Serial dependence of observations leading to contingency tables, and corrections to chi-squared statistics

Biometrika ◽  
1983 ◽  
Vol 70 (1) ◽  
pp. 139-144 ◽  
Author(s):  
SIMON TAVARÉ ◽  
PATRICIA M. E. ALTHAM
Keyword(s):  
Contingency Tables ◽  
Serial Dependence ◽  
Chi Squared

Serial Dependence of Observations Leading to Contingency Tables, and Corrections to Chi-Squared Statistics

Biometrika ◽  
1983 ◽  
Vol 70 (1) ◽  
pp. 139 ◽  
Author(s):  
Simon Tavare ◽  
Patricia M. E. Altham
Keyword(s):  
Contingency Tables ◽  
Serial Dependence ◽  
Chi Squared

Multiway Contingency Tables: Monte Carlo Resampling Probability Values for the Chi-Squared and Likelihood-Ratio Tests

2010 ◽  
Vol 107 (2) ◽  
pp. 501-510 ◽  
Author(s):  
Michael A. Long ◽  
Kenneth J. Berry ◽  
Paul W. Mielke
Keyword(s):  
Monte Carlo ◽  
Likelihood Ratio ◽  
Contingency Table ◽  
Contingency Tables ◽  
Likelihood Ratio Tests ◽  
Ratio Test ◽  
Test Statistics ◽  
Test Statistic ◽  
Resampling Methods ◽  
Chi Squared

Monte Carlo resampling methods to obtain probability values for chi-squared and likelihood-ratio test statistics for multiway contingency tables are presented. A resampling algorithm provides random arrangements of cell frequencies in a multiway contingency table, given fixed marginal frequency totals. Probability values are obtained from the proportion of resampled test statistic values equal to or greater than the observed test statistic value.

Power Anaysis of Independence Testing for Two-Way Contingency Tables Bigger than 2×2

2016 ◽  
Vol 63 (2) ◽  
pp. 191-210 ◽  
Author(s):  
Piotr Sulewski
Keyword(s):  
Monte Carlo ◽  
Statistical Analysis ◽  
Null Hypothesis ◽  
Contingency Tables ◽  
Critical Values ◽  
Simulation Methods ◽  
The Family ◽  
Chi Squared ◽  
Independence Testing

In the statistical literature there are many test measures to study the independence features in the two-way contingency tables. For statistical analysis, the family of six so-called “chi-squared statistic” was selected – including Pearson’s χ2 statistics – and the proposal of the author in the form of modu-lar statistics. In order to free themselves from the limitations of the applicability of the “chi-squared statisti c”, critical values for all analyzed statistics were determined by simulation methods of Monte Carlo. In order to compare the tests, the measure of untruthfulness of H0was proposed and calculated the power of the tests which is the ability of two-way contingency tables to reject null hypothesis which says that between features X and Y there is no relation.

Resampling Programs for Multiway Contingency Tables with Fixed Marginal Frequency Totals

2007 ◽  
Vol 101 (1) ◽  
pp. 18-24 ◽  
Author(s):  
Paul W. Mielke ◽  
Kenneth J. Berry ◽  
Janis E. Johnston
Keyword(s):  
Likelihood Ratio ◽  
Contingency Tables ◽  
Likelihood Ratio Tests ◽  
Marginal Frequency ◽  
Chi Squared

A resampling algorithm is presented for analyzing multiway contingency tables with fixed marginal frequency totals. Applications are illustrated with extensions of Fisher's exact, Pearson's chi-squared, and likelihood-ratio tests to three-way contingency tables.

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