ISBN-10:
1118927095
ISBN-13:
9781118927090
Pub. Date:
10/24/2016
Publisher:
Wiley
Categorical Statistics for Communication Research / Edition 1

Categorical Statistics for Communication Research / Edition 1

by Bryan E. Denham

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Overview

Categorical Statistics for Communication Research / Edition 1

Categorical Statistics for CommunicationResearch presents scholars with a discipline-specific guide to categorical data analysis. The text blends necessary background information and formulas for statistical procedures with data analyses illustrating techniques such as log- linear modeling and logistic regression analysis.

  • Provides techniques for analyzing categorical data from a communication studies perspective
  • Provides an accessible presentation of techniques for analyzing categorical data for communication scholars and other social scientists working at the advanced undergraduate and graduate teaching levels
  • Illustrated with examples from different types of communication research such as health, political and sports communication and entertainment
  • Includes exercises at the end of each chapter and a companion website containing exercise answers and chapter-by-chapter PowerPoint slides

Product Details

ISBN-13: 9781118927090
Publisher: Wiley
Publication date: 10/24/2016
Pages: 296
Product dimensions: 8.90(w) x 6.00(h) x 0.40(d)

About the Author

Bryan E. Denham is Professor of Communication at Clemson University. An expert on logistic regression and log-linear modeling, he has published articles on teaching empirical research methods and applying categorical statistics to social data in outlets such as the Journal of Communication, Journalism & Mass Communication Quarterly, Journalism & Mass Communication Educator, and the Journal of Risk Research. He has taught empirical methods at both the graduate and undergraduate levels and has frequently served as a resource for both faculty and students in the use of categorical statistics from areas such as health, political, and science communication.

Table of Contents

Preface xiii

Acknowledgments xix

About the Companion Website xx

1 Introduction to Categorical Statistics 1

Historical Overview 2

Probability Distributions and Parameter Estimation 5

Example of Maximum Likelihood Estimation 6

A Note on Statistical Software 7

Chapter Summary 7

Chapter Exercises 8

Notes 9

References 10

2 Univariate Goodness of Fit and Contingency Tables in Two Dimensions 12

Chi-Square Test for Goodness of Fit 12

Chi-Square Test of Independence in Contingency Tables 14

Likelihood Ratio Statistic 16

Exact Tests for Small Samples 17

McNemar's Test for Correlated Samples 18

Measures of Association 19

Odds Ratio 19

Relative Risk 21

Phi Coefficient 22

Cramer's V 23

Pearson's Contingency Coefficient 24

Kendall's Tan 25

Goodman and Kruskal's Gamma 28

Somers'd 28

Points of Concern in Bivariate Analyses 29

SPSS Analyses 31

Testing Goodness of Tit in SPSS 31

Testing Independence in SPSS 32

A Note on Style 34

Chapter Summary 35

Chapter Exercises 36

Notes 37

References 38

3 Contingency Tables in Three Dimensions 41

Moving from Two to Three Dimensions 41

Cochran-Mantel-Haenszel Test 43

Breslow-Day Test 45

An Example in Public Health 48

An Example in Political Communication 50

Chapter Summary 54

Chapter Exercises 54

Note 56

References 56

4 Log-linear Analysis 58

Development of Log-linear Models 59

Examples of Published Research 59

Log-linear Analysis: Fundamentals 60

Two-way Tables 61

Three-way Models 62

Goodness of Fit and Model Selection 64

Descriptive Statistics and Residuals for the Fitted Model 65

Parameter Estimation 67

Ordinal Log-linear Analysis 70

Three Ordinal Measures 72

More Complex Models 75

Visual Displays 78

Chapter Summary 83

Chapter Exercises 83

Notes 85

References 86

5 Logit Log-linear Analysis 90

Examples of Published Research 91

Logit Log-linear Analysis: Fundamental Components 92

Logit Model with One Response Measure 93

Logit Model with Two Response Measures 98

SPSS Example 106

Correspondence Analysis 113

Chapter Summary 114

Chapter Exercises 114

References 116

6 Binary Logistic Regression 119

Examples of Published Research 120

Binary Logistic Regression: Fundamentals 121

Simple Logistic Regression Analysis 123

Multiple Logistic Regression Analysis 124

Interactions 127

Model Assessment 128

Additional Statistics 128

Diagnostic Considerations 129

Binary Logistic Regression in SPSS 130

Chapter Summary 144

Chapter Exercises 144

Notes 146

References 146

7 Multinomial Logistic Regression 153

Examples of Published Research 154

Multinomial Logistic Regression: Fundamentals 154

Simple Multinomial Logistic Regression Analysis 155

Multiple Multinomial Logistic Regression Analysis 157

Conditional Logit Modeling 159

Multinomial Logistic Regression in SPSS 160

Chapter Summary 165

Chapter Exercises 165

Notes 168

References 168

8 Ordinal Logistic Regression 171

Examples of Published Research 172

Ordinal Logistic Regression: Fundamentals 172

Simple Ordinal Logistic Regression Analysis 175

Multiple Ordinal Logistic Regression Analysis 176

Interactions 180

Ordinal Logistic Regression in SPSS 182

Chapter Summary 184

Chapter Exercises 186

Notes 193

References 193

9 Probit Analysis 198

Examples of Published Research 199

Probit Analysis: Fundamentals 200

Binary Prohit Analysis 201

Ordinal Probit Analysis 206

Multinomial Probit Analysis 208

Interactions 208

Chapter Summary 211

Chapter Exercises 211

Notes 212

References 213

10 Poisson and Negative Binomial Regression 216

Examples of Published Research 217

Poisson Regression: Fundamentals 218

Negative Binomial Regression: Fundamentals 220

Additional Techniques 222

SPSS Analyses 223

Chapter Summary 227

Chapter Exercises 227

Notes 229

References 229

11 Interrater Agreement Measures for Nominal and Ordinal Data 232

Analysis of Nominal Data with Two Raters 233

Analysis of Nominal Data with Multiple Raters 238

Analysis of Ordinal Data with Two Raters 241

Analysis of Ordinal Data with Multiple Raters 245

Kappa Coefficient in SPSS 247

Intraclass Correlation Coefficients in SPSS 249

Chapter Summary 250

Chapter Exercises 250

Notes 251

References 252

12 Concluding Communication 255

References 257

Appendix A Chi-Square Table 259

Appendix B SPSS Code for Selected Procedures 261

Index 266

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