Advanced Log-Linear Models Using SAS

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SAS Institute, Oct 22, 2002 - Computers - 202 pages
In Advanced Log-Linear Models Using SAS, Daniel Zelterman applies his extensive SAS knowledge and biostatistics experience to illustrate how to use the GENMOD procedure to analyze log-linear models for categorical data. His wide variety of examples illustrate the statistical applications PROC GENMOD can perform. He thoroughly describes the models, provides real data examples, supplies the necessary code, and explains the output from GENMOD. The topics covered include the Pearson goodness-of-fit statistic; tables of categorical data; a review of log-linear model methods for rectangular tables of categorical data; extrapolation methods to estimate population size; new models and distributions for statistical analysis of data; and issues in power analysis and estimating sample size in experiments. The models take advantage of the wide class of generalized linear models and use real data from pharmaceutical studies and epidemiology, wildlife, and government statistics. Statisticians who have a basic understanding both of SAS and of the analysis of categorical data will greatly benefit from this book. The discussion of each model and method emphasizes statistical aspects, such as interpretation of results, rather than programming skills. The numerous examples are used to motivate the theory and methods as they are discussed.

About the author (2002)

Daniel Zelterman, Ph.D., is Professor of Epidemiology and Public Health, Division of Biostatistics, at Yale University and is the Director of the Biostatistics Core of the Yale Cancer Center. Before moving to Yale in 1995, he taught at the University of Minnesota and at the State University of New York at Albany. He is an elected Fellow of the American Statistical Association and is an Associate of Biometrics and other statistical journals. A SAS user since 1977, he remembers when the CARDS statement had a very different meaning. In his spare time Daniel plays bassoon in several chamber and orchestral groups in the New Haven area. !-- minimal footer --

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