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### train.test for Score
library(testthat)
library(prodlim)
library(survival)
library(riskRegression)
library(data.table)
context("riskRegression")
test.train.test <- function(){
train.sample.size <- 200
test.sample.size <- 500
tau <- c(4,5)
types <- list(list(data = "binary", model = "glm", response = "Y",left.extra = "family", right.extra = "binomial"),
list(data = "survival", model = "coxph", response = "Surv(time,event)",left.extra = "x", right.extra = TRUE),
list(data = "competing.risks", model = "CSC", response = "Hist(time,event)"))
for (typ in types){
cat(paste0("Testing ", typ$data, " data with \n"))
test_that(paste0("Testing ", typ$data, " data with "),{
set.seed(18)
train.data <- sampleData(n=train.sample.size,outcome=typ$data)
test.data <- sampleData(n=test.sample.size,outcome=typ$data)
input.m <- list(data=train.data)
if (typ$data != "competing.risks"){
input.m[[typ$left.extra]] <- typ$right.extra
}
input.m1 <- append(list(formula = as.formula(paste0(typ$response,"~X1+X2+X7+X9"))), input.m)
input.m2 <- append(list(formula = as.formula(paste0(typ$response,"~X3+X5+X6"))), input.m)
m1 <- do.call(typ$model, input.m1)
m2 <- do.call(typ$model, input.m2)
input.score <- list(object =list("m(X1+X2+X7+X9)"=m1,"m(X3+X5+X6)"=m2), formula = as.formula(paste0(typ$response,"~1")),data=test.data,conf.int=TRUE,progress.bar=NULL)
if (typ$data != "binary"){
cat("with formula=Hist(time,event) ~ 1 and conservative = FALSE \n")
input.score[["conservative"]] <- FALSE #check dependence on covariates
input.score[["times"]] <- tau
x1 <- do.call(Score, input.score)
cat("with formula=Hist(time,event) ~ 1 and conservative = TRUE \n")
input.score[["conservative"]] <- TRUE #check conservative when censoring does not depend on covariates
x2 <- do.call(Score, input.score)
cat("with formula=Hist(time,event) ~ X1+X2 and conservative = FALSE \n")
input.score[["conservative"]] <- FALSE #check dependence on covariates
input.score[["formula"]] <- as.formula(paste0(typ$response,"~X1+X2"))
x3 <- do.call(Score, input.score)
cat("with formula=Hist(time,event) ~ X1+X2 and conservative = TRUE \n")
input.score[["conservative"]] <- TRUE #check dependence on covariates when conservative is true!
x4 <- do.call(Score, input.score)
}
else {
x1 <- do.call(Score, input.score)
x2 <- "NOT NEEDED HERE"
x3 <- "NOT NEEDED HERE"
x4 <- "NOT NEEDED HERE"
}
expect_output(print(x1))
expect_output(print(x2))
expect_output(print(x3))
expect_output(print(x4))
})
}
}
test.train.test()
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