data_lcmm: Simulated dataset for lcmm and Jointlcmm functions

In CecileProust-Lima/lcmm: Extended Mixed Models Using Latent Classes and Latent Processes

Simulated dataset for lcmm and Jointlcmm functions

Description

The data were simulated from a joint latent class mixed model with 3 classes. Repeated data of 3 longitudinal outcomes (Ydep1, Ydep2, Ydep3) and censored time of event (Tevent, Event) with delayed entry (Tentry) were simulated for a total of 300 subjects. The three latent classes were predicted by the continuous covariate X3. In each latent class, the longitudinal outcome Ydep1 followed a linear mixed model including intercept, time and squared time both with correlated random-effects and class-specific fixed effects. In addition, the binary covariate X1 and its interaction with time X1:Time had a common impact (over classes) on the Ydep1 trajectory. The longitudinal ordinal outcomes Ydep2 and Ydep3 were generated from Ydep1 using threshold models with respectively 30 and 10 thresholds. In each latent class, the time of event followed a class-specific Weibull hazard with a common proportional effect of the binary covariate X2. Both time of entry Tentry and time of censoring had a uniform distribution

Format

A data frame with 1678 observations over 300 different subjects and 22 variables.

ID

subject identification number

Ydep1

longitudinal continuous outcome

Ydep2

longitudinal ordinal outcome with 31 levels

Ydep3

longitudinal ordinal outcome with 11 levels

Tentry

delayed entry for the time-to-event

Tevent

observed time-to-event: either censoring time or time of event

Event

indicator that Tevent is the time of event

Time

time of measurement

X1

binary covariate

X2

binary covariate

X3

continuous covariate

X4

categorical covariate

See Also

Jointlcmm, lcmm, hlme

CecileProust-Lima/lcmm documentation built on March 3, 2024, 5:23 p.m.