nfultz recs

R/estimatr_difference_in_means.R

@@ -240,8 +240,7 @@ difference_in_means <-
     data$cluster <- model_data$cluster
     # rescale weights for convenience
     if (is.numeric(model_data$weights)) {
-      weight_mean <- mean(model_data$weights)
-      data$weights <- model_data$weights / weight_mean
+      data$weights <- model_data$weights / mean(model_data$weights)
     }
     data$block <- model_data$block
 

R/estimatr_lm_lin.R

@@ -265,15 +265,10 @@ lm_lin <- function(formula,
   if (is.numeric(weights)) {
     center <- apply(demeaned_covars, 2, weighted.mean, weights)
   } else {
-    center <- TRUE
+    center <- colMeans(demeaned_covars)
   }
 
-  demeaned_covars <-
-    scale(
-      demeaned_covars,
-      center = center,
-      scale = FALSE
-    )
+  demeaned_covars <- sweep(demeaned_covars, 2, center)
 
   original_covar_names <- colnames(demeaned_covars)
 
@@ -349,7 +344,7 @@ lm_lin <- function(formula,
     formula = formula
   )
 
-  return_list[["scaled_center"]] <- attr(demeaned_covars, "scaled:center")
+  return_list[["scaled_center"]] <- center
   setNames(return_list[["scaled_center"]], original_covar_names)
 
   return_list[["call"]] <- match.call()

tests/testthat/test-lm-lin.R

@@ -312,7 +312,7 @@ test_that("Test LM Lin", {
   )
 })
 
-test_that("lm_lin weights appropriately", {
+test_that("lm_lin same as sampling perspective", {
 
   # Unweighted matches sampling view
   lmo <- lm_lin(mpg ~ am, ~ hp, data = mtcars)
@@ -329,6 +329,9 @@ test_that("lm_lin weights appropriately", {
     ate,
     lmo$coefficients["am"]
   )
+})
+
+test_that("weighted lm_lin same as with one covar sampling view", {
 
   # Weighted matches (one covar)
   lmwo <- lm_lin(mpg ~ am, ~ hp, weights = wt, data = mtcars)
@@ -345,6 +348,9 @@ test_that("lm_lin weights appropriately", {
     wate,
     lmwo$coefficients["am"]
   )
+})
+
+test_that("weighted lm_lin same as with two covar sampling view", {
 
   # Weighted matches (two covars)
   lmw2o <- lm_lin(mpg ~ am, ~ hp + cyl, weights = wt, data = mtcars)