Data used for fitting examples

Description

Example data for logistic, Poisson and negative binomial models.

Usage

data("simData")

Format

A data frame with 200 observations on the following 8 variables.

obs

a binary vector. Used as a response for a logistic model.

x1

a numeric vector.

x2

a numeric vector.

x3

a categorical vector with levels blue, red, and yellow.

z1

a categorical vector with levels D1, D2, D3, D4, and D5.

z2

a categorical vector with levels 1, 2, 3, 4, and 5.

z3

a categorical vectir with levels A, B, and D.

count

a numeric vector. Used as a response for a Poisson model.

Details

The levels of z2 can be nested within $z1$. The observations were generated with the code shown in the examples section.

Examples

set.seed(47819)
x1 <- rnorm(200, 10, 1)
x2 <- rnorm(200, 5, 1)
x3 <- sample(c("red", "blue", "yellow"), size = 200, replace = TRUE)
z1 <- factor(rep(c("D1", "D2", "D3", "D4", "D5"), each = 40))
z2 <- factor(rep(rep(1:4, each = 5), 10))
z3 <- factor(c(rep("A", 100), rep("B", 60), rep("D", 40)))
kX <- model.matrix(~x1 + x2 + x3)
kZ <- cbind(model.matrix(~ 0+z1), model.matrix(~ 0+z1:z2), model.matrix(~ 0+z3))
kBeta <- c(5, -4, 5, 0, 8)
kU <- 3 * rt(28, 5)
linf0 <- kX 
prob0 <- exp(linf0)/(1+exp(linf0))
obs <- as.numeric(runif(100) < prob0)
simData <- data.frame(obs, x1, x2, x3, z1, z2, z3)

Results