simulation: Simulate a dataset which can be analyzed by SLTCA

In SLTCA: Scalable and Robust Latent Trajectory Class Analysis

Description

Simulate a dataset with longitudinal observations.

Usage

simulation(n)

Arguments

n	Sample size.

Value

Returns a data frame with 6 longitudinal features y.1 - y.6, including count (y.1 and y.2), binary (y.3 and y.4) and continuous (y.5 and y.6) type. Variable baselinecov is the baseline risk factor of latent classes. Variable latent is the true latent class labels.

Author(s)

Teng Fei. Email: [e-mail]

References

Hart, K.R., Fei, T. and Hanfelt, J.J. (2020), Scalable and robust latent trajectory class analysis using artificial likelihood. Biometrics. Accepted Author Manuscript <doi:10.1111/biom.13366>.

Examples

dat <- simulation(500)

SLTCA documentation built on Jan. 13, 2021, 5:14 p.m.