Statistical Analysis of Contingency Tables
Auteurs : Fagerland Morten, Lydersen Stian, Laake Petter
Statistical Analysis of Contingency Tables is an invaluable tool for statistical inference in contingency tables. It covers effect size estimation, confidence intervals, and hypothesis tests for the binomial and the multinomial distributions, unpaired and paired 2x2 tables, rxc tables, ordered rx2 and 2xc tables, paired cxc tables, and stratified tables. For each type of table, key concepts are introduced, and a wide range of intervals and tests, including recent and unpublished methods and developments, are presented and evaluated. Topics such as diagnostic accuracy, inter-rater reliability, and missing data are also covered. The presentation is concise and easily accessible for readers with diverse professional backgrounds, with the mathematical details kept to a minimum.
For more information, including a sample chapter and software, please visit the authors' website.
Introduction
The 1 × 2 Table and the Binomial Distribution
The 1 × c Table and the Multinomial Distribution
The 2 × 2 Table
The Ordered r × 2 Table
The Ordered 2 × c Table
The r × c Table
The Paired 2 × 2 Table
The Paired c × c Table
Stratified 2 × 2 Tables and Meta-Analysis
Other Stratified Tables
Sample Size Calculations
Miscellaneous Topics
Morten W. Fagerland, Ph.D. is Head of the Section for Biostatistics, Epidemiology, and Health Economics at Oslo Centre for Biostatistics and Epidemiology, Oslo University Hospital, Norway.
Stian Lydersen, Ph.D. is a Professor of Medical Statistics at Regional Centre for Child and Youth Mental Health and Child Welfare, Norwegian University of Science and Technology, Trondheim, Norway.
Petter Laake, Ph.D. is a Professor of Medical Statistics at the Department of Biostatistics at Oslo Centre for Biostatistics and Epidemiology, University of Oslo, Norway.
Date de parution : 02-2020
15.6x23.4 cm
Date de parution : 07-2017
15.6x23.4 cm
Thèmes de Statistical Analysis of Contingency Tables :
Mots-clés :
Actual Significance Level; Wald Interval; hypothesis; Wilson Score Interval; confidence; Exact Unconditional Test; interval; Marginal Homogeneity; actual; Pearson Chi Squared Test; significance; Coverage Probabilities; level; McNemar Bowker Test; wald; Proportional Odds Model; likelihood; Cochran Mantel Haenszel Test; ratio; Likelihood Ratio Interval; Morten W; Fagerland; Pearson Chi Squared; Stian Lydersen; Exact Conditional Test; Petter Laake; Exact Binomial Test; Nominal Significance Level; Score Interval; Likelihood Ratio Test; Average Coverage Probability; Sample Size Calculations; Ump Unbiased Test; Agresti Coull Interval; Cochran Armitage Test; Multinomial Parameters; Simultaneous Confidence Intervals; General Norwegian Population