Nothing
context("get_candidate_covariates")
test_that("testing rwd data", {
data(rwd)
expect_equal(nrow(rwd), 69333)
expect_equal(ncol(rwd), 9)
expect_equal(length(unique(rwd$person_id)), 1000)
})
test_that("testing end-to-end run of automated covariate selection...", {
data(rwd)
basetable <- rwd %>% select(person_id, treatment, outcome_date) %>% distinct()
patientIds <- basetable$person_id #this can be used as patientIdVector argument for the functions in this package
step1 <- get_candidate_covariates(df = rwd, domainVarname = "domain", eventCodeVarname = "event_code" ,
patientIdVarname = "person_id", patientIdVector = patientIds,n = 100, min_num_patients = 10)
out1 <- step1$covars_data #this will be input to get_recurrence_covariates() function
step2 <- get_recurrence_covariates(df = out1, patientIdVarname = "person_id", eventCodeVarname = "event_code", patientIdVector = patientIds)
out2 <- step2$recurrence_data #this will be input to get_prioritised_covariates() function
out3 <- get_prioritised_covariates(df = out2, patientIdVarname = "person_id", exposureVector = basetable$treatment,
outcomeVector = ifelse(is.na(basetable$outcome_date), 0,1),patientIdVector = patientIds, k = 10)
expect_error(get_prioritised_covariates(df = out2, patientIdVarname = "person_id", exposureVector = basetable$treatment,
outcomeVector = ifelse(is.na(basetable$outcome_date), 0,1),patientIdVector = patientIds, k = 0))
out5 <- get_prioritised_covariates(df = out2, patientIdVarname = "person_id", exposureVector = basetable$treatment,
outcomeVector = ifelse(is.na(basetable$outcome_date), 0,1),patientIdVector = patientIds, k = 1000)
})
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