Categorical and nonparametric data analysis : choosing the best statistical technique /
Nussbaum, E. Michael,author.
Featuring in-depth coverage and nonparametric statistics, this book provides a conceptual framework for choosing the most appropriate type of test in various research scenarios. Class tested at the University of Nevada, the book's clear explanations of the underlying assumptions, computer simulations, and Exploring the Concept boxes help reduce readers anxiety. Problems inspired by actual studies provide  illustrations of the techniques. The underlying assumptions of each test and the factors that impact validity and statistical power are reviewed so readers can explain their assumptions and how tests work in future publications. Numerous examples form psychology, education, and other social sciences demonstrate varied applications of the material. Basic statistics and probability are reviewed for those who need a refresher. Mathematical derivations are placed in optional appendices for those interested in this detailed coverage.
Includes bibliographical references and index.
Levels of measurement, probability, and the binomial formula -- Estimation and hypothesis testing -- Random variables and probability distributions -- Contingency tables : the chi-square test and associated effect sizes -- Contingency tables : special situations -- Basic nonparametric tests for ordinal data -- Nonparametric tests for multiple or related samples -- Advanced rank tests (for interactions and robust ANOVA) -- Linear regression and generalized linear models -- Binary logistic regression -- Multinomial logistic, ordinal, and poisson regression -- Log-linear analysis -- General estimating equations -- Estimation procedures -- Choosing the best statistical technique.
Featuring in-depth coverage and nonparametric statistics, this book provides a conceptual framework for choosing the most appropriate type of test in various research scenarios. Class tested at the University of Nevada, the book's clear explanations of the underlying assumptions, computer simulations, and Exploring the Concept boxes help reduce readers anxiety. Problems inspired by actual studies provide  illustrations of the techniques. The underlying assumptions of each test and the factors that impact validity and statistical power are reviewed so readers can explain their assumptions and how tests work in future publications. Numerous examples form psychology, education, and other social sciences demonstrate varied applications of the material. Basic statistics and probability are reviewed for those who need a refresher. Mathematical derivations are placed in optional appendices for those interested in this detailed coverage.
Multivariate analysis.
Nonparametric statistics.