Fixing logisticCoefs double dot bug

NEWS.md

@@ -1,5 +1,9 @@
 # simstudy (development version)
 
+## Minor fix
+
+* Function `logisticCoefs` now correctly handles double dot notation.
+
 # simstudy 0.7.1
 
 ## Breaking Changes

R/utility.R

@@ -1072,6 +1072,18 @@ logisticCoefs <- function(defCovar, coefs, popPrev, rr = NULL, rd = NULL,
   if (!is.null(rd)) targetStat <- "rd"
   if (!is.null(auc)) targetStat <- "auc"
 
+  # Get any double dot vars from calling environment into this environment
+
+  .formvars <- all.vars(parse(text = defCovar$formula))
+  .dotVars <- .formvars[startsWith(.formvars, "..")]
+  .vars <- gsub("^\\.{2}", "", .dotVars)
+
+  for (i in seq_along(.vars)) {
+    assign(.vars[i], get(.vars[i], envir = parent.frame()))  
+  }
+
+  #
+
   dd <- genData(sampleSize, defCovar)
 
   if (targetStat == "prev") {

tests/testthat/test-generate_data.R

@@ -836,3 +836,53 @@ test_that("genSpline throws errors", {
                           noise.var = .025), regexp = "newrange should be a numeric!")
 })
 
+#logisticCoefs
+
+test_that("logistiCoefs works", {
+
+  skip_on_cran()
+
+  f <- function(n, prevalence, mu_x, coefs_y) {
+
+    defs <- defData(varname = "x", formula = "..mu_x", variance = 1, dist = "normal")
+
+    intercept <- logisticCoefs(defCovar = defs, coefs = coefs_y, popPrev = prevalence)[['B0']]
+
+    defs <- defData(
+      defs,
+      varname = "y",
+      formula = "t(c(..intercept, ..coefs_y)) %*% c(1, x)",
+      dist = "binary", link = "logit")
+
+    genData(n, defs)[, .(x= mean(x), y= mean(y) )]
+
+  }
+
+  p <- rbeta(1, 6, 3)
+  mu_x <- rnorm(1, 5, 1)
+  coefs_y <- c(rnorm(1, 0,.5))
+
+  expect_equal(
+    abs(sum(f(n = 999, prevalence = p, mu_x = mu_x, coefs_y = coefs_y) - c(mu_x, p))),
+    0,
+    tolerance = 0.25
+  )
+
+  defs <- defData(varname = "x", formula = "..mu_x", variance = 1, dist = "normal")
+
+  intercept <- logisticCoefs(defCovar = defs, coefs = coefs_y, popPrev = p)[['B0']]
+
+  defs <- defData(
+    defs,
+    varname = "y",
+    formula = "t(c(..intercept, ..coefs_y)) %*% c(1, x)",
+    dist = "binary", link = "logit")
+
+  expect_equal(
+    abs(sum(genData(n = 999, defs)[, .(x= mean(x), y= mean(y) )] - c(mu_x, p))),
+    0,
+    tolerance = 0.25
+  )
+
+})
+