Bootstrapping multiparameter models, with applications to clustered binary data

Abstract

It is shown how a one-step semiparametric bootstrap procedure can be applied to multiparameter models in different situations: for testing hypotheses, for the construction of simultaneous confidence intervals based on local polynomial smoothers and for improved estimation and bias correction. The method is illustrated on models for clustering binary data