datfc {CovSel}

Simulated Data, Mixed

Description

This data is simulated. The covariates, X, and the treatment, T, are all generated by simulating from independent or multivariate normal distributions and then some variables are dichotomized to get binary variables with a certain dependence structure. The code generating the data is

library(bindata)
set.seed(9327529)
n<-500
x1 <- rnorm(n, mean = 0, sd = 1)
x2 <- rbinom(n, 1, prob = 0.5)
x25 <- rmvbin(n, bincorr=cbind(c(1,0.7),c(0.7,1)), margprob=c(0.5,0.5))
x2 <- x25[,1]
Sigma <- matrix(c(1,0.5,0.5,1),ncol=2)
x34 <- mvrnorm(n, rep(0, 2), Sigma)
x3 <- x34[,1]
x4 <- x34[,2]
x5 <- x25[,2]
x6 <- rbinom(n, 1, prob = 0.5)
x7<- rnorm(n, mean = 0, sd = 1)
x8 <- rbinom(n, 1, prob = 0.5)
e0<-rnorm(n)
e1<-rnorm(n)
p <- 1/(1 + exp(3 - 1.2 * x1 - 3.7 * x2 - 1.5 * x3 - 0.3 * x4 - 0.3 * x5 - 1.9 * x8))
T <- rbinom(n, 1, prob = p)
y0 <- 4 + 2 * x1 + 3 * x4 + 5 * x5 + 2 * x6 + e0
y1 <- 2 + 2 * x1 + 3 * x4+ 5 * x5 + 2 * x6 + e1
y <- y1 * T + y0 * (1 - T)
datfc <- data.frame(x1, x2, x3, x4, x5, x6, x7, x8, y0, y1, y, T)
datfc[, c(2, 5, 6, 8)] <- lapply(datfc[, c(2, 5, 6, 8)], factor)
datfc[, 12] <- as.numeric(datfc[, 12])

Usage

data(datfc)

Format

A data frame with 500 observations on the following 12 variables.

x1

a numeric vector

x2

a factor with two levels

x3

a numeric vector

x4

a numeric vector

x5

a factor with two levels

x6

a factor with two levels

x7

a numeric vector

x8

a factor with two levels

y0

a numeric vector

y1

a numeric vector

y

a numeric vector

T

a numeric vector