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.