mmdgp: Generate longitudinal hierarchical data

In ryannick28/CustomFunctionsYrotha: Collection of my custom functions

Generate longitudinal hierarchical data

Description

A function to generate longitudinal hierarchical data. The data represents measurements from people, nested in classes. Each person is measured once per day for a number of days. There is an age, a gender, a day and a within-subject variable effect. The random effects are random intercepts for people and class, and a random slope for the within-subject predictor. This function can for example be used to test some analysis or some plotting procedure.

Usage

mmdgp(n = 200, nC = 5, sd_S = 3, sd_C = 5, sd_e = 2,
b0 = 50, tb = c(0,4,10,4,0), genb = 10, ageb = 1, xwithnb=2, sd_xwithn=1)

Arguments

n	Number of people
nC	Number of classes
sd_S	Standard deviation of people (random intercept)
sd_C	Standard deviation of classes (random intercept)
sd_e	Standard deviation of errors
b0	Intercept
tb	A vector containing the effects of each day. Length can be chosen depending on how many days should be included in the data set.
genb	Gender effect
ageb	Age effect
xwithnb	Main effect of the within-subject predictor
sd_xwithn	Standard deviation of the random slope effect of the within-subject predictor

Value

A data frame with the predictor variables and the target variable.

Examples

dat <- mmdgp()
# Lmer fit:
# lmerTest::lmer(y ~ gen + age + day + xwithn + (xwithn|id) + (1|class), dat)

ryannick28/CustomFunctionsYrotha documentation built on June 1, 2025, 4:02 p.m.