Fix incorrect calculation of Pearson's r

Previously, bootES calculated Pearson's r incorrectly if the
`contrasts` argument to `bootES` was not lexicographically sorted.
The error arose from a bug in the reordering of the `lambdas` at
line 39 in `pearsonsr.R`.

R/pearsonsr.R

@@ -18,7 +18,7 @@ calcPearsonsR <- function(vals, freq, grps, lambdas) {
   ##   This function is meant to be passed as the 'statistic' argument
   ##   to the 'boot' function. 'freq' should be a frequency vector of
   ##   the type returned by 'boot'
-  
+
   ## Get the integer indices of the different groups.
   grp.idx = split(seq_along(vals), grps, drop=TRUE)   
   grp.nms = names(grp.idx)
@@ -36,7 +36,7 @@ calcPearsonsR <- function(vals, freq, grps, lambdas) {
   }
 
   ## Put means and lambdas in the same order
-  lambdas = lambdas[match(names(lambdas), grp.nms)]
+  lambdas = lambdas[grp.nms]
   C       = sum(lambdas * means) # contrast
   sumWts  = sum(lambdas^2 / ns) # sum of the weights
   SSw     = sum(ss)

tests/testthat/test_calcPearsonsR.R

@@ -24,3 +24,25 @@ test_that("calcPearsonsR produces known result", {
   r.res = bootES:::calcPearsonsR(threeGpsVec, freq=rep(1, length(threeGpsVec)), grps=grpLabels3, lambdas=lambdas3)
   expect_equal(truth, r.res, tolerance=1e-4)
 })
+
+test_that("produces same result with non-lexicographic contrast sorting", {
+  dat = data.frame(cond=rep(c("A", "B", "C"), each=10), score=1:30)
+
+  truth = 0.926
+  res_1 = bootES(
+    dat, data.col="score", group.col="cond", contrast=c(A=-1, B=0.5, C=0.5),
+    effect.type="r")$t0
+  expect_equal(truth, res_1, tolerance=1e-3)
+
+
+  res_2 = bootES(
+    dat, data.col="score", group.col="cond", contrast=c(B=0.5, C=0.5, A=-1),
+    effect.type="r")$t0
+  expect_equal(truth, res_2, tolerance=1e-3)
+
+
+  res_3 = bootES(
+    dat, data.col="score", group.col="cond", contrast=c(C=0.5, A=-1, B=0.5),
+    effect.type="r")$t0
+  expect_equal(truth, res_3, tolerance=1e-3)
+})