly greater gain in weight in anorectic patients than in those not receiving cognitive therapy?’

• Null hypothesis: There is no difference in the weight gain of patients with anorexia nervosa when treated with cognitive therapy compared with a control procedure.

Adapted from: McLeod (2014)


Hypothesis


The Hypothesis Dilemma

A hypothesis may not be appropriate if: • You do not have an educated guess about a particular

situation

• You do not have a set of defined variables

• Your question centres on phenomenological description

• Your question centres on an ethnographic study of a cultural group

• Your aim is to engage in, and research, the process of collaborative change

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From Hypothesis to Statistics

• What you write as a hypothesis is directly linked to the statistic used later.

• The type of measurement (slide 27) will determine the type of statistical method used (slide 28).

• Statistical methodology (Lund Research LTD, 2014): – Descriptive statistics summarizes data from a sample using indexes

such as the mean or standard deviation

– Inferential statistics draws conclusions from data that are subject to random variation (e.g., observational errors, sampling variation)

• The next step is to determine whether interest is in relationship or

differences (see slide 28). – ‘Relationship’ will lead to the selection of multiple regression,

linear-regression, spearman’s r or product-moment correlation.


From Hypothesis to Statistics

• Standard statistical procedure involve the development of a null hypothesis. – Working from a null hypothesis two basic forms of error are recognized:

• Type I errors (null hypothesis is falsely rejected giving a "false positive")

• Type II errors (null hypothesis fails to be rejected and an actual difference between populations is missed giving a "false negative").

• In other words, for example - if units of analysis are categorical for both independent and dependent variables, multiple regression can not be done.

• Therefore it is vital to be able to link aim to objective to hypothesis to statistical methodology (descriptive or inferential) to ensure your research methodology is correct and that the items in your quantitative survey are relevant and measurable for the statistical methodology selected.

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Scales of Measurement and their Statistics



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Selecting a Statistical Test


Non Parametric Tests


Anderson–Darling test Statistical Bootstrap Methods Cochran's Q Cohen's kappa Friedman two-way analysis of variance (by ranks) Kaplan–Meier Kendall's tau Kendall's W Kolmogorov–Smirnov test Kruskal-Wallis one-way analysis of variance (by ranks)

Kuiper's test Logrank Test Mann–Whitney U or Wilcoxon rank sum test McNemar's test median test Pitman's permutation test Rank products Siegel–Tukey test Spearman's rank correlation coefficient Wald–Wolfowitz runs test Wilcoxon signed-rank test

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Categorical Data Analysis

• Common tests: – Chi-square – Fisher’s Exact Test – McNemar test

• Reference for conducting categorical data analysis: http://courses.ncssm.edu/math/Stat_Inst/PDFS/Categorical%20Data%20Analysis.pdf

• E-book:

http://www.planta.cn/forum/files_planta/categorical_data_analysis_202.pdf


PART THREE: SYNCHRONIZING


http://courses.ncssm.edu/math/Stat_Inst/PDFS/Categorical Data Analysis.pdf



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It’s a morbid but necessary job in ageing Japan: to clean up apartments where elderly people have died alone. In March, the body of an elderly man was found on the floor of his apartment in downtown Tokyo. Neighbours hadn’t noticed the octogenarian’s absence. His bank made the rent payments on time, his family didn’t visit, and the only reason for the body’s discovery was a slight smell that troubled the tenant in the flat below. He had been dead for a month. In rapidly ageing Japan, more people are dying alone and unnoticed in a country where more than 5 million elderly people live alone and increasingly isolated lives. For these so-called “lonely deaths”, or kodokushi, families and landlords in Tokyo are increasingly turning to Hirotsugu Masuda and his clean-up crew to salvage apartments where the occupant’s body lay undiscovered for days or weeks. “This has started becoming a bit more common in the world and it’s become more recognised that there’s this sort of job,” says Masuda, whose services are required 3-4 times a week in summer when bodies decompose faster. When Masuda’s team turns up at the Tokyo apartment, police have taken away the corpse but body fluids have seeped into the floor. Workers wearing protective gear spray the apartment with insect repellent, using gloved hands to pack the trash in boxes. The six-hour exercise is conducted discreetly to avoid upsetting neighbours. The crew tells onlookers they are moving house. Masuda’s firm works almost exclusively with “lonely deaths”, charging between ¥81,000 (RM2,494) and ¥341,000 (RM10,497) depending on apartment size. When they are done, incense and flowers are placed where the body had been found, with the man’s photo put where his head had been. Victims forgotten by families are not given a funeral and their remains are interred in unmarked graves. It's a phenomenon that experts say will soon become the norm. "There's likely 40,000 of these cases and we think that in 10 years, it's likely to go over 100,000 cases," says Hideto Kone, an NGO official working on such cases. Data shows victims are more likely to be male. – Reuters Source: Meyers, C (April 3, 2015). Cleaning up Japan’s ‘lonely death’ apartments. The Star online

Synchronizing


Aim Hypothesis Statistics

To investigate why ‘lonely deaths’ occur

There is no relationship between number of family members and ‘lonely deaths’

Linear regression

There is no association between living styles and ‘lonely deaths’

Spearman’s r

There is no difference between genders and ‘lonely deaths’

Chi-square

*Underlined texts = variables of interest. 1. Must first be defined in units of analysis: ratio, interval, nominal, or ordinal 2. Assumptions underlying the statistics must be met before conducting analysis.

A worked example based on the case

If unsure of how to write the aim; use what, where, when, how, or why.

Important words linked to statistical methods to be selected

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Partial references

Brewin, C. R., Andrews, B., Rose, S., & Kirk, M. (1999). Acute stress disorder and posttraumatic stress disorder in victims of violent crime. The American Journal of Psychiatry, 156(3): 360-366

Brian H. R. (2006). Forming research questions. J Clin Epidemiol. 59:881–6. McLeod, S. A. (2014). Aims and Hypotheses. Retrieved from http://www.simplypsychology.org/ aims-

hypotheses.html O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage. Orlich, D., Harder, R., Callahan, R., Trevisan, M., Brown, A. (2004). Teaching strategies: a guide to effective

instruction (7th ed.). Houghton Mifflin. Tan, K.H., Shi, L., Tseng, M.L., Cui, W.-J. (2014). Managing the indirect effects of environmental regulation and

performance measurement, Industrial Engineering and Management Systems, 13 (2): 148-153. V. (July 17, 2013). How to write a Discussion chapter for your thesis or dissertation. Retrieved from:

http://prconnections.net/2013/07/17/how-to-write-a-discussion-chapter-for-your-thesis-or-dissertation/

Queensland University of Technology (Feb 12, 2015). Writing a literature review. Retrieved from:

http://www.citewrite.qut.edu.au/write/litreview.jsp























http://www.citewrite.qut.edu.au/write/litreview.jsp

Synchronization between statistics, research hypotheses and research aims

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