bootmlm: bootmlm: A package for bootstrap resampling with multilevel...

In marklhc/bootmlm: Bootstrap Resampling for Multilevel Models

bootmlm: A package for bootstrap resampling with multilevel data.

Description

Currently, the bootMer() function in the lme4 package only implements the parametric bootstrap and a limited version of semiparametric (or residual) bootstrap. The bootmlm package provides the function bootstrap_mer, which performs various parametric, residual, and case bootstrap resampling for fitted model objects with the lme4 package.

Limitations

• Currently only support multilevel models (a.k.a. linear mixed-effects models) fitted by lmer() with the lme4 package. Support for categorical outcome (i.e., generalized linear mixed-effects models fitted by glmer()) and for models fitted with the nlme package will be added in the future.

• Random effect block bootstrap (type = 'reb') and case bootstrap (type = 'case') only support two-level models.

• Bias-corrected and accelerated bootstrap (using empinf_mer()) only supports two-level models.

marklhc/bootmlm documentation built on May 24, 2023, 9:59 a.m.