Construct a design matrix
model_matrix() is a stricter version of stats::model.matrix(). Notably,
model_matrix() will never drop rows, and the result will be a tibble.
model_matrix(terms, data)
terms |
A terms object to construct a model matrix with. This is
typically the terms object returned from the corresponding call to
|
data |
A tibble to construct the design matrix with. This is
typically the tibble returned from the corresponding call to
|
The following explains the rationale for some of the difference in arguments
compared to stats::model.matrix():
contrasts.arg: Set the contrasts argument, options("contrasts")
globally, or assign a contrast to the factor of interest directly using
stats::contrasts(). See the examples section.
xlev: Not allowed because model.frame() is never called, so it is
unnecessary.
...: Not allowed because the default method of model.matrix() does
not use it, and the lm method uses it to pass potential offsets and
weights through, which are handled differently in hardhat.
A tibble containing the design matrix.
# ---------------------------------------------------------------------------
# Example usage
framed <- model_frame(Sepal.Width ~ Species, iris)
model_matrix(framed$terms, framed$data)
# ---------------------------------------------------------------------------
# Missing values never result in dropped rows
iris2 <- iris
iris2$Species[1] <- NA
framed2 <- model_frame(Sepal.Width ~ Species, iris2)
model_matrix(framed2$terms, framed2$data)
# ---------------------------------------------------------------------------
# Contrasts
# Default contrasts
y <- factor(c("a", "b"))
x <- data.frame(y = y)
framed <- model_frame(~y, x)
# Setting contrasts directly
y_with_contrast <- y
contrasts(y_with_contrast) <- contr.sum(2)
x2 <- data.frame(y = y_with_contrast)
framed2 <- model_frame(~y, x2)
# Compare!
model_matrix(framed$terms, framed$data)
model_matrix(framed2$terms, framed2$data)
# Also, can set the contrasts globally
global_override <- c(unordered = "contr.sum", ordered = "contr.poly")
rlang::with_options(
.expr = {
model_matrix(framed$terms, framed$data)
},
contrasts = global_override
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