A simulation-based goodness-of-fit test for random effects in generalized linear mixed models

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Abstrakt

The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is assessed using a conditional simulation of the random effects conditional on the observations. Provided that the specified joint model for random effects and observations is correct, the marginal distribution of the simulated random effects coincides with the assumed random effects distribution. In practice, the specified model depends on some unknown parameter which is replaced by an estimate. We obtain a correction for this by deriving the asymptotic distribution of the empirical distribution function obtained from the conditional sample of the random effects. The approach is illustrated by simulation studies and data examples.
Udgivelsesdato: DEC
OriginalsprogEngelsk
TidsskriftScandinavian Journal of Statistics
Vol/bind33
Udgave nummer4
Sider (fra-til)721-731
Antal sider11
ISSN1467-9469
StatusUdgivet - 2006

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