Testing independence in two-way contingency tables with data subject to misclassification

Psychometrika ◽  
1967 ◽  
Vol 32 (1) ◽  
pp. 67-76 ◽  
Author(s):  
Kwanchai Assakul ◽  
Charles H. Proctor
Keyword(s):  
Contingency Tables ◽  
Testing Independence ◽  
Data Subject

Choice of Column Scores for Testing Independence in Ordered 2 x K Contingency Tables

Biometrics ◽  
1987 ◽  
Vol 43 (2) ◽  
pp. 471 ◽  
Author(s):  
Barry I. Graubard ◽  
Edward L. Korn
Keyword(s):  
Contingency Tables ◽  
Testing Independence

scholarly journals A Flexible Method for Testing Independence in Two-Way Contingency Tables

2010 ◽  
Vol 9 (2) ◽  
pp. 443-451 ◽  
Author(s):  
Peyman Jafari ◽  
Noori Akhtar-Danesh ◽  
Zahra Bagheri
Keyword(s):  
Contingency Tables ◽  
Testing Independence

scholarly journals The LMS for testing independence in two-way contingency tables

2019 ◽  
Vol 56 (1) ◽  
pp. 17-43 ◽  
Author(s):  
Piotr Sulewski
Keyword(s):  
Monte Carlo ◽  
Statistical Analysis ◽  
Monte Carlo Method ◽  
Contingency Tables ◽  
Critical Values ◽  
Testing Independence ◽  
The Monte Carlo Method ◽  
Qualitative Variables ◽  
Chi Squared

SummaryIn the statistical literature there are proposed many test measures to determine the independence of two qualitative variables in contingency tables, in particular in two-way contingency tables larger than 2×2. For statistical analysis, three of the so-called “chi-squared tests”—the T3 test, BP test and |χ| test—were selected. These tests were compared with a logarithmic minimum test, which is the author’s proposal. Critical values for the tests were determined with the Monte Carlo method. To compare the tests, an appropriate measure of untruthfulness of H0 was used and the power of the tests was calculated.

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