Categorical Data Analysis Using SAS, Third Edition
SAS Institute, Jul 31, 2012 - Mathematics - 590 pages
Statisticians and researchers will find Categorical Data Analysis Using SAS, Third Edition, by Maura Stokes, Charles Davis, and Gary Koch, to be a useful discussion of categorical data analysis techniques as well as an invaluable aid in applying these methods with SAS. Practical examples from a broad range of applications illustrate the use of the FREQ, LOGISTIC, GENMOD, NPAR1WAY, and CATMOD procedures in a variety of analyses. Topics discussed include assessing association in contingency tables and sets of tables, logistic regression and conditional logistic regression, weighted least squares modeling, repeated measurements analyses, loglinear models, generalized estimating equations, and bioassay analysis. The third edition updates the use of SAS/STAT software to SAS/STAT 12.1 and incorporates ODS Graphics. Many additional SAS statements and options are employed, and graphs such as effect plots, odds ratio plots, regression diagnostic plots, and agreement plots are discussed. The material has also been revised and reorganized to reflect the evolution of categorical data analysis strategies. Additional techniques include such topics as exact Poisson regression, partial proportional odds models, Newcombe confidence intervals, incidence density ratios, and so on. This book is part of the SAS Press program.
What people are saying - Write a review
We haven't found any reviews in the usual places.
Other editions - View all
Analysis Using SAS asymptotic Categorical Data Analysis Chapter Charles Coefficient column compute confidence interval Confidence Limits Copyright covariance matrix datalines Davis Deviance DF Value Prob diagnosis displayed in Output distribution drug Estimate Standard Error Estimates Parameter exact p-value exact test explanatory variables female Frequency Gary G gender goodness-of-fit goodness-of-fit statistics input interaction Koch levels Likelihood Ratio log odds logistic regression loglinear model main effects model male Mantel-Haenszel Maura Maximum Likelihood Estimates Mean Scores Differ Model Information MODEL statement odds ratio Odds Ratio Estimates option order=data outcome p-value parameter estimates Pearson placebo Poisson regression Pr>ChiSq PROC CATMOD PROC FREQ proc genmod PROC LOGISTIC procedure proportional odds repeated measurements response functions Response Profile response variable Row Mean Scores sample score statistic specified statements request Stokes strata subjects Summary Statistics test statistic Third Edition Total treatment Type 3 Analysis Wald Chi-Square Pr weight count weighted least squares