The dataset consists in a subsample of the Paquid prospective cohort study. Repeated measures cognitive measures (MMSE, IST, BVRT psychometric tests), physical dependency (HIER) and depression sympatomatology (CESD) were collected over a maximum period of 20 years along with dementia information (age at dementia diagnosis, dementia diagnosis information). Time-independent socio-demographic information is also provided (CEP, male, age_init).
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
The data were simulated from a 3-latent class linear mixed model. Repeated data for 100 subjects were simulated. The three latent classes are predicted by X2 and X3. In each latent class, Y follows a linear mixed model including intercept and time both with correlated random-effects and class-specific fixed effects. In addition, X1 and X1*time have a common impact over classes on the Y trajectory.
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