Exact Statistical Inference for Categorical Data
By Guogen Shan
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About this ebook
Exact Statistical Inference for Categorical Data discusses the way asymptotic approaches have been often used in practice to make statistical inference. This book introduces both conditional and unconditional exact approaches for the data in 2 by 2, or 2 by k contingency tables, and is an ideal reference for users who are interested in having the convenience of applying asymptotic approaches, with less computational time. In addition to the existing conditional exact inference, some efficient, unconditional exact approaches could be used in data analysis to improve the performance of the testing procedure.
- Demonstrates how exact inference can be used to analyze data in 2 by 2 tables
- Discusses the analysis of data in 2 by k tables using exact inference
- Explains how exact inference can be used in genetics
Guogen Shan
Guogen Shan is an Assistant Professor at the School of Community Health Sciences, University of Nevada Las Vegas. His research interests include the development of adaptive clinical trials, exact testing procedures, and efficient parametric and non-parametric statistical inferences.
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Exact Statistical Inference for Categorical Data - Guogen Shan
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Preface
With the development of computational techniques (e.g., super-computers, parallel computing) and statistical software packages (e.g., SAS, R, Stata, StatXact, SPSS, Matlab, PASS), exact statistical inference for categorical data analysis is increasingly available for use in practice. In the cases that traditional asymptotic approaches do not have satisfactory performance with regards to type I error control and accurate sample size determination, exact approaches should be utilized. This book provides an overview of exact approaches, including Fisher’s exact approach, which is also known as the exact conditional approach, and several efficient exact unconditional approaches. Real examples are provided to illustrate the application of these exact approaches, and these approaches are also comprehensively compared in many important statistical