ttest_filter | R Documentation |
Simple univariate filter using t-test using the Rfast package for speed. Can be applied to all or a subset of predictors.
ttest_filter( y, x, force_vars = NULL, nfilter = NULL, p_cutoff = 0.05, rsq_cutoff = NULL, type = c("index", "names", "full") )
y |
Response vector |
x |
Matrix of predictors |
force_vars |
Vector of column names within |
nfilter |
Number of predictors to return. If |
p_cutoff |
p value cut-off |
rsq_cutoff |
r^2 cutoff for removing predictors due to collinearity.
Default |
type |
Type of vector returned. Default "index" returns indices, "names" returns predictor names, "full" returns a matrix of p values. |
Integer vector of indices of filtered parameters (type = "index") or
character vector of names (type = "names") of filtered parameters in order
of t-test p-value. If type
is "full"
full output from
Rfast::ttests is returned.
## sigmoid function sigmoid <- function(x) {1 / (1 + exp(-x))} ## load iris dataset and simulate a binary outcome data(iris) dt <- iris[, 1:4] colnames(dt) <- c("marker1", "marker2", "marker3", "marker4") dt <- as.data.frame(apply(dt, 2, scale)) y2 <- sigmoid(0.5 * dt$marker1 + 2 * dt$marker2) > runif(nrow(dt)) y2 <- factor(y2, labels = c("C1", "C2")) ttest_filter(y2, dt) # returns index of filtered predictors ttest_filter(y2, dt, type = "name") # shows names of predictors ttest_filter(y2, dt, type = "full") # full results table
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