The Canadian Journal of Statistics / La Revue Canadienne de Statistique We consider optimal designs for a class of symmetric models for binary data which includes the common probit and logit models.

Empirical researchers sometimes misinterpret how additional regressors, heterogeneity corrections, and multilevel factors impact the interpretation of the estimated parameters in binary outcome models ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...