logLik.lmm

Extract or compute the log-likelihood of a linear mixed model.

methods

Companion R package for the course "Statistical analysis of correlated and repeated measurements for health science researchers"
taught by the section of Biostatistics of the University of Copenhagen.
It implements linear mixed models where the model for the variance-covariance of the residuals is specified via patterns (compound symmetry, toeplitz, unstructured, ...).
Statistical inference for mean, variance, and correlation parameters is performed based on the observed information and a Satterthwaite approximation of the degrees of freedom.
Normalized residuals are provided to assess model misspecification.
Statistical inference can be performed for arbitrary linear or non-linear combination(s) of model coefficients.
Predictions can be computed conditional to covariates only or also to outcome values.

Brice Ozenne

LMMstar

Repeated Measurement Models for Discrete Times

Julie Forman

logLik.lmm function

<dl><dt>object</dt>
<dd>a <code>lmm</code> object.</dd>
<dt>newdata</dt>
<dd>[data.frame] dataset relative to which the log-likelihood should be computed. Only relevant if differs from the dataset used to fit the model.</dd>
<dt>p</dt>
<dd>[numeric vector] value of the model coefficients at which to evaluate the log-likelihood. Only relevant if differs from the fitted values.</dd>
<dt>indiv</dt>
<dd>[logical] Should the contribution of each cluster to the log-likelihood be output? Otherwise output the sum of all clusters of the derivatives.</dd>
<dt>...</dt>
<dd>Not used. For compatibility with the generic method.</dd></dl>

Arguments

Extract The Log-Likelihood From a Linear Mixed Model — logLik.lmm

<dl>

<dt>object</dt>
<dd>a <code>lmm</code> object.</dd>


<dt>newdata</dt>
<dd>[data.frame] dataset relative to which the log-likelihood should be computed. Only relevant if differs from the dataset used to fit the model.</dd>


<dt>p</dt>
<dd>[numeric vector] value of the model coefficients at which to evaluate the log-likelihood. Only relevant if differs from the fitted values.</dd>


<dt>indiv</dt>
<dd>[logical] Should the contribution of each cluster to the log-likelihood be output? Otherwise output the sum of all clusters of the derivatives.</dd>


<dt>...</dt>
<dd>Not used. For compatibility with the generic method.</dd>

</dl>

logLik.lmm: Extract The Log-Likelihood From a Linear Mixed Model

Description

Usage

Value

Arguments

Details