Inference in mixed models in R - beyond the usual asymptotic likelihood ratio test

Ulrich Halekoh, Søren Højsgaard

Publikation: Konferencebidrag uden forlag/tidsskriftKonferenceabstrakt til konferenceForskningpeer review

Abstrakt

Mixed models in R (www.r-project.org) are currently usually handled with the lme4 package.
Until recently, inference (hypothesis test) in linear mixed models with lme4 was commonly based on the limiting χ2 distribution of the likelihood ratio statistic. The pbkrtest package provides two alternatives: 1) A Kenward-Roger approximation for calculating (or estimating) the numerator degrees of freedom for an ”F-like” test statistic. 2) p-values based on simulating the reference
distribution of the likelihood ratio statistic via parametric bootstrap. A recent addition to the package is a Satterthwaite approximation of the degrees of freedom. We will illustrate the package through various examples, and discuss some directions for further developments.

References
[1] Halekoh, U., Højsgaard, S. (2014). A Kenward-Roger Approximation and Parametric Bootstrap
Methods for Tests in Linear Mixed Models The R Package pbkrtest. Journal of Statistical
Software 59, 1–32.
36
OriginalsprogEngelsk
Publikationsdato2018
Antal sider1
StatusUdgivet - 2018
Begivenhed27th Nordic Conference in Mathematical Statistics - Dorpat Convention Centre, Tartu, Estland
Varighed: 26 jun. 201829 aug. 2018
Konferencens nummer: 27
http://nordstat2018.ut.ee/

Konference

Konference27th Nordic Conference in Mathematical Statistics
Nummer27
LokationDorpat Convention Centre
LandEstland
ByTartu
Periode26/06/201829/08/2018
Internetadresse

Emneord

  • Kenward-Roger approximation
  • parametric bootstrap
  • Satterthwaite approximation

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