The PIT-trap-A "model-free" bootstrap procedure for inference about regression models with discrete, multivariate responses.

ABSTRACT: Bootstrap methods are widely used in statistics, and bootstrapping of residuals can be especially useful in the regression context. However, difficulties are encountered extending residual resampling to regression settings where residuals are not identically distributed (thus not amenable to bootstrapping)-common examples including logistic or Poisson regression and generalizations to handle clustered or multivariate data, such as generalised estimating equations. We propose a bootstrap method based on probability integral transform (PIT-) residuals, which we call the PIT-trap, which assumes data come from some marginal distribution F of known parametric form. This method can be understood as a type of "model-free bootstrap", adapted to the problem of discrete and highly multivariate data.

SUBMITTER: Warton DI 

PROVIDER: S-EPMC5524334 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature