Calculates the BIC as -2 * log-likelihood + log(n) * npar for a longitudinal model where npar is the number of parameters in the fitted-model and n is the number of subjects
a fitted longitudinal model object
some methods for this generic function may require additional arguments
When applying the BIC in a longitudinal context, there is some debate as to whether the sample size should be taken to mean the number of subjects or the total number of observations across all subjects (see Section 7.3 of Hedeker and Gibbons, 2006).
Assuming the default
BIC function accounts for the latter case, this generic function can be
implemented for longitudinal models where the number of subjects can be extracted in order to
calculate the BIC under the alternative definition.
A numeric value with the BIC of the longitudinal model, with the penalty taken as a function of the number of subjects as described.
Maurice Berk [email protected]
Berk, M. (2012). Smoothing-splines Mixed-effects Models in R. Preprint
Hedeker, D. & Gibbons, D. R. (2006). Longitudinal Data Analysis. Wiley
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