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diff --git a/tests/testthat/test_massart.R b/tests/testthat/test_massart.R
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+context("Known results for the example datasets provided by Massart (1997)")
+
+require(chemCal)
+
+test_that("Inverse predictions for example 1 are correct",{
+  m1 <- lm(y ~ x, data = massart97ex1)
+
+  # Known values are from the book
+  p1.1 <- inverse.predict(m1, 15)
+  expect_equal(round(p1.1$Prediction, 1), 6.1)
+  expect_equal(round(p1.1$Confidence, 1), 4.9)
+
+  p1.2 <- inverse.predict(m1, 90)
+  expect_equal(round(p1.2$Prediction, 1), 43.9)
+  expect_equal(round(p1.2$Confidence, 1), 4.9)
+
+  p1.3 <- inverse.predict(m1, rep(90, 5))
+  expect_equal(round(p1.3$Prediction, 1), 43.9)
+  expect_equal(round(p1.3$Confidence, 1), 3.2)
+})
+
+
+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)
+
+  # Known values are from the book
+  p3.1 <- inverse.predict(m3, 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)
+  expect_equal(round(p3.2$Prediction, 1), 44.1)
+  expect_equal(round(p3.2$Confidence, 1), 7.9)
+})