medsim

datasets

The main function calculates confidence intervals (CI) for Mixed Models, utilizing both classical estimators from the lmer() function in the 'lme4' package and robust estimators from the rlmer() function in the 'robustlmm' package, as well as the varComprob() function in the 'robustvarComp' package. Three methods are available: the classical Wald method, the wild bootstrap, and the parametric bootstrap. Bootstrap methods offer flexibility in obtaining lower and upper bounds through percentile or BCa methods. More details are given in Mason, F., Cantoni, E., & Ghisletta, P. (2021) <doi:10.5964/meth.6607> and Mason, F., Cantoni, E., & Ghisletta, P. (2024) <doi:10.1037/met0000643>.

Fabio Mason

confintROB

Confidence Intervals for Robust and Classical Linear Mixed Model
Estimators

Manuel Koller

Eva Cantoni

Paolo Ghisletta

medsim function

`medsim`
a data.frame with 5 columns and 420 rows:<dl>
<dt>obs</dt>
<dd>row number</dd><dt>id</dt>
<dd>participant number</dd><dt>time</dt>
<dd>time in waves from 0 to 18, with increments of 3</dd><dt>treat</dt>
<dd>treatment assignment, 1= treatment; 0= control</dd><dt>pos</dt>
<dd>the positive mood score</dd></dl>

Format

The simulated data set ispired by the medication example — medsim

`medsim`
a data.frame with 5 columns and 420 rows:<dl>
<dt>obs</dt>
<dd>row number</dd>

<dt>id</dt>
<dd>participant number</dd>

<dt>time</dt>
<dd>time in waves from 0 to 18, with increments of 3</dd>

<dt>treat</dt>
<dd>treatment assignment, 1= treatment; 0= control</dd>

<dt>pos</dt>
<dd>the positive mood score</dd>

</dl>

The simulated data set ispired by the medication example

medsim: The simulated data set ispired by the medication example

Description

Usage

Arguments

Format