Research Design and Analysis

A concise, straightforward overview of research design and analysis, helping readers form a general basis for designing and conducting research

The practice of designing and analyzing research continues to evolve with advances in technology that enable greater technical analysis of data--strengthening the ability of researchers to study the interventions and relationships of factors and assisting consumers of research to understand and evaluate research reports. Research Design and Analysis is an accessible, wide-ranging overview of how to design, conduct, analyze, interpret, and present research. This book helps those in the sciences conduct their own research without requiring expertise in statistics and related fields and enables informed reading of published research.

Requiring no background in statistics, this book reviews the purpose, ethics, and rules of research, explains the fundamentals of research design and validity, and describes how to select and employ appropriate statistical techniques and reporting methods. Readers gain knowledge central to various research scenarios, from sifting through reports of meta-analyses and preparing a research paper for submission to a peer-reviewed journal to discussing, evaluating, and communicating research results. This book:

• Provides end-to-end guidance on the entire research design and analysis process

• Teaches readers how to both conduct their own research and evaluate the research of others

• Offers a clear, concise introduction to fundamental topics ideal for both reference and general education functions

• Presents information derived from the author's experience teaching the subject in real-world classroom settings

• Includes a full array of learning tools including tables, examples, additional resource suggestions, complete references, and appendices that cover statistical analysis software and data sets

Research Design and Analysis: A Primer for the Non-Statistician is a valuable source of information for students and trainees in medical and allied health professions, journalism, education, and those interested in reading and comprehending research literature.

Autorentext

LESLIE D. ROSENSTEIN, PHD, serves on the faculty of the Department of Psychiatry, Division of Psychology at the University of Texas Southwestern Medical Center. She earned her PhD in??Differential Psychology from the University of Texas at Austin and completed a doctoral respecialization in Clinical Neuropsychology at the University of Arizona in Tucson. Dr. Rosenstein has taught courses in??Introductory Statistics and Research Design and Analysis to Psychology students.

Inhalt
List of Figures xiii

List of Tables xv

Introduction xix

Section 1 The Purpose, Ethics, and Rules of Research 1

1 The Purpose and Ethics of Research 3

1.1 The Purpose and Risks of Research 3

1.2 History of Harm to Humans 4

1.3 Ethical Issues in the Social Sciences 9

1.4 History of Harm to Animal Subjects in Research 10

1.4.1 Summary 12

1.5 Ethics, Principles, and Guidelines 12

1.6 Statutes and Regulations Protecting Humans and Animals in Research 16

1.7 More About Informed Consent 18

1.8 The Importance of Freedom to Withdraw 22

1.9 Separation of ProviderResearcher Role 22

1.10 Undue Influence 24

1.11 Anonymity 24

1.12 Summary 25

Section 2 Basic Research Designs and Validity 27

2 Research Validity 29

2.1 Internal Validity 30

2.1.1 History 30

2.1.2 Maturation 31

2.1.3 Measurement Error 32

2.1.4 Selection Bias and Random Assignment 33

2.1.5 Attrition 35

2.1.6 Experimenter Bias 35

2.1.7 Expectation 36

2.1.8 Sensitization and Practice Effects 36

2.1.9 Incorrect Conclusions of Causality 37

2.2 External Validity 37

2.3 Summary 45

3 Research Designs 47

3.1 The Lingo 47

3.2 BetweenSubjects Designs 49

3.2.1 More Examples of BetweenSubjects Designs 49

3.2.2 Statistical Analyses for BetweenSubjects Designs 50

3.3 WithinSubjects Designs/Repeated Measures 52

3.3.1 Statistical Analyses for WithinSubjects Designs 53

3.4 BetweenWithin Subjects Designs (Mixed Factorial/SplitPlot Designs) 54

3.4.1 Statistical Analyses for BetweenWithin Subjects Designs 55

3.5 Latin Square Designs 57

3.5.1 Summary 59

3.5.2 Double Latin Square Designs 59

3.5.3 GraecoLatin and Hyper GraecoLatin Square Designs 59

3.6 Nesting 60

3.7 Matching 60

3.8 Blocking 61

3.9 Nonexperimental Research 62

3.10 Case Studies 62

3.11 Summary 64

Section 3 The Nuts and Bolts of Data Analysis 65

4 Interpretation 67

4.1 Probability and Significance 67

4.2 The Null Hypothesis, Type I (), and Type II () Errors 68

4.3 Power 69

4.4 Managing Error Variance to Improve Power 71

4.5 Power Analyses 72

4.6 Effect Size 72

4.7 Confidence Intervals and Precision 74

4.8 Summary 76

5 Parametric Statistical Techniques 77

5.1 A Little More Lingo 77

5.1.1 Population Parameters Versus Sample Statistics 78

5.1.2 Data 78

5.1.2.1 Ratio and Interval Data 78

5.1.2.2 Ordinal Data 78

5.1.2.3 Nominal Data 79

5.1.3 Central Tendency 79

5.1.3.1 Mode 79

5.1.3.2 Median 79

5.1.3.3 Mean 86

5.1.4 Distributions 86

5.1.5 Dependent Variables 92

5.1.5.1 To Scale or Not to Scale 95

5.1.6 Summary 97

5.2 t Tests 97

5.2.1 Independent Samples t Tests 97

5.2.2 Matched Group Comparison 98

5.2.3 Assumptions of t Tests 99

5.2.4 More Examples of Studies Employing t Tests 100

5.2.5 Statistical Software Packages for Conducting t Tests 101

5.3 The NOVAs and Mixed Linear Model Analysis 101

5.3.1 ANOVA 102

5.3.1.1 ANOVA with a Multifactorial Design 104

5.3.1.2 Main Effects and Interactions 104

5.3.1.3 More Illustrations of Interactions and Main Effects 106

5.3.1.4 Assumptions of ANOVA 107

5.3.2 ANCOVA 109

5.3.3 MANOVA/MANCOVA 111 5.3.4 Stati...