vcrpart-demo {vcrpart} | R Documentation |
Synthetic data sets
Description
Synthetic data for illustrations.
Usage
data(vcrpart_1)
data(vcrpart_2)
data(vcrpart_3)
data(unemp)
Format
y
ordered factor. The response variable
id, PID
factor. The subject identification vector.
wave
numeric. The wave identification vector.
treat
a dummy variable. The treatment effect.
x1, x2
numeric predictor variables.
z1, z2, z3, z2
moderator (partitioning) variables.
GHQL
self rated general happiness.
YEAR
survey year.
UNEMP
unemployed or not.
AGE
age.
FISIT
self-reported financial situation.
GENDER
gender.
UEREGION
regional unemployment.
See Also
Examples
## --------------------------------------------------------- #
## generating 'vcrpart_1'
## --------------------------------------------------------- #
## create skeletton
set.seed(1)
vcrpart_1 <- data.frame(id = factor(rep(1:50, each = 4)),
wave = rep(1:4, 50),
treat = sample(0:1, 200, TRUE))
## add partitioning variables
vcrpart_1$z1 <- rnorm(50)[vcrpart_1$id]
vcrpart_1$z2 <- rnorm(200)
vcrpart_1$z3 <- factor(sample(1:2, 50, TRUE)[vcrpart_1$id])
vcrpart_1$z4 <- factor(sample(1:2, 200, TRUE))
## simulate response
eta <- 2 * vcrpart_1$treat * (vcrpart_1$z4 == "1")
eta <- eta + rnorm(50)[vcrpart_1$id] + rlogis(200)
vcrpart_1$y <- cut(-eta, c(-Inf, -1, 1, Inf), 1:3,
ordered_result = TRUE)
## --------------------------------------------------------- #
## generating 'vcrpart_2'
## --------------------------------------------------------- #
set.seed(1)
vcrpart_2 <- data.frame(x1 = rnorm(100),
x2 = rnorm(100),
z1 = factor(sample(1:3, 100, TRUE)),
z2 = factor(sample(1:3, 100, TRUE)))
vcrpart_2$y <- vcrpart_2$x1 * (vcrpart_2$z1 == "2") +
2 * vcrpart_2$x1 * (vcrpart_2$z1 == "3")
vcrpart_2$y <- vcrpart_2$y + rnorm(100)
## --------------------------------------------------------- #
## generating 'vcrpart_3'
## --------------------------------------------------------- #
set.seed(1)
vcrpart_3 <- data.frame(x1 = rnorm(100),
z1 = runif(100, -pi/2, pi/2))
vcrpart_3$y <- vcrpart_3$x1 * sin(vcrpart_3$z1) + rnorm(100)
## --------------------------------------------------------- #
## generating 'unemp'
## --------------------------------------------------------- #
## create skeletton
set.seed(1)
unemp <- data.frame(PID = factor(rep(1:50, each = 4)),
UNEMP = rep(c(0, 0, 1, 1), 50),
YEAR = rep(2001:2004, 50))
## add partitioning variables
unemp$AGE <- runif(50, 25, 60)[unemp$PID] + unemp$YEAR - 2000
unemp$FISIT <- ordered(sample(1:5, 200, replace = TRUE))
unemp$GENDER <- factor(sample(c("female", "male"), 50, replace = TRUE)[unemp$PID])
unemp$UEREGION <- runif(50, 0.02, 0.1)[unemp$PID]
## simulate response
eta <- 2 * unemp$UNEMP * (unemp$FISIT == "1" | unemp$FISIT == "2")
eta <- eta + rnorm(50)[unemp$PID] + rlogis(200)
unemp$GHQL <- cut(-eta, c(-Inf, -1, 0, 1, Inf), 1:4,
ordered_result = TRUE)
[Package vcrpart version 1.0-5 Index]