Scale development : theory and applications / Robert F. DeVellis, University of North Carolina, Chapel Hill, USA.

Format:

Book

Author/Creator:

DeVellis, Robert F., author.

Language:

English

Subjects (All):

Scaling (Social sciences).

Physical Description:

xvii, 262 pages : illustrations ; 22 cm

Edition:

Fourth edition.

Place of Publication:

Los Angeles : SAGE, [2017]

Contents:

Chapter 1 Overview 1

General Perspectives on Measurement 2

Historical Origins of Measurement in Social Science 4

Early Examples 4

Emergence of Statistical Methods and the Role of Mental Testing 6

The Role of Psychophysics 6

Later Developments in Measurement 7

Evolution of Basic Concepts 7

Evolution of Mental Testing 8

Assessment of Mental Illness 8

Broadening the Domain of Psychometrics 12

The Role of Measurement in the Social Sciences 13

The Relationship of Theory to Measurement 13

Theoretical and Atheoretical Measures 14

Measurement Scales 15

All Scales Are Not Created Equal 17

Costs of Poor Measurement 19

Summary and Preview 20

Exercises 21

Chapter 2 Understanding the Latent Variable 23

Constructs Versus Measures 23

Latent Variable as the Presumed Cause of Item Values Path Diagrams 26

Diagrammatic Conventions 26

Path Diagrams in Scale Development 27

Further Elaboration of the Measurement Model 29

Classical Measurement Assumptions 29

Parallel Tests 30

Alternative Models 33

Choosing a Causal Model 36

Exercises 37

Note 37

Chapter 3 Reliability 39

Methods Based on the Analysis of Variance 40

Continuous Verstis Dichotomous Items 42

Internal Consistency 42

Coefficient Alpha 43

The Covariance Matrix 44

Covariance Matrices for Multi-Item Scales 45

Alpha and the Covariance Matrix 46

Alternative Formula for Alpha 50

Critique of Alpha 52

Remedies to Alpha's Limitations 57

Coefficient Omega (ω) 59

Reliability Based on Correlations Between Scale Scores 61

Alternate-Forms Reliability 61

Split-Half Reliability 62

Inter-Rater Agreement 66

Temporal Stability 67

Reliability of Change Scores 70

Reliability and Statistical Power 76

Generalizability Theory 77

Summary 80

Exercises 81

Notes 82

Chapter 4 Validity 83

Content Validity 84

Scope of the Variable and Implications for Content Validity 85

Criterion-Related Validity 92

Criterion-Related Validity Versus Accuracy 92

Construct Validity 95

Differentiating Construct From Criterion-Related Validity 95

Attenuation 97

How Strong Should Correlations Be to Demonstrate Construct Validity? 98

Multitrait-Multimethod Matrix 98

What About Face Validity? 100

Exercises 103

Chapter 5 Guidelines in Scale Development 105

Step 1 Determine Clearly What It Is You Want to Measure 105

Theory as an Aid to Clarity 105

Specificity as an Aid to Clarity 106

Being Clear About What to Include in a Measure 108

Step 2 Generate an Item Pool 109

Choose Items That Reflect the Scale's Purpose 109

Redundancy 110

Number of Items 113

Beginning the Process of Writing Items 113

Characteristics of Good and Bad Items 114

Positively and Negatively Worded Items 116

Conclusion 118

Step 3 Determine the Format for Measurement 118

Thurstone Scaling 119

Guttman Scaling 120

Scales With Equally Weighted Items 122

How Many Response Categories? 122

Specific Types of Response Formats 126

Likert Scale 127

Semantic Differential 129

Visual Analog 130

Numerical Response Formats and Basic Neural Processes 132

Binary Options 133

Item Time Frames 134

Step 4 Have Initial Item Pool Reviewed by Experts 134

Step 5 Consider Inclusion of Validation Items 136

Step 6 Administer Items to a Development Sample 137

Step 7 Evaluate the Items 139

Initial Examination of Items' Performance 140

Reverse Scoring 140

Item-Scale Correlations 142

Item Variances 142

Item Means 143

Dimensionality 143

Reliability 144

Step 8 Optimize Scale Length 146

Effect of Scale Length on Reliability 146

Effects of Dropping "Bad" Items 147

Tinkering With Scale length 148

Split Samples 149

Exercises 150

Note 151

Chapter 6 Factor Analysis 153

Overview of Factor Analysis 155

Examples of Methods Analogous to Factor Analytic Concepts 156

Example 1 156

Example 2 157

Shortcomings of These Methods 158

Conceptual Description of Factor Analysis 161

Extracting Factors 161

The First Factor 161

Subsequent Factors 164

Deciding How Many Factors to Extract 165

Rotating Factors 171

Rotation Analogy 1 172

Rotation Analogy 2 172

Rotation Analogy 3 175

Orthogonal Versus Oblique Rotation 180

Choosing Type of Rotation 184

Bifactor and Hierarchical Factor Models 185

Interpreting Factors 192

Principal Components Versus Common Factors 193

Same or Different? 194

Confirmatory Factor Analysis 197

Using Factor Analysis in Scale Development 199

Sample Size 203

Conclusion 204

Exercises 204

Chapter 7 An Overview of Item Response Theory 205

Item Difficulty 209

Item Discrimination 210

Guessing, or False Positives 211

Item-Characteristic Curves 213

IRT Applied to Multiresponse Items 217

Theta and Computerized Adaptive Testing (CAT) 224

Complexities of IRT 226

Conclusions 229

Exercises 231

Chapter 8 Measurement in the Broader Research Context 233

Before Scale Development 233

Look for Existing Tools 233

View the Construct in the Context of the Population of Interest 235

Decide on the Mode of Scale Administration 237

Consider the Scale in the Context of Other Measures or Procedures 237

After Scale Administration 239

Analytic Issues 239

Interpretation Issues 239

Generalizability 240

Final Thoughts 240

Small Measurement and Big Measurement 240

Canoes and Cruise Ships 240

Measurement "Canoes" and Measurement "Cruise Ships" 242

Practical Implications of Small Versus Big Measurement 244

Remember, Measurement Matters 246

Exercise 246.

Notes:

Includes bibliographical references and index.

ISBN:

9781506341569

150634156X

OCLC:

931226867