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Analysis of residuals in contingency tables: another nail in the coffin of conditional approaches to significance testing.

Authors :
García Pérez, Miguel Ángel
Núñez Antón, Vicente
Alcalá Quintana, Rocío
García Pérez, Miguel Ángel
Núñez Antón, Vicente
Alcalá Quintana, Rocío
Publication Year :
2023

Abstract

Omnibus tests of significance in contingency tables use statistics of the chi-square type. When the null is rejected, residual analyses are conducted to identify cells in which observed frequencies differ significantly from expected frequencies. Residual analyses are thus conditioned on a significant omnibus test. Conditional approaches have been shown to substantially alter type I error rates in cases involving t tests conditional on the results of a test of equality of variances, or tests of regression coefficients conditional on the results of tests of heteroscedasticity. We show that residual analyses conditional on a significant omnibus test are also affected by this problem, yielding type I error rates that can be up to 6 times larger than nominal rates, depending on the size of the table and the form of the marginal distributions. We explored several unconditional approaches in search for a method that maintains the nominal type I error rate and found out that a bootstrap correction for multiple testing achieved this goal. The validity of this approach is documented for two-way contingency tables in the contexts of tests of independence, tests of homogeneity, and fitting psychometric functions. Computer code in MATLAB and R to conduct these analyses is provided as Supplementary Material.<br />Ministerio de Ciencia e Innovación (MICINN)<br />Ministerio de Economía y Competitividad (MINECO)<br />Ministerio de Ciencia e Innovación and FEDER<br />Universidad del PaísVasco UPV/EHU<br />Departamento de Educación del Gobierno Vasco<br />UPV/EHU Econometrics Research Group<br />Depto. de Psicobiología y Metodología en Ciencias del Comportamiento<br />Fac. de Psicología<br />TRUE<br />pub

Details

Database :
OAIster
Notes :
application/pdf, 1554-3528, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1413944857
Document Type :
Electronic Resource