datf {CovSel}

Simulated Data, Factors

Description

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

library(bindata)
set.seed(9327529)
n<-500
x1 <- 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))
x34 <- rmvbin(n, bincorr=cbind(c(1,0.7),c(0.7,1)), margprob=c(0.5,0.5))
x2 <- x25[,1]
x3 <- x34[,1]
x4 <- x34[,2]
x5 <- x25[,2]
x6 <- rbinom(n, 1, prob = 0.5)
x7<- rbinom(n, 1, prob = 0.5)
x8 <- rbinom(n, 1, prob = 0.5)
e0<-rnorm(n)
e1<-rnorm(n)
p <- 1/(1 + exp(3 - 1.5 * x1 - 1.5 * x2 - 1.5 * x3 - 0.1 * x4 - 0.1 * x5 - 1.3 * 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)
datf <- data.frame(x1, x2, x3, x4, x5, x6, x7, x8, y0, y1, y, T)
datf[, 1:8] <- lapply(datf[, 1:8], factor)
datf[, 12] <- as.numeric(datf[, 12])

Usage

data(datf)

Format

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

x1

a factor with two levels

x2

a factor with two levels

x3

a factor with two levels

x4

a factor with two levels

x5

a factor with two levels

x6

a factor with two levels

x7

a factor with two levels

x8

a factor with two levels

y0

a numeric vector

y1

a numeric vector

y

a numeric vector

T

a numeric vector