Post-selection inference for linear mixed model parameters using the conditional Akaike information criterion
Gerda Claeskens,
Katarzyna Reluga,
Stefan Sperlich
Abstract:We investigate the issue of post-selection inference for a fixed and a mixed parameter in a linear mixed model using a conditional Akaike information criterion as a model selection procedure. Within the framework of linear mixed models we develop complete theory to construct confidence intervals for regression and mixed parameters under three frameworks: nested and general model sets as well as misspecified models. Our theoretical analysis is accompanied by a simulation experiment and a post-selection examinat… Show more
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