predict.dtComb {dtComb}

Predict combination scores and labels for new data sets using the training model

Description

The predict.dtComb is a function that generates predictions for a new dataset of biomarkers using the parameters from the fitted model. The function takes arguments newdata and model. The function's output is the combination scores and labels of object type.

Usage

## S3 method for class 'dtComb'
predict(object, newdata = NULL, ...)

Arguments

object

a list object where the parameters from the training model are saved.

newdata

a numeric new data set that includes biomarkers that have not been introduced to the model before.

...

further arguments. Currently has no effect on the results.

Value

A data.frame predicted combination scores (or probabilities) and labels

Author(s)

Serra Ilayda Yerlitas, Serra Bersan Gengec, Necla Kochan, Gozde Erturk Zararsiz, Selcuk Korkmaz, Gokmen Zararsiz

Examples

# call data
data(exampleData1)

# define the function parameters
markers <- exampleData1[, -1]
status <- factor(exampleData1$group, levels = c("not_needed", "needed"))
event <- "needed"

score1 <- linComb(
  markers = markers, status = status, event = event,
  method = "logistic", resample = "none",
  standardize = "none", direction = "<", cutoff.method = "Youden"
)

comb.score1 <- predict(score1, markers)

score2 <- nonlinComb(
  markers = markers, status = status, event = "needed", include.interact = TRUE,
  method = "polyreg", resample = "repeatedcv", nfolds = 5,
  nrepeats = 10, cutoff.method = "Youden", direction = "auto"
)

comb.score2 <- predict(score2, markers)

score3 <- mathComb(
  markers = markers, status = status, event = event,
  method = "distance", distance = "euclidean", direction = "auto",
  standardize = "tScore", cutoff.method = "Youden"
)

comb.score3 <- predict(score3, markers)