Add to ORKGIn the setting of mixed models, some researchers may construct a semiparametric bootstrap by sampling from the best linear unbiased predictor residuals. This paper demonstrates both mathematically and by simulation that such a bootstrap will consistently underestimate the variation in the data in finite samples.Bootstrap Correlated data Mixed models Nested models
International audienceBootstrap methods are used in many disciplines to estimate the uncertainty of ...
The bootstrap has become a popular method for exploring model (structure) uncertainty. Our experime...
The paper investigates how the particular choice of residuals used in a bootstrap-based testing proc...
In the setting of mixed models, some researchers may construct a semiparametric bootstrap by samplin...
International audienceA version of the nonparametric bootstrap, which resamples the entire subjects ...
In the framework of Mixed Models, it is often of interest to provide an es- timate of the uncertaint...
A multiplier bootstrap procedure for construction of likelihood-based confidence sets is considered ...
The bootstrap is a computationally intensive data analysis technique. It is particularly useful for ...
A multiplier bootstrap procedure for construction of likelihood-based confidence sets is considered ...
International audienceThe bootstrap is a technique for performing statistical inference. The underly...
The linear mixed model (LMM) is a popular statistical model for the analysis of longitudinal data. H...
and FCAR for their financial support. We would also like to thank a referee and an Associate Editor ...
International audiencePurpose Non-linear mixed effect models are widely used and increasingly integr...
The bootstrap is a computer-intensive resampling method for estimating the uncertainty of complex st...
A bootstrap method for generating confidence intervals in linear models is suggested. The method is ...
International audienceBootstrap methods are used in many disciplines to estimate the uncertainty of ...
The bootstrap has become a popular method for exploring model (structure) uncertainty. Our experime...
The paper investigates how the particular choice of residuals used in a bootstrap-based testing proc...
In the setting of mixed models, some researchers may construct a semiparametric bootstrap by samplin...
International audienceA version of the nonparametric bootstrap, which resamples the entire subjects ...
In the framework of Mixed Models, it is often of interest to provide an es- timate of the uncertaint...
A multiplier bootstrap procedure for construction of likelihood-based confidence sets is considered ...
The bootstrap is a computationally intensive data analysis technique. It is particularly useful for ...
A multiplier bootstrap procedure for construction of likelihood-based confidence sets is considered ...
International audienceThe bootstrap is a technique for performing statistical inference. The underly...
The linear mixed model (LMM) is a popular statistical model for the analysis of longitudinal data. H...
and FCAR for their financial support. We would also like to thank a referee and an Associate Editor ...
International audiencePurpose Non-linear mixed effect models are widely used and increasingly integr...
The bootstrap is a computer-intensive resampling method for estimating the uncertainty of complex st...
A bootstrap method for generating confidence intervals in linear models is suggested. The method is ...
International audienceBootstrap methods are used in many disciplines to estimate the uncertainty of ...
The bootstrap has become a popular method for exploring model (structure) uncertainty. Our experime...
The paper investigates how the particular choice of residuals used in a bootstrap-based testing proc...