mmm2 (version 1.2)

mlcd: Multivariate Longitudinal Count Data (MLCD)

Description

A data frame with 2000 observations on the following 6 variables. MLCD is a simulated bivariate longitudinal count dataset assuming there are 500 subjects in the study whose data are collected at 4 equally-spaced time points.

Usage

data(mlcd)

Format

A data frame with 2000 observations on the following 6 variables.

ID

a numeric vector for subject ID

resp1

a numeric vector for the first longitudinal count response

resp2

a numeric vector for the second longitudinal count response

X

a numeric vector for the covariate, X

time

a numeric vector for the time point at which observations are collected

X.time

a numeric vector for the interaction between X and time

Details

The covariates, X and time are the standardized values indeed. The related interaction is calculated by using these standardized values. X is a time-independent covariate. For the details of data generation see the user manual of the R package mmm at http://cran.r-project.org/web/packages/mmm/index.html.

References

Asar, O. (2012). On multivariate longitudinal binary data models and their applications in forecasting. MS Thesis, Middle East Technical University. Available at http://www.lancaster.ac.uk/pg/asar/thesis-Ozgur-Asar.

Erhardt, V. (2009). corcounts: Generate Correlated Count Random Variable. R package version 1.4. URL http://CRAN.R-project.org/package=corcounts.

Examples

data(mlcd)
plot(mlcd$X,mlcd$resp1)