Process Data for Model Construction

Preprocesses data for binomial or survival analysis. Aligns and filters data based on sample IDs, optionally scales data, and ensures appropriate data types. Handles missing values by removing columns with NA values.

Usage

ProcessingData(x, y, scale, type = c("binomial", "survival"))

Arguments

x

Data frame of predictors with first column as IDs.

y

Data frame of outcomes with first column as IDs. For survival, expects two additional columns for time and status.

scale

Logical indicating whether to scale predictors.

type

Character string: `"binomial"` or `"survival"`.

Value

List containing:

x_scale

Processed predictor matrix

y

Processed outcome variable

x_ID

Sample IDs

Examples

x <- data.frame(ID = 1:10, predictor1 = rnorm(10), predictor2 = rnorm(10))
y <- data.frame(ID = 1:10, outcome = sample(c(0, 1), 10, replace = TRUE))
result <- ProcessingData(x, y, scale = TRUE, type = "binomial")
#> ℹ Converting outcome to factor