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 ...

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 ...

The researchers used multivariable conditional logistic regression analyses to measure the risk of 11 individual outcomes as the composite outcome: fracture, osteoporosis, type 2 diabetes ...

Conditional logistic regression was used to assess the associations, with adjustments for various covariates and sensitivity analyses excluding participants with missing genetic data.