format

Author: malcolmbarrett

R/bal_prognostic_score.R

@@ -280,15 +280,15 @@ bal_prognostic_fit_model <- function(
         data = control_data,
         family = family
       )
-      
+
       # Add weights if provided
       if (!is.null(.weights)) {
         glm_args$weights <- .weights
       }
-      
+
       # Add any additional arguments
       glm_args <- c(glm_args, list(...))
-      
+
       # Use do.call to bypass non-standard evaluation
       do.call(stats::glm, glm_args)
     },

R/geom_qq2.R

@@ -29,8 +29,8 @@
 #' @inheritParams ggplot2_params
 #' @param quantiles Numeric vector of quantiles to compute. Default is
 #'   `seq(0.01, 0.99, 0.01)` for 99 quantiles.
-#' @param .reference_level The reference treatment level to use for comparisons. 
-#'   If `NULL` (default), uses the first level for factors or the minimum value 
+#' @param .reference_level The reference treatment level to use for comparisons.
+#'   If `NULL` (default), uses the first level for factors or the minimum value
 #'   for numeric variables.
 #'
 #' @return A ggplot2 layer.

tests/testthat/test-check_ess.R

@@ -44,15 +44,24 @@ test_that("check_ess works with binary groups", {
 })
 
 test_that("check_ess works with categorical groups", {
-  result <- check_ess(nhefs_weights, .weights = w_cat_ate, .group = alcoholfreq_cat)
+  result <- check_ess(
+    nhefs_weights,
+    .weights = w_cat_ate,
+    .group = alcoholfreq_cat
+  )
 
   expect_s3_class(result, "tbl_df")
   expect_true("group" %in% names(result))
   expect_true(length(unique(result$group)) > 2)
 })
 
 test_that("check_ess works with continuous groups", {
-  result <- check_ess(nhefs_weights, .weights = w_ate, .group = age, n_tiles = 4)
+  result <- check_ess(
+    nhefs_weights,
+    .weights = w_ate,
+    .group = age,
+    n_tiles = 4
+  )
 
   expect_s3_class(result, "tbl_df")
   expect_true("group" %in% names(result))
@@ -123,7 +132,11 @@ test_that("ESS calculation is correct", {
     wts2 = c(4, 0, 0, 0) # All weight on one obs -> ESS = 1
   )
 
-  result <- check_ess(test_df, .weights = c(wts, wts2), include_observed = FALSE)
+  result <- check_ess(
+    test_df,
+    .weights = c(wts, wts2),
+    include_observed = FALSE
+  )
 
   expect_equal(result$ess[result$method == "wts"], 4)
   expect_equal(result$ess[result$method == "wts2"], 1)

tests/testthat/test-compute_balance.R

@@ -114,7 +114,11 @@ test_that("bal_smd handles missing values", {
   w_na <- data$w_uniform
 
   # Should return NA when na.rm = FALSE
-  expect_true(is.na(bal_smd(.covariate = x_na, .exposure = g_na, na.rm = FALSE)))
+  expect_true(is.na(bal_smd(
+    .covariate = x_na,
+    .exposure = g_na,
+    na.rm = FALSE
+  )))
 
   # Should work when na.rm = TRUE
   smd_na.rm <- bal_smd(.covariate = x_na, .exposure = g_na, na.rm = TRUE)
@@ -612,7 +616,10 @@ test_that("functions handle unbalanced groups", {
 
   # Test with very unbalanced groups
   expect_no_error({
-    smd_unbal <- bal_smd(.covariate = data$x_cont, .exposure = data$g_unbalanced)
+    smd_unbal <- bal_smd(
+      .covariate = data$x_cont,
+      .exposure = data$g_unbalanced
+    )
     vr_unbal <- bal_vr(
       .covariate = data$x_cont,
       .exposure = data$g_unbalanced

tests/testthat/test-geom_roc.R

@@ -36,7 +36,10 @@ test_that("geom_roc and stat_roc work", {
   expect_no_error(ggplot_build(p_stat))
 
   # Test with .focal_level parameter
-  p_treatment <- ggplot(nhefs_weights, aes(estimate = .fitted, exposure = qsmk)) +
+  p_treatment <- ggplot(
+    nhefs_weights,
+    aes(estimate = .fitted, exposure = qsmk)
+  ) +
     geom_roc(.focal_level = "1")
   expect_s3_class(p_treatment, "gg")
   expect_no_error(ggplot_build(p_treatment))

tests/testthat/test-plot_ess.R

@@ -59,7 +59,11 @@ test_that("plot_ess includes reference line", {
 
 test_that("plot_ess labels work correctly", {
   p_with_labels <- plot_ess(nhefs_weights, .weights = w_ate, show_labels = TRUE)
-  p_without_labels <- plot_ess(nhefs_weights, .weights = w_ate, show_labels = FALSE)
+  p_without_labels <- plot_ess(
+    nhefs_weights,
+    .weights = w_ate,
+    show_labels = FALSE
+  )
 
   # Check for text layer
   text_layer_with <- sapply(

tests/testthat/test-plot_qq.R

@@ -31,7 +31,13 @@ test_that("plot_qq works with multiple weights", {
 })
 
 test_that("plot_qq works without observed", {
-  p <- plot_qq(nhefs_weights, age, qsmk, .weights = w_ate, include_observed = FALSE)
+  p <- plot_qq(
+    nhefs_weights,
+    age,
+    qsmk,
+    .weights = w_ate,
+    include_observed = FALSE
+  )
 
   expect_s3_class(p, "ggplot")
 
@@ -137,7 +143,13 @@ test_that("plot_qq visual regression tests", {
   # Without observed
   expect_doppelganger(
     "qq plot no observed",
-    plot_qq(nhefs_weights, age, qsmk, .weights = w_ate, include_observed = FALSE)
+    plot_qq(
+      nhefs_weights,
+      age,
+      qsmk,
+      .weights = w_ate,
+      include_observed = FALSE
+    )
   )
 
   # With propensity score