tests/testthat/test-NMA_run.R

In ICON-in-R/NMA: Easy Network Meta-Analysis

test_that("new_NMA", {
  
  bugs_params <-
    list(
      PROG = "openBugs",  # which version of BUGS to use to run the MCMC
      N.BURNIN = 10,#00,  # number of steps to throw away
      N.SIMS = 150,#0,    # total number of simulations
      N.CHAINS = 2,       # number of chains
      N.THIN = 1,         # thinning rate
      PAUSE = TRUE)
  
  REFTX <- "X"                # reference treatment
  label_name <- "label_name"
  
  file_name <- system.file("extdata", package = "NMA")
  # file_name <- "C:/Users/n8tha/Documents/R/NMA/inst/extdata/survdata_"
  
  survDataHR <-
    read.csv(file.path(file_name, "survdata_hr_test.csv"),
             header = TRUE,
             as.is = TRUE)
  
  survDataBin <-
    read.csv(file.path(file_name, "survdata_bin_test.csv"),
             header = TRUE,
             as.is = TRUE)
  
  survDataMed <-
    read.csv(file.path(file_name, "survdata_med_test.csv"),
             header = TRUE,
             as.is = TRUE) %>% 
    mutate(medR = floor(medR))
  
  data_types <- c("hr_data", "surv_bin_data", "med_data")
  
  nma_model <- list()
  
  # random or fixed effects models
  for (i in c(TRUE, FALSE)) {
    
    datasets <- combn(data_types, 2, simplify = FALSE)
    nma_model[[as.character(i)]] <-
      vector(mode = "list", length = length(datasets))
    
    # all pairs of types of survival data
    for (j in seq_along(datasets)) {
      
      nma_model[[as.character(i)]][[j]] <-
        new_NMA(survDataHR = survDataHR,
                survDataMed = survDataMed,
                survDataBin = survDataBin,
                bugs_params = bugs_params,
                is_random = i,
                data_type = datasets[[j]],
                refTx = REFTX ,
                effectParam = "beta",
                label = "",
                endpoint = "")
    }
  }
  
  model_ref <- readRDS(test_path("nma_model.RDS"))
  
  expect_length(nma_model, length(model_ref))
})


test_that("NMA_run", {
  
  model_ref <- readRDS(test_path("nma_model.RDS"))

  
  nma_res <- list()

  for (i in c(TRUE, FALSE)) {

    nma_res[[as.character(i)]] <-
      vector(mode = "list", length = length(model_ref[[1]]))

    for (j in seq_along(model_ref[[1]])) {
      nma_res[[as.character(i)]][[j]] <-
        NMA_run(model_ref[[as.character(i)]][[j]], save = FALSE)
    }
  }
  
  expect_length(nma_res, length(model_ref))
})



# test if data not available

# test updating model runs