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lme4 (version 1.1-35.5)

rePCA: PCA of random-effects covariance matrix

Description

PCA of random-effects variance-covariance estimates

Usage

rePCA(x)

Value

a prcomplist object

Arguments

x

a merMod object

Author

Douglas Bates

Details

Perform a Principal Components Analysis (PCA) of the random-effects variance-covariance estimates from a fitted mixed-effects model. This allows the user to detect and diagnose overfitting problems in the random effects model (see Bates et al. 2015 for details).

References

  • Douglas Bates, Reinhold Kliegl, Shravan Vasishth, and Harald Baayen. Parsimonious Mixed Models. arXiv:1506.04967 [stat], June 2015. arXiv: 1506.04967.

See Also

isSingular

Examples

Run this code
  fm1 <- lmer(Reaction~Days+(Days|Subject), sleepstudy)
  rePCA(fm1)

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