Fix inverse predictions for replicate measurements

For details, see NEWS.md

1 files changed, 12 insertions, 10 deletions

diff --git a/tests/testthat/test_massart.R b/tests/testthat/test_massart.R
index 791c2e7..6e4ce75 100644
--- a/tests/testthat/test_massart.R
+++ b/tests/testthat/test_massart.R
@@ -19,22 +19,24 @@ test_that("Inverse predictions for example 1 are correct",{
   expect_equal(round(p1.3$Confidence, 1), 3.2)
 })
 
+test_that("Inverse predictions for example data 3 are correct when regressing on means",{
+  weights <- with(massart97ex3, {
+    yx <- split(y, x)
+    ybar <- sapply(yx, mean)
+    s <- round(sapply(yx, sd), digits = 2)
+    w <- round(1 / (s^2), digits = 3)
+  })
 
-test_that("Inverse predictions for example 3 are correct",{
-  attach(massart97ex3)
-  yx <- split(y, x)
-  ybar <- sapply(yx, mean)
-  s <- round(sapply(yx, sd), digits = 2)
-  w <- round(1 / (s^2), digits = 3)
-  weights <- w[factor(x)]
-  m3 <- lm(y ~ x, w = weights)
+  massart97ex3.means <- aggregate(y ~ x, massart97ex3, mean)
+
+  m3.means <- lm(y ~ x, w = weights, data = massart97ex3.means)
 
   # Known values are from the book
-  p3.1 <- inverse.predict(m3, 15, ws = 1.67)
+  p3.1 <- inverse.predict(m3.means, 15, ws = 1.67)
   expect_equal(round(p3.1$Prediction, 1), 5.9)
   expect_equal(round(p3.1$Confidence, 1), 2.5)
 
-  p3.2 <- inverse.predict(m3, 90, ws = 0.145)
+  p3.2 <- inverse.predict(m3.means, 90, ws = 0.145)
   expect_equal(round(p3.2$Prediction, 1), 44.1)
   expect_equal(round(p3.2$Confidence, 1), 7.9)
 })