summary.mlmm

Estimates, p-values, and confidence intevals for multiple linear mixed models.

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

summary.mlmm function

<dl><dt>object</dt>
<dd>an <code>mlmm</code> object, output of <code>mlmm</code>.</dd>
<dt>digits</dt>
<dd>[integer,&gt;0] number of digits used to display numeric values.</dd>
<dt>method</dt>
<dd>[character] type of adjustment for multiple comparisons: one of <code>"none"</code>, <code>"bonferroni"</code>, <code>"single-step"</code>, <code>"single-step2"</code>.</dd>
<dt>print</dt>
<dd>[logical] should the output be printed in the console.
Can be a vector of length 2 where the first element refer to the global tests and the second to the individual tests.</dd>
<dt>hide.data</dt>
<dd>[logical] should information about the dataset not be printed.</dd>
<dt>hide.fit</dt>
<dd>[logical] should information about the model fit not be printed.</dd>
<dt>...</dt>
<dd>other arguments are passed to <code>summary.Wald_lmm</code>.</dd></dl>

Arguments

Summary of Multiple Linear Mixed Models — summary.mlmm

<dl>

<dt>object</dt>
<dd>an <code>mlmm</code> object, output of <code>mlmm</code>.</dd>


<dt>digits</dt>
<dd>[integer,&gt;0] number of digits used to display numeric values.</dd>


<dt>method</dt>
<dd>[character] type of adjustment for multiple comparisons: one of <code>"none"</code>, <code>"bonferroni"</code>, <code>"single-step"</code>, <code>"single-step2"</code>.</dd>


<dt>print</dt>
<dd>[logical] should the output be printed in the console.
Can be a vector of length 2 where the first element refer to the global tests and the second to the individual tests.</dd>


<dt>hide.data</dt>
<dd>[logical] should information about the dataset not be printed.</dd>


<dt>hide.fit</dt>
<dd>[logical] should information about the model fit not be printed.</dd>


<dt>...</dt>
<dd>other arguments are passed to <code>summary.Wald_lmm</code>.</dd>

</dl>

summary.mlmm: Summary of Multiple Linear Mixed Models

Description

Usage

Arguments