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 ...

Applications of random-parameter logit models can be found in various disciplines. These models have non-concave simulated likelihood functions and the choice of starting values is therefore crucial ...

The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of ...