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Categorical Data Analysis

TLDR
Modeling and inferential procedures (estimation and precision assessment) are discussed for a single proportion, thereafter in the context of cross-classified data, i.e., contingency tables, is discussed, with particular emphasis on testing the null hypothesis of no association (independence) between the row and column classification.
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An introduction to categorical data analysis

Two--Way Contingency Tables. Three--Way Contingency Tables. Generalized Linear Models. Logistic Regression. Loglinear Models for Contingency Tables. Building and Applying Logit and Loglinear Models.…
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Approximate is Better than “Exact” for Interval Estimation of Binomial Proportions

Abstract For interval estimation of a proportion, coverage probabilities tend to be too large for “exact” confidence intervals based on inverting the binomial test and too small for the interval…
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Statistical Methods for the Social Sciences

1.Introduction 1.1 Introduction to statistical methodology 1.2 Descriptive statistics and inferential statistics 1.3 The role of computers in statistics 1.4 Chapter summary 2. Sampling and…
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A Survey of Exact Inference for Contingency Tables

The past decade has seen substantial research on exact infer- ence for contingency tables, both in terms of developing new analyses and developing efficient algorithms for computations. Coupled with…
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Simple and Effective Confidence Intervals for Proportions and Differences of Proportions Result from Adding Two Successes and Two Failures

Abstract The standard confidence intervals for proportions and their differences used in introductory statistics courses have poor performance, the actual coverage probability often being much lower…
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Foundations of Linear and Generalized Linear Models

TLDR
This book presents a broad, in-depth overview of the most commonly used linear statistical models by discussing the theory underlying the models, R software applications, and examples with crafted models to elucidate key ideas and promote practical modelbuilding.

Analysis of Ordinal Categorical Data: Agresti/Analysis

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Simple capture-recapture models permitting unequal catchability and variable sampling effort.

We consider two capture-recapture models that imply that the logit of the probability of capture is an additive function of an animal catchability parameter and a parameter reflecting the sampling…
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Random effect models for repeated measures of zero-inflated count data

For count responses, the situation of excess zeros (relative to what standard models allow) often occurs in biomedical and sociological applications. Modeling repeated measures of zero-inflated count…
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