Breslow and Cain (1988) proposed a conditional likelihood approach based on the validation set. We combine the conditional likelihoods of the validation set and the non-validation set. The proposed ...

A class of conditional logistic regression models for clustered binary data is considered. This includes the polychotomous logistic model of Rosner (1984) as a special case. Properties such as the ...

Finland: Children diagnosed with type 1 diabetes mellitus (T1DM) may face an elevated risk of developing acute leukemia, ...

We created two conditional logistic regression models, relating each model-derived density measurement to likelihood of contralateral breast cancer diagnosis, adjusted for age, BMI, family history, ...

Using conditional logistic regression with adjustment for age, race and ethnic group, underlying conditions, and exposures to persons with Covid-19, we estimated vaccine effectiveness for partial ...

In a conditional logistic-regression multivariate analysis, neither ACE inhibitors nor ARBs were associated with the likelihood of SARS-CoV-2 infection.

Multivariate conditional logistic regression modeling failed to find a significant association between exposure and hospital mortality (adjusted OR 1.15, 95% CI 0.65 to 2.04) or other relevant ...

Logistic regression confirmed drug combinations for CVDs [cardiovascular diseases] or hypertension associated with increased BP risk," the authors wrote.