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This page provides some brief discussion of statistical software that can be used to analyze categorical data.
S-PLUS has many functions and libraries that are used for analyzing categorical data. Click here for more details.
R has many functions and libraries that are used for analyzing categorical data. Click here for more details.
Several procedures in SAS are used for analyzing categorical data. Click here for more details.
SPSS does not have a generalized linear models module, but it includes methods for loglinear models, logistic and probit regression, and multinomial response models. Books that discuss analyzing categorical data using SPSS include Categorical Data Analysis with SAS and SPSS Applications by Bayo Lawal and SPSS 12.0 Advanced Models.
LIMDEP contains functionality for a wide array of count regression models, including Poisson and negative binomial models that provide for zero inflation, hurdle models, and sandwich covariance estimation, binary response models, and multinomial response models.
StatXact and LogXact provide extensive capabilities for exact (conditional) analyses of many different types, using state-of-the-art algorithms. StatXact includes small-sample confidence intervals, Fisher's exact test, tests for homogeneous association and conditional independence. LogXact performs exact logistic regression. Click here for a pdf file describing exact inference for categorical data as implemented in StatXact.
CDAS (the Categorical Data Analysis System) is a freeware DOS program that fits various models to categorical data, including association models (with the possibility of covariates), loglinear models, and latent class models. The ANOAS program mentioned in the Preface of the book (page ix) is available as a module of this program.
Stata can be used to fit many count regression models, including Poisson and negative binomial models that provide for zero inflation, binary response models, and multinomial response models. The book A Handbook of Statistical Analyses Using Stata, Fourth Edition by S. Rabe-Hesketh and B.S. Everitt discusses analyzing categorical data using Stata.