Statistical inference for binomial data addresses the analysis of outcomes that can take one of two values, typically termed “success” or “failure”. Central to this domain is the estimation of the ...

Model averaging addresses the challenge of model uncertainty by combining estimates from multiple candidate models rather than relying on a single selected specification. By assigning weights to each ...

In this module, we will introduce the basic conceptual framework for experimental design and define the models that will allow us to answer meaningful questions about the differences between group ...