Correction of the P-value after multiple coding of an explanatory variable in logistic regression.
We propose a method and a program to determine a significance level for a series of codings of an explanatory variable in logistic regression. Dichotomous and Box-Cox transformations are considered. Three methods of correcting the significance level are studied: the Bonferroni method; Efron's method, which uses the correlation between successive tests, and the exact calculation by numerical integration using all correlations. A simulation study has led to a strategy for the choice and number of the different codings of the variable. This method is illustrated using the data of a study of the relation between cholesterol and dementia.
Liquet
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INSERM U330, Université Victor Segalen Bordeaux 2, 146 rue Léo-Saignat, 33076 Bordeaux Cedex, France. liquet@dim.u-bordeaux2.fr
Commenges
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D
D000368:Aged; D008076:Cholesterol, HDL / Q000009:adverse effects; D015331:Cohort Studies; D003198:Computer Simulation; D003704:Dementia / Q000453:epidemiology / Q000209:etiology; D004812:Epidemiologic Methods; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male
D008076:Cholesterol, HDL