R: Estimate Correlations Between Repeatedly Measured Endpoints (E.g., Reliability) Based on Linear Mixed-Effects Models

# Estimate Correlations Between Repeatedly Measured Endpoints (E.g., Reliability) Based on Linear Mixed-Effects Models

## Documentation for package ‘CorrMixed’ version 1.1

- DESCRIPTION file
- Package NEWS

## Help Pages

Example.Data | An example dataset
Explore.WS.Corr | Explore within-subject correlations (reliabilities)
Fract.Poly | Fit fractional polynomials
Heatmap | Plot a heatmap of the correlation structure
Model.Fit | Compare the fit of linear mixed-effects models
plot Explore.WS.Corr | Plot of exploratory within-subject correlations (reliabilities)
plot WS.Corr.Mixed | Plot the within-subject correlations (reliabilities) obtained by using the mixed-effects modeling approch
plot WS.Corr.Mixed.SAS | Plot the within-subject correlations (reliabilities) obtained by using the mixed-effects modeling approch
plot.Explore.WS.Corr | Plot of exploratory within-subject correlations (reliabilities)
plot.WS.Corr.Mixed | Plot the within-subject correlations (reliabilities) obtained by using the mixed-effects modeling approch
plot.WS.Corr.Mixed.SAS | Plot the within-subject correlations (reliabilities) obtained by using the mixed-effects modeling approch
Spaghetti.Plot | Make a Spaghetti plot
WS.Corr.Mixed | Estimate within-subject correlations (reliabilities) based on a mixed-effects model.
WS.Corr.Mixed.SAS | Estimate within-subject (test-retest) correlations based on a mixed-effects model using the SAS proc MIXED output.