Delete random effect terms with zero variance
deleteZeroComponents(m) ## S3 method for class 'lme' deleteZeroComponents(m) ## S3 method for class 'merMod' deleteZeroComponents(m)
For merMod class models:
Uses the cnms slot of m and the relative covariance factors to
rewrite the random effects part of the formula, reduced by those parameters
that have an optimum on the boundary. This is necessary to obtain the true
conditional corrected Akaike information. For the theoretical justification
see Greven and Kneib (2010). The reduced model formula is then updated. The
function deleteZeroComponents is then called iteratively to check if in the
updated model there are relative covariance factors parameters on the
boundary.
For lme class models:
...
NULL
NULL
For models called via gamm4 or gamm
no automated update is available.
Instead a warning with terms to omit from the model is returned.
Benjamin Saefken \& David Ruegamer \& Philipp Baumann
Greven, S. and Kneib T. (2010) On the behaviour of marginal and conditional AIC in linear mixed models. Biometrika 97(4), 773-789.
## Currently no data with variance equal to zero... b <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy) deleteZeroComponents(b)
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