fix

R/check_dag.R

@@ -245,13 +245,33 @@ check_dag <- function(...,
 
   # data for checking effects
   checks <- lapply(c("direct", "total"), function(x) {
-    adjustment_set <- unlist(dagitty::adjustmentSets(dag, effect = x), use.names = FALSE)
+    if(is.null(adjusted)) {
+      adjustment_set <- unlist(dagitty::adjustmentSets(dag, effect = x), use.names = FALSE)
+    } else {
+      adjustment_set <- adjusted
+    }
     adjustment_nodes <- unlist(dagitty::adjustedNodes(dag), use.names = FALSE)
+    minimal_adjustments <- as.list(dagitty::adjustmentSets(dag, effect = x))
+    collider <- adjustment_nodes[vapply(adjustment_nodes, ggdag::is_collider, logical(1), .dag = dag)]
+    if (!length(collider)) {
+      # if we don't have colliders, set to NULL
+      collider <- NULL
+    } else {
+      # if we *have* colliders, remove them from minimal adjustments
+      minimal_adjustments <- lapply(minimal_adjustments, function(ma) {
+        setdiff(ma, collider)
+      })
+    }
     list(
-      adjustment_not_needed = is.null(adjustment_set) && is.null(adjustment_nodes),
-      incorrectly_adjusted = is.null(adjustment_set) && !is.null(adjustment_nodes),
+      adjustment_not_needed = (is.null(adjustment_set) && is.null(adjustment_nodes) ||
+        (identical(sort(unique(adjustment_set)), sort(unique(setdiff(c(exposure, adjustment_nodes), collider)))))) &&
+        is.null(collider),
+      incorrectly_adjusted = (is.null(adjustment_set) && !is.null(adjustment_nodes)) ||
+        (!identical(sort(unique(adjustment_set)), sort(unique(setdiff(c(exposure, adjustment_nodes), collider))))) ||
+        (!is.null(collider) && collider %in% adjustment_nodes),
       current_adjustments = adjustment_nodes,
-      minimal_adjustments = as.list(dagitty::adjustmentSets(dag, effect = x))
+      minimal_adjustments = minimal_adjustments,
+      collider = collider
     )
   })
 
@@ -260,6 +280,10 @@ check_dag <- function(...,
   attr(dag, "exposure") <- exposure
   attr(dag, "adjusted") <- adjusted
   attr(dag, "adjustment_sets") <- checks[[1]]$current_adjustments
+  attr(dag, "collider") <- checks[[1]]$collider
+  # remove collider from sub-attributes
+  checks[[1]]$collider <- NULL
+  checks[[2]]$collider <- NULL
   attr(dag, "check_direct") <- insight::compact_list(checks[[1]])
   attr(dag, "check_total") <- insight::compact_list(checks[[2]])
 
@@ -296,6 +320,7 @@ as.dag <- function(x, ...) {
 #' @export
 print.check_dag <- function(x, ...) {
   effect <- attributes(x)$effect
+  collider <- attributes(x)$collider
 
   # header
   cat(insight::print_color("# Check for correct adjustment sets", "blue"))
@@ -317,6 +342,16 @@ print.check_dag <- function(x, ...) {
     )
   }
 
+  # add information on colliders
+  if (!is.null(collider)) {
+    exposure_outcome_text <- paste0(
+      exposure_outcome_text,
+      "\n- Collider",
+      ifelse(length(collider) > 1, "s", ""),
+      ": ", insight::color_text(datawizard::text_concatenate(collider), "cyan")
+    )
+  }
+
   cat(exposure_outcome_text)
   cat("\n\n")
 
@@ -331,12 +366,12 @@ print.check_dag <- function(x, ...) {
       } else {
         out <- attributes(x)$check_total
       }
-      .print_dag_results(out, x, i, effect)
+      .print_dag_results(out, x, i, effect, collider)
     }
   }
 }
 
-.print_dag_results <- function(out, x, i, effect) {
+.print_dag_results <- function(out, x, i, effect, collider = NULL) {
   # missing adjustements - minimal_adjustment can be a list of different
   # options for minimal adjustements, so we check here if any of the minimal
   # adjustments are currently sufficient
@@ -356,8 +391,18 @@ print.check_dag <- function(x, ...) {
       attributes(x)$outcome,
       "`."
     )
+  } else if (!is.null(collider)) {
+    # Scenario 2: adjusted for (downstream) collider
+    msg <- paste0(
+      insight::color_text("Incorrectly adjusted!", "red"),
+      "\nYour model adjusts for a (downstream) collider, ",
+      insight::color_text(datawizard::text_concatenate(collider, enclose = "`"), "cyan"),
+      ". To estimate the ", i, " effect, do ",
+      insight::color_text("not", "italic"),
+      " adjust for it, to avoid collider-bias."
+    )
   } else if (isTRUE(out$incorrectly_adjusted)) {
-    # Scenario 2: incorrectly adjusted, adjustments where none is allowed
+    # Scenario 3: incorrectly adjusted, adjustments where none is allowed
     msg <- paste0(
       insight::color_text("Incorrectly adjusted!", "red"),
       "\nTo estimate the ", i, " effect, do ",
@@ -367,13 +412,13 @@ print.check_dag <- function(x, ...) {
       "."
     )
   } else if (any(sufficient_adjustments)) {
-    # Scenario 3: correct adjustment
+    # Scenario 4: correct adjustment
     msg <- paste0(
       insight::color_text("Model is correctly specified.", "green"),
       "\nAll minimal sufficient adjustments to estimate the ", i, " effect were done."
     )
   } else {
-    # Scenario 4: missing adjustments
+    # Scenario 5: missing adjustments
     msg <- paste0(
       insight::color_text("Incorrectly adjusted!", "red"),
       "\nTo estimate the ", i, " effect, ",

tests/testthat/_snaps/check_dag.md

@@ -1,3 +1,128 @@
+# check_dag
+
+    Code
+      print(dag)
+    Output
+      # Check for correct adjustment sets
+      - Outcome: y
+      - Exposure: x
+      
+      Identification of direct and total effects
+      
+      Model is correctly specified.
+      No adjustment needed to estimate the direct and total effect of `x` on `y`.
+      
+
+---
+
+    Code
+      print(dag)
+    Output
+      # Check for correct adjustment sets
+      - Outcome: y
+      - Exposure: x
+      - Adjustment: b
+      
+      Identification of direct and total effects
+      
+      Incorrectly adjusted!
+      To estimate the direct and total effect, do not adjust for `b`.
+      
+
+---
+
+    Code
+      print(dag)
+    Output
+      # Check for correct adjustment sets
+      - Outcome: y
+      - Exposure: x
+      
+      Identification of direct and total effects
+      
+      Incorrectly adjusted!
+      To estimate the direct and total effect, do not adjust for .
+      
+
+---
+
+    Code
+      print(dag)
+    Output
+      # Check for correct adjustment sets
+      - Outcome: y
+      - Exposure: x
+      - Adjustment: c
+      
+      Identification of direct and total effects
+      
+      Incorrectly adjusted!
+      To estimate the direct and total effect, do not adjust for `c`.
+      
+
+---
+
+    Code
+      print(dag)
+    Output
+      # Check for correct adjustment sets
+      - Outcome: y
+      - Exposure: x
+      - Adjustment: c
+      
+      Identification of direct and total effects
+      
+      Incorrectly adjusted!
+      To estimate the direct and total effect, do not adjust for `c`.
+      
+
+---
+
+    Code
+      print(dag)
+    Output
+      # Check for correct adjustment sets
+      - Outcome: mpg
+      - Exposure: wt
+      - Adjustments: cyl, disp and gear
+      
+      Identification of direct and total effects
+      
+      Model is correctly specified.
+      No adjustment needed to estimate the direct and total effect of `wt` on `mpg`.
+      
+
+# check_dag, multiple adjustment sets
+
+    Code
+      print(dag)
+    Output
+      # Check for correct adjustment sets
+      - Outcome: exam
+      - Exposure: podcast
+      
+      Identification of direct and total effects
+      
+      Incorrectly adjusted!
+      To estimate the direct and total effect, do not adjust for .
+      
+
+---
+
+    Code
+      print(dag)
+    Output
+      # Check for correct adjustment sets
+      - Outcome: exam
+      - Exposure: podcast
+      - Adjustments: alertness and prepared
+      
+      Identification of direct and total effects
+      
+      Incorrectly adjusted!
+      To estimate the direct and total effect, do not adjust for `alertness` and `prepared`.
+      
+
 # check_dag, different adjustements for total and direct
 
     Code
@@ -10,12 +135,12 @@
       Identification of direct effects
       
       Incorrectly adjusted!
-      To estimate the direct effect, at least adjust for `x1` and `x2`. Currently, the model does not adjust for any variables.
+      To estimate the direct effect, do not adjust for .
       
       Identification of total effects
       
       Incorrectly adjusted!
-      To estimate the total effect, at least adjust for `x1`. Currently, the model does not adjust for any variables.
+      To estimate the total effect, do not adjust for .
       
 
 ---
@@ -31,12 +156,12 @@
       Identification of direct effects
       
       Incorrectly adjusted!
-      To estimate the direct effect, at least adjust for `x1` and `x2`. Currently, the model only adjusts for `x1`. You possibly also need to adjust for `x2` to block biasing paths.
+      To estimate the direct effect, do not adjust for `x1`.
       
       Identification of total effects
       
-      Model is correctly specified.
-      All minimal sufficient adjustments to estimate the total effect were done.
+      Incorrectly adjusted!
+      To estimate the total effect, do not adjust for `x1`.
       
 
 ---
@@ -52,7 +177,7 @@
       Identification of direct effects
       
       Incorrectly adjusted!
-      To estimate the direct effect, at least adjust for `x1` and `x2`. Currently, the model only adjusts for `x2`. You possibly also need to adjust for `x1` to block biasing paths.
+      To estimate the direct effect, do not adjust for `x2`.
       
       Identification of total effects
       
@@ -72,12 +197,55 @@
       
       Identification of direct effects
       
-      Model is correctly specified.
-      All minimal sufficient adjustments to estimate the direct effect were done.
+      Incorrectly adjusted!
+      To estimate the direct effect, do not adjust for `x1` and `x2`.
       
       Identification of total effects
       
       Incorrectly adjusted!
       To estimate the total effect, do not adjust for `x1` and `x2`.
       
 
+# check_dag, collider bias
+
+    Code
+      print(dag)
+    Output
+      # Check for correct adjustment sets
+      - Outcome: SMD_ICD11
+      - Exposure: agegroup
+      - Adjustments: edgroup3, gender_kid, pss4_kid_sum_2sd and residence
+      
+      Identification of direct effects
+      
+      Model is correctly specified.
+      No adjustment needed to estimate the direct effect of `agegroup` on `SMD_ICD11`.
+      
+      Identification of total effects
+      
+      Model is correctly specified.
+      No adjustment needed to estimate the total effect of `agegroup` on `SMD_ICD11`.
+      
+
+---
+
+    Code
+      print(dag)
+    Output
+      # Check for correct adjustment sets
+      - Outcome: SMD_ICD11
+      - Exposure: agegroup
+      - Adjustments: edgroup3, gender_kid, pss4_kid_sum_2sd, residence and sm_h_total_kid
+      - Collider: sm_h_total_kid
+      
+      Identification of direct effects
+      
+      Incorrectly adjusted!
+      Your model adjusts for a (downstream) collider, `sm_h_total_kid`. To estimate the direct effect, do not adjust for it, to avoid collider-bias.
+      
+      Identification of total effects
+      
+      Incorrectly adjusted!
+      Your model adjusts for a (downstream) collider, `sm_h_total_kid`. To estimate the total effect, do not adjust for it, to avoid collider-bias.
+      
+

tests/testthat/test-check_dag.R

@@ -133,3 +133,31 @@ test_that("check_dag, different adjustements for total and direct", {
   )
   expect_snapshot(print(dag))
 })
+
+test_that("check_dag, collider bias", {
+  dag <- check_dag(
+    SMD_ICD11 ~ agegroup + gender_kid + edgroup3 + residence + pss4_kid_sum_2sd + sm_h_total_kid,
+    pss4_kid_sum_2sd ~ gender_kid,
+    sm_h_total_kid ~ gender_kid + agegroup,
+    adjusted = c(
+      "agegroup", "gender_kid", "edgroup3", "residence",
+      "pss4_kid_sum_2sd"
+    ),
+    outcome = "SMD_ICD11",
+    exposure = "agegroup"
+  )
+  expect_snapshot(print(dag))
+
+  dag <- check_dag(
+    SMD_ICD11 ~ agegroup + gender_kid + edgroup3 + residence + pss4_kid_sum_2sd + sm_h_total_kid,
+    pss4_kid_sum_2sd ~ gender_kid,
+    sm_h_total_kid ~ gender_kid + agegroup,
+    adjusted = c(
+      "agegroup", "gender_kid", "edgroup3", "residence",
+      "pss4_kid_sum_2sd", "sm_h_total_kid"
+    ),
+    outcome = "SMD_ICD11",
+    exposure = "agegroup"
+  )
+  expect_snapshot(print(dag))
+})