[下载]Statistical Methods for Categorical Data Analysis

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<H1 align=center>
</H1><P align=center><b>Daniel A. Powers
Department of Sociology
University of Texas at Austin

Yu Xie
Department of Sociology
University of Michigan

Copyright 1999
Academic Press, Inc. </b></P><P align=left></P><H2><A>Contents</A> </H2><!--Table of Contents--><UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00200000000000000000" target="_blank" >Preface</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00300000000000000000" target="_blank" >Introduction</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00310000000000000000" target="_blank" >Why Categorical Data Analysis?</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00311000000000000000" target="_blank" >Defining Categorical Variables</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00312000000000000000" target="_blank" >Dependent and Independent Variables</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00313000000000000000" target="_blank" >Categorical Dependent Variables</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00314000000000000000" target="_blank" >Types of Measurement</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00320000000000000000" target="_blank" >Two Philosophies of Categorical Data</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00321000000000000000" target="_blank" >The Transformational Approach</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00322000000000000000" target="_blank" >The Latent Variable Approach</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00330000000000000000" target="_blank" >An Historical Note</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00340000000000000000" target="_blank" >Approach of This Book</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00341000000000000000" target="_blank" >Organization of the Book</A> </LI></UL></LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00400000000000000000" target="_blank" >Review of Linear Regression Models</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00410000000000000000" target="_blank" >Regression Models</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00411000000000000000" target="_blank" >Three Conceptualizations of Regression</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00412000000000000000" target="_blank" >Anatomy of Linear Regression</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00413000000000000000" target="_blank" >Basics of Statistical Inference</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00414000000000000000" target="_blank" >Tension between Accuracy and Parsimony</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00420000000000000000" target="_blank" >Linear Regression Models Revisited</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00421000000000000000" target="_blank" >Least Squares Estimation</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00422000000000000000" target="_blank" >Maximum Likelihood Estimation</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00423000000000000000" target="_blank" >Assumptions for Least Squares Regression</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00424000000000000000" target="_blank" >Comparisons of Conditional Means</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00425000000000000000" target="_blank" >Linear Models with Weaker Assumptions</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00430000000000000000" target="_blank" >Differences between Categorical and
Continuous Dependent Variables</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00431000000000000000" target="_blank" >A Working Typology</A> </LI></UL></LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00500000000000000000" target="_blank" >Logit and Probit Models for Binary Data</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00510000000000000000" target="_blank" >Introduction to Binary Data</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00520000000000000000" target="_blank" >The Transformational Approach</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00521000000000000000" target="_blank" >The Linear Probability Model</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00522000000000000000" target="_blank" >The Logit Model</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00523000000000000000" target="_blank" >The Probit Model</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00524000000000000000" target="_blank" >An Application Using Grouped Data</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00530000000000000000" target="_blank" >Justification of Logit and Probit
Models</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00531000000000000000" target="_blank" >The Latent Variable Approach</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00532000000000000000" target="_blank" >Extending the Latent Variable Approach</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00533000000000000000" target="_blank" >Estimation of Binary Response Models</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00534000000000000000" target="_blank" >Goodness-of-Fit and Model Selection</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00535000000000000000" target="_blank" >Hypothesis Testing and Statistical Inference</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00540000000000000000" target="_blank" >Interpreting Estimates</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00541000000000000000" target="_blank" >The Odds-Ratio</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00542000000000000000" target="_blank" >Marginal Effects</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00543000000000000000" target="_blank" >An Application Using Individual-Level Data</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00550000000000000000" target="_blank" >Alternative Probability Models</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00551000000000000000" target="_blank" >The Complementary Log-Log Model</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00552000000000000000" target="_blank" >Programming Binomial Response Models</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00560000000000000000" target="_blank" >Summary</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00600000000000000000" target="_blank" >Loglinear Models for Contingency Tables</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00610000000000000000" target="_blank" >Contingency Tables</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00611000000000000000" target="_blank" >Types of Contingency Tables</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00612000000000000000" target="_blank" >An Example and Notation</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00613000000000000000" target="_blank" >Independence and the Pearson <!-- MATH: $\protect\pmb\chi ^{2}$ --><IMG src="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/img11.gif" align=middle border=0> Statistic</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00620000000000000000" target="_blank" >Measures of Association</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00621000000000000000" target="_blank" >Homogeneous Proportions</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00622000000000000000" target="_blank" >Relative Risks</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00623000000000000000" target="_blank" >Odds-Ratios</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00624000000000000000" target="_blank" >The Invariance Property of Odds-Ratios</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00630000000000000000" target="_blank" >Estimation and Goodness-of-Fit</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00631000000000000000" target="_blank" >Simple Models and the Pearson <!-- MATH: $\protect\pmb\chi ^{2}$ --><IMG src="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/img11.gif" align=middle border=0> Statistic</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00632000000000000000" target="_blank" >Sampling Models and Maximum Likelihood
Estimation</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00633000000000000000" target="_blank" >The Likelihood-Ratio Chi-Squared Statistic</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00634000000000000000" target="_blank" >Bayesian Information Criterion</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00640000000000000000" target="_blank" >Models for Two-Way Tables</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00641000000000000000" target="_blank" >The General Setup</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00642000000000000000" target="_blank" >Normalization</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00643000000000000000" target="_blank" >Interpretation of Parameters</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00644000000000000000" target="_blank" >Topological Model</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00645000000000000000" target="_blank" >Quasi-Independence Model</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00646000000000000000" target="_blank" >Symmetry and Quasi-Symmetry</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00647000000000000000" target="_blank" >Crossings Model</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00650000000000000000" target="_blank" >Models for Ordinal Variables</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00651000000000000000" target="_blank" >Linear-by-Linear Association</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00652000000000000000" target="_blank" >Uniform Association</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00653000000000000000" target="_blank" >Row-Effect and Column-Effect Models</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00654000000000000000" target="_blank" >Goodman's <IMG src="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/img13.gif" align=bottom border=0> Model</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00660000000000000000" target="_blank" >Models for Multiway Tables</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00661000000000000000" target="_blank" >Three-Way Tables</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00662000000000000000" target="_blank" >The Saturated Model for Three-Way Tables</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00663000000000000000" target="_blank" >Collapsibility</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00664000000000000000" target="_blank" >Classes of Models for Three-Way Tables</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00665000000000000000" target="_blank" >Analysis of Variation in Association</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00666000000000000000" target="_blank" >Model Selection</A> </LI></UL></LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00700000000000000000" target="_blank" >Statistical Models for Rates</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00710000000000000000" target="_blank" >Introduction</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00720000000000000000" target="_blank" >Log-Rate Models</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00721000000000000000" target="_blank" >The Role of Exposure</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00722000000000000000" target="_blank" >Estimating Log-Rate Models</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00723000000000000000" target="_blank" >Illustration</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00724000000000000000" target="_blank" >Interpretation</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00730000000000000000" target="_blank" >Discrete-Time Hazard Models</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00731000000000000000" target="_blank" >Data Structure</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00732000000000000000" target="_blank" >Estimation</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00740000000000000000" target="_blank" >Semiparametric Rate Models</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00741000000000000000" target="_blank" >The Piecewise Constant Exponential Model</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00742000000000000000" target="_blank" >The Cox Model</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00750000000000000000" target="_blank" >Models for Panel Data</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00751000000000000000" target="_blank" >Fixed Effects Models for Binary Data</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00752000000000000000" target="_blank" >Random Effects Models for Binary Data</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00760000000000000000" target="_blank" >Unobserved Heterogeneity in Event-History Models</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00761000000000000000" target="_blank" >The Gamma Mixture Model</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00770000000000000000" target="_blank" >Summary</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00800000000000000000" target="_blank" >Models for Ordinal Dependent Variables</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00810000000000000000" target="_blank" >Introduction</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00820000000000000000" target="_blank" >Scoring Methods</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00821000000000000000" target="_blank" >Integer Scoring</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00822000000000000000" target="_blank" >Midpoint Scoring</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00823000000000000000" target="_blank" >Normal Score Transformation</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00824000000000000000" target="_blank" >Scaling with Additional Information</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00830000000000000000" target="_blank" >Logit Models for Grouped Data</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00831000000000000000" target="_blank" >Baseline, Adjacent, and Cumulative Logits</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00832000000000000000" target="_blank" >Adjacent Category Logit Model</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00833000000000000000" target="_blank" >Adjacent Category Logit Models and Loglinear Models</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00840000000000000000" target="_blank" >Ordered Logit and Probit Models</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00841000000000000000" target="_blank" >Cumulative Logits and Probits</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00842000000000000000" target="_blank" >The Ordered Logit Model</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00843000000000000000" target="_blank" >The Ordered Probit Model</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00844000000000000000" target="_blank" >The Latent Variable Approach</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00845000000000000000" target="_blank" >Estimation</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00846000000000000000" target="_blank" >Marginal Effects</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00850000000000000000" target="_blank" >Summary</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00900000000000000000" target="_blank" >Models for Unordered Dependent Variables</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00910000000000000000" target="_blank" >Introduction</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00920000000000000000" target="_blank" >Multinomial Logit Models</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00921000000000000000" target="_blank" >Review of the Binary Logit Model</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00922000000000000000" target="_blank" >General Setup for the Multinomial Logit
Model</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00930000000000000000" target="_blank" >The Standard Multinomial Logit
Model</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00931000000000000000" target="_blank" >Estimation</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00932000000000000000" target="_blank" >Interpreting Results from Multinomial Logit
Models</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00940000000000000000" target="_blank" >Loglinear Models for Grouped Data</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00941000000000000000" target="_blank" >Two-Way Tables</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00942000000000000000" target="_blank" >Three- and Higher-Way Tables</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00950000000000000000" target="_blank" >The Latent Variable Approach</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00960000000000000000" target="_blank" >The Conditional Logit Model</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00961000000000000000" target="_blank" >Interpretation</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00962000000000000000" target="_blank" >The Mixed Model</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00970000000000000000" target="_blank" >Specification Issues</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00971000000000000000" target="_blank" >Independence of Irrelevant Alternatives:
The IIA Assumption</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00972000000000000000" target="_blank" >Sequential Logit Models</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION00980000000000000000" target="_blank" >Summary</A> </LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001000000000000000000" target="_blank" >The Matrix Approach to Regression</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001010000000000000000" target="_blank" >Introduction</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001020000000000000000" target="_blank" >Matrix Algebra</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001021000000000000000" target="_blank" >The Matrix Approach to Regression</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001022000000000000000" target="_blank" >Basic Matrix Operations</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001023000000000000000" target="_blank" >Numerical Example</A> </LI></UL></LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001100000000000000000" target="_blank" >Maximum Likelihood Estimation</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001110000000000000000" target="_blank" >Introduction</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001120000000000000000" target="_blank" >Basic Principles</A>
<UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001121000000000000000" target="_blank" >Example 1: Binomial Proportion</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001122000000000000000" target="_blank" >Example 2: Normal Mean and Variance</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001123000000000000000" target="_blank" >Example 3: Binary Logit Model</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001124000000000000000" target="_blank" >Example 4: Loglinear Model</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001125000000000000000" target="_blank" >Iteratively Reweighted Least Squares</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001126000000000000000" target="_blank" >Generalized Linear Models</A>
<LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001127000000000000000" target="_blank" >Minimum <!-- MATH: $\pmb{\chi^2}$ --><IMG src="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/img11.gif" align=middle border=0> Estimation</A> </LI></UL></LI></UL><LI><a href="http://www.la.utexas.edu/research/faculty/dpowers/book/htmlbook/book.html#SECTION001200000000000000000" target="_blank" >Bibliography</A> </LI></UL><!--End of Table of Contents--><!--SKIP
<H1><A>
Preface</A></H1>

In this book, we intend to give a comprehensive introduction to methods and
models for the analysis of categorical data and their applications in social
science research. The primary audiences are graduate students and
practicing researchers in social science. The book also serves as a
reference.

One feature that distinguishes our book from other books on the topic is our
explicit aim to integrate the transformational approach and the latent
variable approach, two diverse but complementary traditions dealing with the
analysis of categorical data. The statistical, or transformational, approach
to categorical data analysis is most familiar to researchers in demography
and biostatistics, whereas the latent variable approach is often taken by
economists. A discussion of the two approaches is given in Chapter 1.

We assume that the reader has prior knowledge such as that covered
in a typical applied regression course but not necessarily in advanced
mathematical statistics. Although some technical details are unavoidable
in a book like this, we make the book accessible by resorting to
substantive examples. Some readers may wish to skip portions of the book
that are technical without losing much appreciation of the book.

To utilize the internet technology fully, we have set up a website
for the book at




http://www.la.utexas.edu/research/faculty/dpowers/book.<a href="#foot111" target="_blank" ><SUP>1.1</SUP></A>





The website contains the data sets and the programming codes
in several popular statistical packages (e.g., GLIM [Numerical
Algorithms Group 1986], LIMDEP [Greene 1995], SAS [SAS Institute 1990],
STATA [Stata Corporation 1995], and TDA [Rowher 1995]) for the examples
discussed in the book. The website provides some GLIM macros and
GAUSS (Aptech Systems 1997) subroutines to illustrate details of estimation
as well as several applications of specialized programs for models that
cannot be estimated in a standard software package. We will continue to update
the website (1) to provide exercises, (2) to add new examples,
(3) to expand to other software packages, and (4) to provide other
related materials.

<H2><A>
Use of This Text in a Course on Categorical Data Models</A></H2>

This book is appropriate for a single-term course in categorical data
modeling. Chapters 1 and 2 provide an introduction and basic foundation
for the course. Our view is that, regardless of the type of data, a
regression-type modeling approach can be an appropriate analytic method.
Chapter 3 provides an introduction and detailed treatment of regression
models for binary data. Chapter 4 goes into greater detail on the
methods for analyzing contingency tables. Chapter 5 discusses models for
transition rates. The core sections include Sections 5.1-5.3. Sections
5.4-5.6 can be omitted without loss of continuity. Chapters 6 and 7
provide an overview of methods for ordered and nonordered categorical
responses. This material is linked to the contingency table approach of
Chapter 4 and the latent variable framework outlined in Chapter 3.

<H2><A>
Acknowledgments</A></H2>

At various stages of the book project, we benefited from the
encouragement of and association with the following scholars: Paul
Allison, Mark Becker, John Fox, Richard Gonzalez, Leo Goodman, David
Grusky, Robert Hauser, Michael Hout, Kenneth Land, Scott Long, Charles
Manski, Robert Mare, Bill Mason, Susan Murphy, Trond Peterson, Adrian Raftery,
Steve Raudenbush, Arthur Sakamoto, Herbert Smith, Michael Sobel, Chris Winship, Larry Wu, and
Kazuo Yamaguchi. In addition, we extend our gratitude to many graduate
students who have taken statistics courses from us and inspired us to
write the book.

A Dean's Fellowship at the University of Texas at Austin to Dan Powers,
a National Science Foundation's Young Investigator Award to Yu Xie, and
University of Michigan's internal funds to Yu Xie provided partial
support for this project.

We also thank the external reviewers for providing                valuable critiques
on early versions of the manuscript and                Pam Bennett,                John Fox,
Kimberly Goyette, and James Raymo for carefully proofreading the final
version of the manuscript and providing programming examples.
We alone are responsible for errors that remain. Last, but not least,
we thank J. Scott Bentley, our editor at Academic Press, for initiating
the project and then making efforts to bring it to completion.








Daniel A. Powers

Yu Xie

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关键词：Statistical Categorical statistica statistic Analysis Copyright

Website for CATEGORICAL DATA ANALYSIS, 2nd edition

For the second edition of Categorical Data Analysis by Alan Agresti (Wiley, 2002), this site contains (1) information on the use of other software (such as R and S-plus, Stata, SPSS, StatXact and LogXact) not covered in Appendix A of the text (which discusses SAS in some detail), (2) data sets for examples in the form of complete SAS programs for conducting the analyses, (3) data sets used in some of the homework exercises, (4) short answers for many of the odd-numbered exercises, (5) extra exercises, and (6) corrections of errors in early printings of the book. Also, there's (7) a review paper about Bayesian methods for categorical data analysis.

1. Software for categorical data analyses: Here is a file containing information and links for several software packages as well as a link to a manual by Dr. Laura Thompson for using S-Plus and R to perform the examples in the text.

• Software

2. Primary datasets: For data sets for many of the main examples in the text, in the form of SAS programs for conducting the analyses, click on

• Primary datasets

3. Other datasets not shown in text: Here is a pdf file of

• other datasets used in some of the homework exercises for which tables are not shown in the text.

Here is a html file of these

• other datasets.

4. Selected answers: Here is a pdf file of short

• solutions for many of the odd-numbered exercises at the ends of the chapters:

5. Additional exercises: Here is a pdf file containing

• Extra exercises

6. Corrections: Here is a pdf file showing

• corrections of typos in early printings of the second edition.

7. Finally, for those of you with interest in the Bayesian approach to inference -- I had intended to include a chapter in the second edition on Bayesian analyses for categorical data analysis (to beef up the short section in Chapter 15), but the book just became too long. However, David Hitchcock (Statistics Dept., Univ. of South Carolina) and I have written a survey paper about such methods:

• Bayesian inference for categorical data analysis: A survey

Categorical Data Analysis with GraphicsMichael Friendly SCS Short Course

---

This document provides several versions of my short course notes for Categorical Data Analysis with Graphics, offered through the Statistical Consulting Service at York University.

• Lecture slides (4up) --- PDF version
  • Part 1
  • Part 2
  • Part 3
• Lecture notes --- PDF version
• Lecture notes --- HTML version The HTML version contains an earlier version of the the text, tables, and character-based graphs of the printed version, and many, but not all, of the high-resolution graphs.

The main source for these materials is my book, Visualizing Categorical Data

If you want to learn more about categorical data analysis, there are several books and other resources I recommend:

• Agresti, A. (1990). Categorical Data Analysis. NY: Wiley.
• Christensen, R. (1990). :Log-Linear Models. Springer-Verlag.
• Everitt, B. S. (1992). The Analysis of Contingency Tables, London: Chapman & Hall (Monograph 45).
• Stokes, M.E., Davis, C.S., and Koch, G.S. (1995). Categorical Data Analysis Using the SAS(R) System. Cary, NC: SAS Institute.
• Robert Hanneman's Generalized Linear Models: An Introductioon

Let us go to find them out!

• Categorical Data Analysis (Wiley Series in Probability and Statistics) by Alan Agresti
• Categorical Data Analysis Using the SAS System by Maura E. Stokes
• Applied Logistic Regression (Wiley Series in Probability and Statistics - Applied Probability and Statistics Section) by David W. Hosmer
• The Little SAS Book: A Primer, Third Edition by Lora D. Delwiche
• Applied Statistics and the SAS Programming Language by Ronald P. Cody
• Introduction to Mathematical Statistics (6th Edition) by Robert V. Hogg
• An Introduction to Categorical Data Analysis by Alan Agresti

Categorical Data Analysis, Second Edition Alan Agresti ISBN: 0-471-36093-7 Hardcover 734 pages July 2002

CDN $136.99

Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Categorical Data Analysis was among those chosen.

A valuable new edition of a standard reference. "A 'must-have' book for anyone expecting to do research and/or applications in categorical data analysis." -Statistics in Medicine on Categorical Data Analysis, First Edition

The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. Responding to new developments in the field as well as to the needs of a new generation of professionals and students, this new edition of the classic Categorical Data Analysis offers a comprehensive introduction to the most important methods for categorical data analysis.

Designed for statisticians and biostatisticians as well as scientists and graduate students practicing statistics, Categorical Data Analysis, Second Edition summarizes the latest methods for univariate and correlated multivariate categorical responses. Readers will find a unified generalized linear models approach that connects logistic regression and Poisson and negative binomial regression for discrete data with normal regression for continuous data. Adding to the value in the new edition is coverage of:

• Three new chapters on methods for repeated measurement and other forms of clustered categorical data, including marginal models and associated generalized estimating equations (GEE) methods, and mixed models with random effects
• Stronger emphasis on logistic regression modeling of binary and multicategory data
• An appendix showing the use of SAS for conducting nearly all analyses in the book
• Prescriptions for how ordinal variables should be treated differently than nominal variables
• Discussion of exact small-sample procedures
• More than 100 analyses of real data sets to illustrate application of the methods, and more than 600 exercises

Preface.

1. Introduction: Distributions and Inference for Categorical Data.

1.1 Categorical Response Data.

1.2 Distributions for Categorical Data.

1.3 Statistical Inference for Categorical Data.

1.4 Statistical Inference for Binomial Parameters.

1.5 Statistical Inference for Multinomial Parameters.

Notes.

Problems.

2. Describing Contingency Tables.

2.1 Probability Structure for Contingency Tables.

2.2 Comparing Two Proportions.

2.3 Partial Association in Stratified 2 x 2 Tables.

2.4 Extensions for I x J Tables.

Notes.

Problems.

3. Inference for Contingency Tables.

3.1 Confidence Intervals for Association Parameters.

3.2 Testing Independence in Two-Way Contingency Tables.

3.3 Following-Up Chi-Squared Tests.

3.4 Two-Way Tables with Ordered Classifications.

3.5 Small-Sample Tests of Independence.

3.6 Small-Sample Confidence Intervals for 2 x 2 Tables*.

3.7 Extensions for Multiway Tables and Nontabulated Responses.

Notes.

Problems.

4. Introduction to Generalized Linear Models.

4.1 Generalized Linear Model.

4.2 Generalized Linear Models for Binary Data.

4.3 Generalized Linear Models for Counts.

4.4 Moments and Likelihood for Generalized Linear Models*.

4.5 Inference for Generalized Linear Models.

4.6 Fitting Generalized Linear Models.

4.7 Quasi-likelihood and Generalized Linear Models*.

4.8 Generalized Additive Models*.

Notes.

Problems.

5. Logistic Regression.

5.1 Interpreting Parameters in Logistic Regression.

5.2 Inference for Logistic Regression.

5.3 Logit Models with Categorical Predictors.

5.4 Multiple Logistic Regression.

5.5 Fitting Logistic Regression Models.

Notes.

Problems.

6. Building and Applying Logistic Regression Models.

6.1 Strategies in Model Selection.

6.2 Logistic Regression Diagnostics.

6.3 Inference About Conditional Associations in 2 x 2 x K Tables.

6.4 Using Models to Improve Inferential Power.

6.5 Sample Size and Power Considerations*.

6.6 Probit and Complementary Log-Log Models*.

6.7 Conditional Logistic Regression and Exact

Distributions*.

Notes.

Problems.

7. Logit Models for Multinomial Responses.

7.1 Nominal Responses: Baseline-Category Logit Models.

7.2 Ordinal Responses: Cumulative Logit Models.

7.3 Ordinal Responses: Cumulative Link Models.

7.4 Alternative Models for Ordinal Responses*.

7.5 Testing Conditional Independence in I x J x K Tables*.

7.6 Discrete-Choice Multinomial Logit Models*.

Notes.

Problems.

8. Loglinear Models for Contingency Tables.

8.1 Loglinear Models for Two-Way Tables.

8.2 Loglinear Models for Independence and Interaction in Three-Way Tables.

8.3 Inference for Loglinear Models.

8.4 Loglinear Models for Higher Dimensions.

8.5 The Loglinear_Logit Model Connection.

8.6 Loglinear Model Fitting: Likelihood Equations and Asymptotic Distributions*.

8.7 Loglinear Model Fitting: Iterative Methods and their Application*.

Notes.

Problems.

9. Building and Extending Loglinear/Logit Models.

9.1 Association Graphs and Collapsibility.

9.2 Model Selection and Comparison.

9.3 Diagnostics for Checking Models.

9.4 Modeling Ordinal Associations.

9.5 Association Models*.

9.6 Association Models, Correlation Models, and Correspondence Analysis*.

9.7 Poisson Regression for Rates.

9.8 Empty Cells and Sparseness in Modeling Contingency Tables.

Notes.

Problems.

10. Models for Matched Pairs.

10.1 Comparing Dependent Proportions.

10.2 Conditional Logistic Regression for Binary Matched Pairs.

10.3 Marginal Models for Square Contingency Tables.

10.4 Symmetry, Quasi-symmetry, and Quasiindependence.

10.5 Measuring Agreement Between Observers.

10.6 Bradley-Terry Model for Paired Preferences.

10.7 Marginal Models and Quasi-symmetry Models for Matched Sets*.

Notes.

Problems.

11. Analyzing Repeated Categorical Response Data.

11.1 Comparing Marginal Distributions: Multiple Responses.

11.2 Marginal Modeling: Maximum Likelihood Approach.

11.3 Marginal Modeling: Generalized Estimating Equations Approach.

11.4 Quasi-likelihood and Its GEE Multivariate Extension: Details*.

11.5 Markov Chains: Transitional Modeling.

Notes.

Problems.

12. Random Effects: Generalized Linear Mixed Models for Categorical Responses.

12.1 Random Effects Modeling of Clustered Categorical Data.

12.2 Binary Responses: Logistic-Normal Model.

12.3 Examples of Random Effects Models for Binary Data.

12.4 Random Effects Models for Multinomial Data.

12.5 Multivariate Random Effects Models for Binary Data.

12.6 GLMM Fitting, Inference, and Prediction.

Notes.

Problems.

13. Other Mixture Models for Categorical Data*.

13.1 Latent Class Models.

13.2 Nonparametric Random Effects Models.

13.3 Beta-Binomial Models.

13.4 Negative Binomial Regression.

13.5 Poisson Regression with Random Effects.

Notes.

Problems.

14. Asymptotic Theory for Parametric Models.

14.1 Delta Method.

14.2 Asymptotic Distributions of Estimators of Model Parameters and Cell Probabilities.

14.3 Asymptotic Distributions of Residuals and Goodnessof-Fit Statistics.

14.4 Asymptotic Distributions for Logit/Loglinear Models.

Notes.

Problems.

15. Alternative Estimation Theory for Parametric Models.

15.1 Weighted Least Squares for Categorical Data.

15.2 Bayesian Inference for Categorical Data.

15.3 Other Methods of Estimation.

Notes.

Problems.

16. Historical Tour of Categorical Data Analysis*.

16.1 Pearson-Yule Association Controversy.

16.2 R. A. Fisher's Contributions.

16.3 Logistic Regression.

16.4 Multiway Contingency Tables and Loglinear Models.

16.5 Recent and Future? Developments.

Appendix A. Using Computer Software to Analyze Categorical Data.

A.1 Software for Categorical Data Analysis.

A.2 Examples of SAS Code by Chapter.

Appendix B. Chi-Squared Distribution Values.

References.

Examples Index.

Author Index.

Subject Index.

*Sections marked with an asterisk are less important for an overview.

9492.zip (4.78 MB, 需要: 10 个论坛币) 本附件包括：

• 00 frontmatter.pdf
• 01 introduction - distributions and inference for categorical data.pdf
• 02 describing contingency tables.pdf
• 03 inference for contingency tables.pdf
• 04 introduction to generalized linear models.pdf
• 05 logistic regression.pdf
• 06 building and applying logistic regression models.pdf
• 07 logit models for multinomial responses.pdf
• 08 loglinear models for contingency tables.pdf
• 09 building and extending loglinear_logit models.pdf
• 10 models for matched pairs.pdf
• 11 analyzing repeated categorical response data.pdf
• 12 random effects.pdf
• 13 other mixture models for categorical data.pdf
• 14 asymptotic theory for parametric models.pdf
• 15 alternative estimation theory for parametric models.pdf
• 16 historical tour of categorical data analysis.pdf
• 17 appendix a - using computer software.pdf
• 18 appendix b - chi-squared distribution values.pdf
• 19 references.pdf
• 20 examples index.pdf
• 21 author index.pdf
• 22 subject index.pdf
• 23 wiley series in probability and statistics.pdf

2005-3-2 08:13:00 上传

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It is a very good book. Thanks.

thanks

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Recent Advances in Categorical Data Analysis