humanpred · billdenney · Aug 20, 2026 · Aug 20, 2026
diff --git a/NEWS.md b/NEWS.md
@@ -6,6 +6,16 @@ the dosing including dose amount and route.
 
 # Development version
 
+* Corrected registry description strings that did not match the
+  implementation (#582).  `adj.r.squared.factor` is described as selecting
+  the regression with the most points among those within the tolerance of
+  the best adjusted r^2, rather than as a factor added per data point.
+  `span.ratio` is described as the lambda z time span divided by the
+  half-life; the previous text stated the inverse.  The eight dose-aware
+  `aucint*`/`aumcint*` parameters ending in `.dose` no longer describe
+  themselves as `AUCdn`/`AUMCdn`, which is this package's abbreviation for
+  dose normalization (`auclast.dn` and similar).
+
 * Bug fix: `pk.calc.sparse_auc()` and `pk.calc.sparse_aumc()` now use their
   `options` argument when integrating the mean concentration-time profile, so
   per-run options (e.g. `PKNCAdata(options = list(conc.blq = "keep"))`) affect

diff --git a/R/PKNCA.options.R b/R/PKNCA.options.R
@@ -4,9 +4,12 @@
   adj.r.squared.factor=function(x, default=FALSE, description=FALSE) {
     if (description)
       return(paste(
-        "The adjusted r^2 for the calculation of lambda.z has this factor",
-        "times the number of data points added to it.  It allows for more",
-        "data points to be preferred in the calculation of half-life."))
+        "During the calculation of lambda.z, all candidate regressions",
+        "with an adjusted r^2 within adj.r.squared.factor of the best",
+        "adjusted r^2 are considered acceptable, and the acceptable",
+        "regression using the most data points is selected.  It allows",
+        "for more data points to be preferred in the calculation of",
+        "half-life."))
     if (default)
       return(0.0001)
     checkmate::assert_number(x, .var.name = "adj.r.squared.factor")

diff --git a/R/aucint.R b/R/aucint.R
@@ -262,7 +262,7 @@ add.interval.col("aucint.last.dose",
                  values=c(FALSE, TRUE),
                  unit_type="auc",
                  pretty_name="AUCint (based on AUClast extrapolation, dose-aware)",
-                 desc="AUCdn T1 to T2 (zero extrap)",
+                 desc="AUC T1 to T2, dose-aware (zero extrap)",
                  formalsmap=list(conc="conc.group", time="time.group", time.dose="time.dose.group"),
                  pptestcd_cdisc="AUCINTD",
                  pptest_cdisc="AUC from T1 to T2 Normalized by Dose")
@@ -282,7 +282,7 @@ add.interval.col("aucint.all.dose",
                  values=c(FALSE, TRUE),
                  unit_type="auc",
                  pretty_name="AUCint (based on AUCall extrapolation, dose-aware)",
-                 desc="AUCdn T1 to T2 (AUCall extrap)",
+                 desc="AUC T1 to T2, dose-aware (AUCall)",
                  formalsmap=list(conc="conc.group", time="time.group", time.dose="time.dose.group"),
                  pptestcd_cdisc="AUCINTAD",
                  pptest_cdisc="AUCint (based on AUCall extrapolation, dose-aware)")
@@ -303,7 +303,7 @@ add.interval.col("aucint.inf.obs.dose",
                  values=c(FALSE, TRUE),
                  unit_type="auc",
                  pretty_name="AUCint (based on AUCinf,obs extrapolation, dose-aware)",
-                 desc="AUCdn T1 to T2 (AUCinf,obs extrap)",
+                 desc="AUC T1 to T2, dose-aware (AUCinf,obs)",
                  formalsmap=list(conc="conc.group", time="time.group", time.dose="time.dose.group"),
                  depends=c("lambda.z", "clast.obs"),
                  pptestcd_cdisc="AUCINTID",
@@ -325,7 +325,7 @@ add.interval.col("aucint.inf.pred.dose",
                  values=c(FALSE, TRUE),
                  unit_type="auc",
                  pretty_name="AUCint (based on AUCinf,pred extrapolation, dose-aware)",
-                 desc="AUCdn T1 to T2 (AUCinf,pred extrap)",
+                 desc="AUC T1 to T2, dose-aware (AUCinf,pred)",
                  formalsmap=list(conc="conc.group", time="time.group", time.dose="time.dose.group"),
                  depends=c("lambda.z", "clast.pred"),
                  pptestcd_cdisc="AUCINTPD",
@@ -416,7 +416,7 @@ add.interval.col("aumcint.last.dose",
                  values=c(FALSE, TRUE),
                  unit_type="aumc",
                  pretty_name="AUMCint (based on AUMClast extrapolation, dose-aware)",
-                 desc="AUMCdn T1 to T2 (zero extrap)",
+                 desc="AUMC T1 to T2, dose-aware (zero extrap)",
                  formalsmap=list(conc="conc.group", time="time.group", time.dose="time.dose.group"))
 
 # aumcint.all (without dose awareness)
@@ -434,7 +434,7 @@ add.interval.col("aumcint.all.dose",
                  values=c(FALSE, TRUE),
                  unit_type="aumc",
                  pretty_name="AUMCint (based on AUMCall extrapolation, dose-aware)",
-                 desc="AUMCdn T1 to T2 (AUMCall extrap)",
+                 desc="AUMC T1 to T2, dose-aware (AUMCall)",
                  formalsmap=list(conc="conc.group", time="time.group", time.dose="time.dose.group"))
 
 # aumcint.inf.obs (without dose awareness)
@@ -453,7 +453,7 @@ add.interval.col("aumcint.inf.obs.dose",
                  values=c(FALSE, TRUE),
                  unit_type="aumc",
                  pretty_name="AUMCint (based on AUMCinf,obs extrapolation, dose-aware)",
-                 desc="AUMCdn T1 to T2 (AUMCinf,obs extrap)",
+                 desc="AUMC T1 to T2, dose-aware (AUMCinf,obs)",
                  formalsmap=list(conc="conc.group", time="time.group", time.dose="time.dose.group"),
                  depends=c("lambda.z", "clast.obs"))
 
@@ -473,7 +473,7 @@ add.interval.col("aumcint.inf.pred.dose",
                  values=c(FALSE, TRUE),
                  unit_type="aumc",
                  pretty_name="AUMCint (based on AUMCinf,pred extrapolation, dose-aware)",
-                 desc="AUMCdn T1 to T2 (AUMCinf,pred extrap)",
+                 desc="AUMC T1 to T2, dose-aware (AUMCinf,pred)",
                  formalsmap=list(conc="conc.group", time="time.group", time.dose="time.dose.group"),
                  depends=c("lambda.z", "clast.pred"))
 

diff --git a/R/half.life.R b/R/half.life.R
@@ -757,7 +757,7 @@ add.interval.col("span.ratio",
                  values=c(FALSE, TRUE),
                  unit_type="fraction",
                  pretty_name="Span ratio",
-                 desc="Half-life to calculation duration ratio",
+                 desc="Lambda z time span to half-life ratio",
                  depends="half.life",
                  pptestcd_cdisc="LAMZSPN",
                  pptest_cdisc="Lambda z Span")

diff --git a/tests/testthat/test-PKNCA.options.R b/tests/testthat/test-PKNCA.options.R
@@ -481,3 +481,9 @@ test_that("PKNCA.options fails when setting defaults and another option simultan
   )
 })
 
+
+test_that("adj.r.squared.factor description matches the selection rule in the code (#582)", {
+  desc <- PKNCA.options.describe("adj.r.squared.factor")
+  expect_match(desc, "within adj.r.squared.factor of the best", fixed = TRUE)
+  expect_match(desc, "regression using the most data points is selected", fixed = TRUE)
+})
diff --git a/tests/testthat/test-aucint.R b/tests/testthat/test-aucint.R
@@ -738,3 +738,26 @@ test_that("Integration functions are passed correctly through wrapper", {
   expect_true(is.numeric(auc_result) && auc_result > 0)
   expect_true(is.numeric(aumc_result) && aumc_result > 0)
 })
+
+test_that("the *int.inf.* descriptions name the AUCinf extrapolation they use (#582)", {
+  cols <- get.interval.cols()
+  auc_inf <- grep("^aucint[.]inf[.]", names(cols), value = TRUE)
+  aumc_inf <- grep("^aumcint[.]inf[.]", names(cols), value = TRUE)
+  expect_equal(length(auc_inf), 4)
+  expect_equal(length(aumc_inf), 4)
+  auc_desc <- vapply(cols[auc_inf], FUN = function(x) x$desc, FUN.VALUE = character(1))
+  aumc_desc <- vapply(cols[aumc_inf], FUN = function(x) x$desc, FUN.VALUE = character(1))
+  expect_true(all(grepl("AUCinf,", auc_desc, fixed = TRUE)))
+  expect_true(all(grepl("AUMCinf,", aumc_desc, fixed = TRUE)))
+})
+
+test_that("dose-aware interval parameters are not described as dose-normalized (#582)", {
+  cols <- get.interval.cols()
+  dose_aware <- grep("int[.].*[.]dose$", names(cols), value = TRUE)
+  expect_equal(length(dose_aware), 8)
+  descs <- vapply(cols[dose_aware], FUN = function(x) x$desc, FUN.VALUE = character(1))
+  # "dn" is the abbreviation for dose normalization (auclast.dn and friends);
+  # these parameters use dose-aware interpolation instead.
+  expect_equal(unname(descs[grepl("dn", descs, fixed = TRUE)]), character(0))
+  expect_true(all(grepl("dose-aware", descs, fixed = TRUE)))
+})
diff --git a/tests/testthat/test-half.life.R b/tests/testthat/test-half.life.R
@@ -996,3 +996,8 @@ test_that("pk.calc.half.life tobit manually.selected.points sets exclude for neg
     "Negative half-life estimated with manually-selected points"
   )
 })
+
+test_that("span.ratio is described as span over half-life, not the inverse (#582)", {
+  # ret$span.ratio <- (max(data$time) - min(data$time))/ret$half.life
+  expect_equal(get.interval.cols()[["span.ratio"]]$desc, "Lambda z time span to half-life ratio")
+})