Skip to main content

Exact Statistical Inference for Categorical Data

  • 1st Edition - October 30, 2015
  • Latest edition
  • Author: Guogen Shan
  • Language: English

Exact Statistical Inference for Categorical Data discusses the way asymptotic approaches have been often used in practice to make statistical inference. This book introduce… Read more

World Book Day celebration

Where learning shapes lives

Up to 25% off trusted resources that support research, study, and discovery.

Description

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.

Key features

  • 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

Readership

Researchers from pharmaceutical companies, research universities and institutes and students who are interested in categorical data analysis

Table of contents

  • Preface
  • Chapter 1: Exact Statistical Inference for a 2 × 2 Table
    • Abstract
    • Independent Study
    • Comparative Study
    • Double Dichotomy Study
    • 1.1 Exact Testing Procedures
    • 1.2 Comparison of Exact Approaches
  • Chapter 2: Exact Statistical Inference for a 2 × K Table
    • Abstract
    • 2.1 Testing Trend for Binary Data from a 2 × K Table
    • 2.2 Testing for Hardy-Weinberg Equilibrium
  • Chapter 3: Sample Size Determination Using Exact Approaches
    • Abstract
    • 3.1 Exact Sample Size Computation for a Clinical Trial with Historical Controls
  • Conclusions

Product details

  • Edition: 1
  • Latest edition
  • Published: December 15, 2015
  • Language: English

About the author

GS

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.
Affiliations and expertise
University of Nevada, Las Vegas, NV, USA

View book on ScienceDirect

Read Exact Statistical Inference for Categorical Data on ScienceDirect