1d:T73e,# Predict combination scores and labels for new data sets using the training model 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. ```r ## 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. ## Returns A `data.frame` predicted combination scores (or probabilities) and labels ## Examples ```r # call data data(laparotomy) # define the function parameters markers <- laparotomy[, -1] status <- factor(laparotomy$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) ``` ## Author(s) Serra Ilayda Yerlitas, Serra Bersan Gengec, Necla Kochan, Gozde Erturk Zararsiz, Selcuk Korkmaz, Gokmen Zararsiz

predict.dtComb function