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Title:
Categorical statistics for communication research / Bryan E. Denham.
Author:
Denham, Bryan E., 1967- author.
Published:
Chichester, West Sussex ; Malden, MA : John Wiley & Sons, Ltd, 2017.

©2017
Description:
xviii, 270 pages ; 23 cm
Bibliography:
Includes bibliographical references and index.
ISBN:
1118927095 paperback

1118927109 hardcover alkaline paper

9781118927090 paperback

9781118927106 hardcover alkaline paper

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Summary

Summary

Categorical Statistics for Communication Research 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


Author Notes

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 method 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, spoils, and science communication.


Table of Contents

Prefacep. xiii
Acknowledgmentsp. xix
About the Companion Websitep. xx
1 Introduction to Categorical Statisticsp. 1
Historical Overviewp. 2
Probability Distributions and Parameter Estimationp. 5
Example of Maximum Likelihood Estimationp. 6
A Note on Statistical Softwarep. 7
Chapter Summaryp. 7
Chapter Exercisesp. 8
Notesp. 9
Referencesp. 10
2 Univariate Goodness of Fit and Contingency Tables in Two Dimensionsp. 12
Chi-Square Test for Goodness of Fitp. 12
Chi-Square Test of Independence in Contingency Tablesp. 14
Likelihood Ratio Statisticp. 16
Exact Tests for Small Samplesp. 17
McNemar's Test for Correlated Samplesp. 18
Measures of Associationp. 19
Odds Ratiop. 19
Relative Riskp. 21
Phi Coefficientp. 22
Cramer's Vp. 23
Pearson's Contingency Coefficientp. 24
Kendall's Tanp. 25
Goodman and Kruskal's Gammap. 28
Somers'dp. 28
Points of Concern in Bivariate Analysesp. 29
SPSS Analysesp. 31
Testing Goodness of Tit in SPSSp. 31
Testing Independence in SPSSp. 32
A Note on Stylep. 34
Chapter Summaryp. 35
Chapter Exercisesp. 36
Notesp. 37
Referencesp. 38
3 Contingency Tables in Three Dimensionsp. 41
Moving from Two to Three Dimensionsp. 41
Cochran-Mantel-Haenszel Testp. 43
Breslow-Day Testp. 45
An Example in Public Healthp. 48
An Example in Political Communicationp. 50
Chapter Summaryp. 54
Chapter Exercisesp. 54
Notep. 56
Referencesp. 56
4 Log-linear Analysisp. 58
Development of Log-linear Modelsp. 59
Examples of Published Researchp. 59
Log-linear Analysis: Fundamentalsp. 60
Two-way Tablesp. 61
Three-way Modelsp. 62
Goodness of Fit and Model Selectionp. 64
Descriptive Statistics and Residuals for the Fitted Modelp. 65
Parameter Estimationp. 67
Ordinal Log-linear Analysisp. 70
Three Ordinal Measuresp. 72
More Complex Modelsp. 75
Visual Displaysp. 78
Chapter Summaryp. 83
Chapter Exercisesp. 83
Notesp. 85
Referencesp. 86
5 Logit Log-linear Analysisp. 90
Examples of Published Researchp. 91
Logit Log-linear Analysis: Fundamental Componentsp. 92
Logit Model with One Response Measurep. 93
Logit Model with Two Response Measuresp. 98
SPSS Examplep. 106
Correspondence Analysisp. 113
Chapter Summaryp. 114
Chapter Exercisesp. 114
Referencesp. 116
6 Binary Logistic Regressionp. 119
Examples of Published Researchp. 120
Binary Logistic Regression: Fundamentalsp. 121
Simple Logistic Regression Analysisp. 123
Multiple Logistic Regression Analysisp. 124
Interactionsp. 127
Model Assessmentp. 128
Additional Statisticsp. 128
Diagnostic Considerationsp. 129
Binary Logistic Regression in SPSSp. 130
Chapter Summaryp. 144
Chapter Exercisesp. 144
Notesp. 146
Referencesp. 146
7 Multinomial Logistic Regressionp. 153
Examples of Published Researchp. 154
Multinomial Logistic Regression: Fundamentalsp. 154
Simple Multinomial Logistic Regression Analysisp. 155
Multiple Multinomial Logistic Regression Analysisp. 157
Conditional Logit Modelingp. 159
Multinomial Logistic Regression in SPSSp. 160
Chapter Summaryp. 165
Chapter Exercisesp. 165
Notesp. 168
Referencesp. 168
8 Ordinal Logistic Regressionp. 171
Examples of Published Researchp. 172
Ordinal Logistic Regression: Fundamentalsp. 172
Simple Ordinal Logistic Regression Analysisp. 175
Multiple Ordinal Logistic Regression Analysisp. 176
Interactionsp. 180
Ordinal Logistic Regression in SPSSp. 182
Chapter Summaryp. 184
Chapter Exercisesp. 186
Notesp. 193
Referencesp. 193
9 Probit Analysisp. 198
Examples of Published Researchp. 199
Probit Analysis: Fundamentalsp. 200
Binary Prohit Analysisp. 201
Ordinal Probit Analysisp. 206
Multinomial Probit Analysisp. 208
Interactionsp. 208
Chapter Summaryp. 211
Chapter Exercisesp. 211
Notesp. 212
Referencesp. 213
10 Poisson and Negative Binomial Regressionp. 216
Examples of Published Researchp. 217
Poisson Regression: Fundamentalsp. 218
Negative Binomial Regression: Fundamentalsp. 220
Additional Techniquesp. 222
SPSS Analysesp. 223
Chapter Summaryp. 227
Chapter Exercisesp. 227
Notesp. 229
Referencesp. 229
11 Interrater Agreement Measures for Nominal and Ordinal Datap. 232
Analysis of Nominal Data with Two Ratersp. 233
Analysis of Nominal Data with Multiple Ratersp. 238
Analysis of Ordinal Data with Two Ratersp. 241
Analysis of Ordinal Data with Multiple Ratersp. 245
Kappa Coefficient in SPSSp. 247
Intraclass Correlation Coefficients in SPSSp. 249
Chapter Summaryp. 250
Chapter Exercisesp. 250
Notesp. 251
Referencesp. 252
12 Concluding Communicationp. 255
Referencesp. 257
Appendix A Chi-Square Tablep. 259
Appendix B SPSS Code for Selected Proceduresp. 261
Indexp. 266