From 140b1f202b0a05c4bff885edd13a846ac376852a Mon Sep 17 00:00:00 2001
From: rpsychologist <1629860+rpsychologist@users.noreply.github.com>
Date: Wed, 18 Apr 2018 15:13:17 +0200
Subject: [PATCH] fix #10

---
 NEWS.md                           |  7 +++++++
 R/simulate.R                      |  2 +-
 tests/testthat/tests.simulation.R | 10 ++++++++++
 3 files changed, 18 insertions(+), 1 deletion(-)

diff --git a/NEWS.md b/NEWS.md
index e453a37..db79a60 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,4 +1,11 @@
 
+# Changes in version 0.3.9000
+
+
+## Bug fixes
+* `summary.plcp_sim()` now show fixed effect `theta`s in the correct order, thanks to
+GitHub user Johnzav888 (#10).
+
 # Changes in version 0.3.0
 
 ## New features
diff --git a/R/simulate.R b/R/simulate.R
index 658c39d..ad74a13 100644
--- a/R/simulate.R
+++ b/R/simulate.R
@@ -1064,7 +1064,7 @@ summarize_FE <- function(res, theta, alpha) {
         pvals_bw <- get_p_val_df(t = estimate/se,
                                  df = df_bw,
                                  parameter = para)
-        theta_i <- theta[[i]]
+        theta_i <- theta[[para]]
         tmp[[i]] <- data.frame(
                     parameter = para,
                     M_est = mean(estimate),
diff --git a/tests/testthat/tests.simulation.R b/tests/testthat/tests.simulation.R
index 5b6621e..3c78367 100644
--- a/tests/testthat/tests.simulation.R
+++ b/tests/testthat/tests.simulation.R
@@ -86,6 +86,9 @@ test_that("extract results", {
 
 test_that("simulation summary", {
 
+    p <- update(p, fixed_intercept = 4.4,
+                   fixed_slope = -0.22)
+
     set.seed(5446)
     formula <- list("correct" = "y ~ treatment * time + (1 + time | subject) +
                     (0 + time | cluster)")
@@ -93,6 +96,13 @@ test_that("simulation summary", {
                     progress = FALSE)
     tmp <- summary(res)
 
+    # params
+    x <- as.character(tmp$summary$correct$FE$parameter)
+    expect_equal(x, c("(Intercept)", "treatment", "time", "time:treatment"))
+
+    # theta
+    expect_equal(tmp$summary$correct$FE$theta, c(4.4, 0, -0.22, 0.1131371), tolerance = 0.00001)
+
     # Est
     est <- c(res$res$correct$FE[c(4,8,12), "estimate"])
     y <- mean(est)