R Under development (unstable) (2025-10-08 r88906 ucrt) -- "Unsuffered Consequences"
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> library(medicalcoder)
> 
> ################################################################################
> # Verify that the pccc codes are retrievable as a data.frame
> pccc_codes <- get_pccc_codes()
> stopifnot("pccc_codes are a data.frame" = identical(class(pccc_codes), "data.frame"))
> stopifnot(
+   identical(
+     names(pccc_codes),
+     c("icdv", "dx", "full_code", "code", "condition", "subcondition", "transplant_flag", "tech_dep_flag", "pccc_v3.1", "pccc_v3.0", "pccc_v2.1", "pccc_v2.0")
+   )
+ )
> 
> ################################################################################
> # verify that there is not going to be an error if no matches are found
> dat <- data.frame(patid = 1:26,
+                   icd = c(letters, LETTERS),
+                   pr1 = 1:26,
+                   icdv = sample(9:10, size = 26, replace = TRUE))
> 
> stopifnot(sum(
+     comorbidities(data = dat, icd.codes = "icd", poa = 1, flag.method = "current", method = "pccc_v3.0")
+     , na.rm = TRUE) == 0)
> 
> stopifnot(sum(comorbidities(data = dat, id.vars = "patid", icd.codes = "icd",                    poa = 1, flag.method = "current", method = "pccc_v3.0"), na.rm = TRUE) == sum(1:26))
> stopifnot(sum(comorbidities(data = dat, id.vars = "patid", icd.codes = "icd", icdv.var = "icdv", poa = 1, flag.method = "current", method = "pccc_v3.0"), na.rm = TRUE) == sum(1:26))
> stopifnot(sum(comorbidities(data = dat, id.vars = "patid", icd.codes = "icd", icdv = 9,          poa = 1, flag.method = "current", method = "pccc_v3.0"), na.rm = TRUE) == sum(1:26))
> stopifnot(sum(comorbidities(data = dat, id.vars = "patid", icd.codes = "icd", icdv = 10,         poa = 1, flag.method = "current", method = "pccc_v3.0"), na.rm = TRUE) == sum(1:26))
> stopifnot(sum(comorbidities(data = dat, id.vars = "patid", icd.codes = "icd", dx = 1L,       poa = 1, flag.method = "current", method = "pccc_v3.0"), na.rm = TRUE) == sum(1:26))
> stopifnot(sum(comorbidities(data = dat, id.vars = "patid", icd.codes = "icd", dx = 0L,       poa = 1, flag.method = "current", method = "pccc_v3.0"), na.rm = TRUE) == sum(1:26))
> 
> stopifnot(sum(comorbidities(data = dat, icd.codes = "icd", method = "pccc_v2.0", poa = 1, flag.method = "current"), na.rm = TRUE) == 0)
> 
> stopifnot(sum(comorbidities(data = dat, id.vars = "patid", icd.codes = "icd",                    poa = 1, flag.method = "current", method = "pccc_v2.0"), na.rm = TRUE) == sum(1:26))
> stopifnot(sum(comorbidities(data = dat, id.vars = "patid", icd.codes = "icd", icdv.var = "icdv", poa = 1, flag.method = "current", method = "pccc_v2.0"), na.rm = TRUE) == sum(1:26))
> stopifnot(sum(comorbidities(data = dat, id.vars = "patid", icd.codes = "icd", icdv = 9,          poa = 1, flag.method = "current", method = "pccc_v2.0"), na.rm = TRUE) == sum(1:26))
> stopifnot(sum(comorbidities(data = dat, id.vars = "patid", icd.codes = "icd", icdv = 10,         poa = 1, flag.method = "current", method = "pccc_v2.0"), na.rm = TRUE) == sum(1:26))
> stopifnot(sum(comorbidities(data = dat, id.vars = "patid", icd.codes = "icd", dx = 1L,       poa = 1, flag.method = "current", method = "pccc_v2.0"), na.rm = TRUE) == sum(1:26))
> stopifnot(sum(comorbidities(data = dat, id.vars = "patid", icd.codes = "icd", dx = 0L,       poa = 1, flag.method = "current", method = "pccc_v2.0"), na.rm = TRUE) == sum(1:26))
> 
> ################################################################################
> # Verify the output of the pccc call
> 
> rtn <- comorbidities(data = mdcr, icd.codes = "code", method = "pccc_v3.0", poa = 1, flag.method = "current")
> 
> expected_rtn <-
+   structure(
+     list(
+       congeni_genetic_dxpr_only = 1L,
+       congeni_genetic_tech_only = 0L,
+       congeni_genetic_dxpr_and_tech = 0L,
+       congeni_genetic_dxpr_or_tech = 1L,
+       cvd_dxpr_only = 0L,
+       cvd_tech_only = 0L,
+       cvd_dxpr_and_tech = 1L,
+       cvd_dxpr_or_tech = 1L,
+       gi_dxpr_only = 0L,
+       gi_tech_only = 0L,
+       gi_dxpr_and_tech = 1L,
+       gi_dxpr_or_tech = 1L,
+       hemato_immu_dxpr_only = 1L,
+       hemato_immu_tech_only = 0L,
+       hemato_immu_dxpr_and_tech = 0L,
+       hemato_immu_dxpr_or_tech = 1L,
+       malignancy_dxpr_only = 1L,
+       malignancy_tech_only = 0L,
+       malignancy_dxpr_and_tech = 0L,
+       malignancy_dxpr_or_tech = 1L,
+       metabolic_dxpr_only = 0L,
+       metabolic_tech_only = 0L,
+       metabolic_dxpr_and_tech = 1L,
+       metabolic_dxpr_or_tech = 1L,
+       misc_dxpr_only = 0L,
+       misc_tech_only = 0L,
+       misc_dxpr_and_tech = 1L,
+       misc_dxpr_or_tech = 1L,
+       neonatal_dxpr_only = 1L,
+       neonatal_tech_only = 0L,
+       neonatal_dxpr_and_tech = 0L,
+       neonatal_dxpr_or_tech = 1L,
+       neuromusc_dxpr_only = 0L,
+       neuromusc_tech_only = 0L,
+       neuromusc_dxpr_and_tech = 1L,
+       neuromusc_dxpr_or_tech = 1L,
+       renal_dxpr_only = 0L,
+       renal_tech_only = 0L,
+       renal_dxpr_and_tech = 1L,
+       renal_dxpr_or_tech = 1L,
+       respiratory_dxpr_only = 0L,
+       respiratory_tech_only = 0L,
+       respiratory_dxpr_and_tech = 1L,
+       respiratory_dxpr_or_tech = 1L,
+       any_tech_dep = 1L,
+       any_transplant = 1L,
+       num_cmrb = 11L,
+       cmrb_flag = 1L
+     ),
+     row.names = c(NA, -1L),
+     class = c("medicalcoder_comorbidities", "data.frame"),
+     method = "pccc_v3.0",
+     id.vars = "..medicalcoder_id..",
+     flag.method = "current"
+   )
> 
> stopifnot(
+   "pccc v3 with mdcr is as all.equal" = isTRUE(all.equal(rtn, expected_rtn)),
+   "pccc v3 with mdcr is as expected" = isTRUE(identical(rtn, expected_rtn))
+ )
> 
> ################################################################################
> # test longitudinal output
> 
> args <- list(data = mdcr_longitudinal, id.vars = c("patid", "date"), icdv.var = "icdv", icd.codes = "code", poa = 1)
> 
> current <-
+   list(
+     pccc_current_v3.1    = do.call(comorbidities, c(args, list(flag.method = 'current',    method = "pccc_v3.1"))),
+     pccc_cumulative_v3.1 = do.call(comorbidities, c(args, list(flag.method = "cumulative", method = "pccc_v3.1"))),
+     pccc_current_v3.0    = do.call(comorbidities, c(args, list(flag.method = 'current',    method = "pccc_v3.0"))),
+     pccc_cumulative_v3.0 = do.call(comorbidities, c(args, list(flag.method = "cumulative", method = "pccc_v3.0"))),
+     pccc_current_v2.1    = do.call(comorbidities, c(args, list(flag.method = 'current',    method = "pccc_v2.1"))),
+     pccc_cumulative_v2.1 = do.call(comorbidities, c(args, list(flag.method = "cumulative", method = "pccc_v2.1"))),
+     pccc_current_v2.1    = do.call(comorbidities, c(args, list(flag.method = 'current',    method = "pccc_v2.0"))),
+     pccc_cumulative_v2.1 = do.call(comorbidities, c(args, list(flag.method = "cumulative", method = "pccc_v2.0")))
+ )
> 
> expected <- list.files(path = "expected-results-for-test-pccc", pattern = "\\.rds$", full.name = TRUE)
> names(expected) <- sub("\\.rds", "", basename(expected))
> expected <- sapply(expected, readRDS, simplify = FALSE)
> 
> for (obj in names(current)) {
+   stopifnot(all.equal(expected[[obj]], current[[obj]]))
+ }
> 
> ################################################################################
> # tests for different sets of inputs
> # with or with icdv
> # with or without dx
> 
> # common arguments for the calls to comorbidities
> cargs <-
+   list(
+     data = mdcr,
+     id.vars = "patid",
+     icd.codes = "code",
+     poa = 1,
+     method = "pccc_v3.1"
+   )
> 
> out00 <- do.call(comorbidities, c(cargs, list(icdv.var = "icdv", dx.var = "dx")))
> out01 <- do.call(comorbidities, c(cargs, list(                   dx.var = "dx")))
> out02 <- do.call(comorbidities, c(cargs, list(icdv = 9,          dx.var = "dx")))
> out03 <- do.call(comorbidities, c(cargs, list(icdv = 10,         dx.var = "dx")))
> out04 <- do.call(comorbidities, c(cargs, list(icdv.var = "icdv"               )))
> out05 <- do.call(comorbidities, c(cargs, list(icdv.var = "icdv", dx = 0       )))
> out06 <- do.call(comorbidities, c(cargs, list(icdv.var = "icdv", dx = 1       )))
> out07 <- do.call(comorbidities, c(cargs))
> 
> # all the outputs should be unique
> stopifnot(
+   !isTRUE(all.equal(out00, out01)),
+   !isTRUE(all.equal(out00, out02)),
+   !isTRUE(all.equal(out00, out03)),
+   !isTRUE(all.equal(out00, out04)),
+   !isTRUE(all.equal(out00, out05)),
+   !isTRUE(all.equal(out00, out06)),
+   !isTRUE(all.equal(out00, out07)),
+ 
+   !isTRUE(all.equal(out01, out02)),
+   !isTRUE(all.equal(out01, out03)),
+   !isTRUE(all.equal(out01, out04)),
+   !isTRUE(all.equal(out01, out05)),
+   !isTRUE(all.equal(out01, out06)),
+   !isTRUE(all.equal(out01, out07)),
+ 
+   !isTRUE(all.equal(out02, out03)),
+   !isTRUE(all.equal(out02, out04)),
+   !isTRUE(all.equal(out02, out05)),
+   !isTRUE(all.equal(out02, out06)),
+   !isTRUE(all.equal(out02, out07)),
+ 
+   !isTRUE(all.equal(out03, out04)),
+   !isTRUE(all.equal(out03, out05)),
+   !isTRUE(all.equal(out03, out06)),
+   !isTRUE(all.equal(out03, out07)),
+ 
+   !isTRUE(all.equal(out04, out05)),
+   !isTRUE(all.equal(out04, out06)),
+   !isTRUE(all.equal(out04, out07)),
+ 
+   !isTRUE(all.equal(out05, out06)),
+   !isTRUE(all.equal(out05, out07)),
+ 
+   !isTRUE(all.equal(out06, out07))
+ )
> 
> # out00 should be "correct", out01 and out04 should only have false positives
> stopifnot(
+   all(out00$num_cmrb <= out01$num_cmrb),
+   all(out00$num_cmrb <= out04$num_cmrb)
+ )
> 
> # for out02, out03, out05, and out06, there will be false positives and false
> # negatives
> stopifnot(
+   !identical(out00$num_cmrb, out02$num_cmrb),
+   !identical(out00$num_cmrb, out03$num_cmrb),
+   !identical(out00$num_cmrb, out05$num_cmrb),
+   !identical(out00$num_cmrb, out06$num_cmrb),
+   !identical(out00$num_cmrb, out07$num_cmrb)
+ )
> 
> ################################################################################
> #                                 End of File                                  #
> ################################################################################
> 
> proc.time()
   user  system elapsed 
  16.17    2.25   18.32