Categorical Data Analysis for the Behavioral and Social Sciences

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A01=Cindy M. Walker
A01=Razia Azen
Author_Cindy M. Walker
Author_Razia Azen
Behavioral science
Bernoulli Distribution
binomial
Binomial Distribution
Categorical data analysis
categorical data modeling in psychology
Category=GPS
Category=JMB
Category=PBT
Common Odds Ratio
Common Odds Ratio Estimate
Conditional Association
Conditional Odds Ratios
confidence
Contingency Table
Data Set
distribution
Dummy Coding
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
ernoulli
Expected Cell Counts
Fit GLMMs
frequentist
Homogeneous Association
hypothesis
likelihood
Likelihood Ratio Test
Log Linear Model
Log Odds
log-linear
logistic
multinomial
multinomial logistic regression
Non-restricted Model
Partial Tables
Pearson Chi Squared Test Statistic
Poisson
Predicted Log Odds
Proportional Odds Assumption
Proportional Odds Model
psychometric analysis
R
R programming statistics
Random Intercept Model
ratio
SAS
SAS Output
SAS statistical modeling
Saturated Model
social science quantitative methods
Social sciences
SPSS
SPSS data analysis
SPSS Menu
SPSS Output
SPSS Syntax
Stata
statistic
statistical analysis
test
wald

Product details

  • ISBN 9780367352769
  • Weight: 585g
  • Dimensions: 178 x 254mm
  • Publication Date: 27 May 2021
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Featuring a practical approach with numerous examples, the second edition of Categorical Data Analysis for the Behavioral and Social Sciences focuses on helping the reader develop a conceptual understanding of categorical methods, making it a much more accessible text than others on the market. The authors cover common categorical analysis methods and emphasize specific research questions that can be addressed by each analytic procedure, including how to obtain results using SPSS, SAS, and R, so that readers are able to address the research questions they wish to answer.

Each chapter begins with a "Look Ahead" section to highlight key content. This is followed by an in-depth focus and explanation of the relationship between the initial research question, the use of software to perform the analyses, and how to interpret the output substantively. Included at the end of each chapter are a range of software examples and questions to test knowledge.

New to the second edition:

  • The addition of R syntax for all analyses and an update of SPSS and SAS syntax.
  • The addition of a new chapter on GLMMs.
  • Clarification of concepts and ideas that graduate students found confusing, including revised problems at the end of the chapters.

Written for those without an extensive mathematical background, this book is ideal for a graduate course in categorical data analysis taught in departments of psychology, educational psychology, human development and family studies, sociology, public health, and business. Researchers in these disciplines interested in applying these procedures will also appreciate this book’s accessible approach.

Razia Azen is Professor at the University of Wisconsin–Milwaukee, USA, where she teaches basic and advanced statistics courses. Her research focuses on methods that compare the relative importance of predictors in linear models. She received her MS in statistics and PhD in quantitative psychology from the University of Illinois, USA.

Cindy M. Walker is President and CEO of Research Analytics Consulting, LLC. Previously, she was a professor at the University of Wisconsin–Milwaukee, where she taught basic and advanced measurement and statistics courses. Her research focuses on applied issues in psychometrics. She received her PhD in quantitative research methodologies from the University of Illinois at Urbana–Champaign, USA.

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