Abstract
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
| Original language | English |
|---|---|
| Publication date | 2018 |
| Number of pages | 1 |
| Publication status | Published - 2018 |
| Event | 27th Nordic Conference in Mathematical Statistics - Dorpat Convention Centre, Tartu, Estonia Duration: 26 Jun 2018 → 29 Aug 2018 Conference number: 27 http://nordstat2018.ut.ee/ |
Conference
| Conference | 27th Nordic Conference in Mathematical Statistics |
|---|---|
| Number | 27 |
| Location | Dorpat Convention Centre |
| Country | Estonia |
| City | Tartu |
| Period | 26/06/2018 → 29/08/2018 |
| Internet address |
Fingerprint
Keywords
- Kenward-Roger approximation
- parametric bootstrap
- Satterthwaite approximation
Cite this
}
Inference in mixed models in R - beyond the usual asymptotic likelihood ratio test. / Halekoh, Ulrich; Højsgaard, Søren.
2018. 31 Abstract from 27th Nordic Conference in Mathematical Statistics , Tartu, Estonia.Research output: Contribution to conference without publisher/journal › Conference abstract for conference › Research › peer-review
TY - ABST
T1 - Inference in mixed models in R - beyond the usual asymptotic likelihood ratio test
AU - Halekoh, Ulrich
AU - Højsgaard, Søren
PY - 2018
Y1 - 2018
N2 - 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 referencedistribution 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 BootstrapMethods for Tests in Linear Mixed Models The R Package pbkrtest. Journal of StatisticalSoftware 59, 1–32.36
AB - 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 referencedistribution 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 BootstrapMethods for Tests in Linear Mixed Models The R Package pbkrtest. Journal of StatisticalSoftware 59, 1–32.36
KW - Kenward-Roger approximation
KW - parametric bootstrap
KW - Satterthwaite approximation
KW - Kenward-Roger approximation
KW - parametric bootstrap
KW - Satterthwaite approximation
M3 - Conference abstract for conference
SP - 31
ER -