Exact Statistical Inference for Categorical Data

*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.

Autorentext
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.

Klappentext

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.

Inhalt

Chapter 1: exact inference for data in 2 by 2 tables
1.1. independent case with binary outcome
1.2. dependent case with binary outcome
Chapter 2: exact inference for data from 2 by k tables
2.1. trend test for independent k groups with binary outcome
2.2. test for two ordered multinomials
Chapter 3: exact inference for genetics
3.1. Test for hardy-Weingerg equilibrium