odata | R Documentation |
A simulated example dataset with ordered categorical outcome variable containing different types of covariates for illustration purposes.
odata
A data frame with 1000 rows and 5 variables
For the exact data generating process, see the example below.
Y |
ordered outcome, classes 1, 2, and 3 |
X1 |
continuous covariate, N(0,1) |
X2 |
categorical covariate, values 1, 2, and 3 |
X3 |
binary covariate, values 0 and 1 |
X4 |
continuous covariate, N(0,10) |
# generate example data # set seed for replicability set.seed(123) # number of observations n <- 1000 # various covariates X1 <- rnorm(n, 0, 1) # continuous X2 <- rbinom(n, 2, 0.5) # categorical X3 <- rbinom(n, 1, 0.5) # dummy X4 <- rnorm(n, 0, 10) # noise # bind into matrix X <- as.matrix(cbind(X1, X2, X3, X4)) # deterministic component deterministic <- X1 + X2 + X3 # generate continuous outcome with logistic error Y <- deterministic + rlogis(n, 0, 1) # thresholds for continuous outcome cuts <- quantile(Y, c(0, 1/3, 2/3, 1)) # discretize outcome into ordered classes 1, 2, 3 Y <- as.numeric(cut(Y, breaks = cuts, include.lowest = TRUE)) # save data as a dataframe odata <- as.data.frame(cbind(Y, X)) # end of data generating
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