data.sim.ibm: A simulated data set under a mixed model with random...

In lmenssp: Linear Mixed Effects Models with Non-Stationary Stochastic Processes

Description

A longitudinal data set containing measurements on 500 subjects, each with their own sequence of follow-up time points collected at irregularly spaced follow-up time points.

Usage

data("data.sim.ibm")

Format

A data frame with 8462 observations on the following 6 variables.

id

a numeric vector: subject identification

sex

a numeric vector: 0 = male, 1 = female

bage

a numeric vector: baseline age in years

fu

a numeric vector: follow-up time in years

pwl

a numeric vector: piecewise linear term, calculated as, max(0, age-56.5)

log.egfr

a numeric vector: response variable representing natural logarithm of estimated glomerular filtration rate

Details

For the details of the true parameter settings, see Diggle, Sousa and Asar (2015).

References

Diggle PJ, Sousa I, Asar O (2015) Real time monitoring of progression towards renal failure in primary care patients. Biostatistics, 16(3), 522-536.

Examples

data(data.sim.ibm)
str(data.sim.ibm)

lmenssp documentation built on May 2, 2019, 8:32 a.m.