Several statistical methods have been developed for adjusting the Odds Ratio of the relation between two dichotomous variables X and Y for some confounders Z. With the exception of the Mantel-Haenszel method, commonly used methods, notably binary logistic regression, are not symmetrical in X and Y. The classical Mantel-Haenszel method however only works for confounders with a limited number of discrete strata, which limits its utility, and appears to have no basis in statistical models. Here we revisit the Mantel-Haenszel method and propose an extension to continuous and vector valued Z. The idea is to replace the observed cell entries in strata of the Mantel-Haenszel procedure by subject specific classification probabilities for the four p...
For cases in which a parameter may be estimated from several independent data sets, Mather (1935) pr...
International audienceThe model's coefficients can be interpreted via the odds and odds ratio, which...
The primary objective of this paper is a focused introduction to the logistic regression model and i...
<div><p>Several statistical methods have been developed for adjusting the Odds Ratio of the relation...
Several statistical methods have been developed for adjusting the Odds Ratio of the relation between...
Several statistical methods have been developed for adjusting the Odds Ratio of the relation between...
The Mantel-Haenszel problem involves inferences about a common odds ratio in a set of 2 x 2 tables. ...
This paper examines the tests of homogeneity ofodds ratios in in dependent experiments. Breslow and ...
For a two-way contingency table, odds ratios are commonly used to describe the relationships between...
This paper examines the tests of homogeneity of odds ratios in independent experiments. Breslow and ...
For a two–way contingency table with categorical variables, local odds ratios are commonly used to d...
Stratification allows to control for confounding by creating two or more categories or subgroups in ...
IRT, odds-ratio, sufficient statistic, weak item independence, manifest monotonicity, Rasch model, D...
The logistic regression originally is intended to explain the relationship between the probability o...
In a regression context, the dichotomization of a continuous outcome variable is often motivated by...
For cases in which a parameter may be estimated from several independent data sets, Mather (1935) pr...
International audienceThe model's coefficients can be interpreted via the odds and odds ratio, which...
The primary objective of this paper is a focused introduction to the logistic regression model and i...
<div><p>Several statistical methods have been developed for adjusting the Odds Ratio of the relation...
Several statistical methods have been developed for adjusting the Odds Ratio of the relation between...
Several statistical methods have been developed for adjusting the Odds Ratio of the relation between...
The Mantel-Haenszel problem involves inferences about a common odds ratio in a set of 2 x 2 tables. ...
This paper examines the tests of homogeneity ofodds ratios in in dependent experiments. Breslow and ...
For a two-way contingency table, odds ratios are commonly used to describe the relationships between...
This paper examines the tests of homogeneity of odds ratios in independent experiments. Breslow and ...
For a two–way contingency table with categorical variables, local odds ratios are commonly used to d...
Stratification allows to control for confounding by creating two or more categories or subgroups in ...
IRT, odds-ratio, sufficient statistic, weak item independence, manifest monotonicity, Rasch model, D...
The logistic regression originally is intended to explain the relationship between the probability o...
In a regression context, the dichotomization of a continuous outcome variable is often motivated by...
For cases in which a parameter may be estimated from several independent data sets, Mather (1935) pr...
International audienceThe model's coefficients can be interpreted via the odds and odds ratio, which...
The primary objective of this paper is a focused introduction to the logistic regression model and i...