Case-Wise and Cluster-Wise Derivatives for Mixed Effects Models

Compute case-wise and cluster-wise derivative for mixed effects models with respect to fixed effects parameter, random effect (co)variances, and residual variance. This material is partially based on work supported by the National Science Foundation under Grant Number 1460719.

merDeriv is a free, open source R package for computing derivatives of mixed models estimated via lme4. Allows users to compute scores (casewise first derivatives of likelihood function) and variance-covariance matrix of all estimated parameters, including random effect (co)variances.

For further information, see:

Wang, T. & Merkle, E. C. (2018). Derivative Computations and Robust Standard Errors for Linear Mixed Effects Models in lme4.. Journal of Statistical Software, 16(9), 1–16.


Reference manual

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0.2-1 by Ting Wang, 3 days ago

Browse source code at

Authors: Ting Wang [aut, cre] , Edgar Merkle [aut] , Yves Rosseel [ctb]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports utils, Matrix, numDeriv

Depends on lme4, stats, methods, nonnest2, sandwich, lavaan

Suggests tinytest, smdata, mirt

Imported by varTestnlme.

Suggested by lmeInfo, tram.

See at CRAN