Fix some typos; rebuild

05_mixed1/exercises-pwrlmm.md

@@ -1,7 +1,7 @@
 Exercise: Power simulation for longitudinal data
 ================
 
-## Risperidone vs. haloperidol and schizophrenia
+## Risperidone vs. haloperidol and schizophrenia \[@Moeller08\]
 
 ``` r
 dat       <- read.table("../data/moeller.csv", header = TRUE, sep = ",")

06_mixed2/exercises.md

@@ -33,7 +33,7 @@ dat$ResponseId <- factor(dat$ResponseId)
       using `lattice::xyplot()`
     - Aggregate the data over Subjects and plot one panel for each rater
     - How would you choose the random effects for a model testing
-      healing over the three conditions
+      healing over the three conditions?
 
 2.  Fit the model you think fits the experimental design best
 
@@ -41,16 +41,16 @@ dat$ResponseId <- factor(dat$ResponseId)
 
 4.  Run a power simulation for a replication study:
 
-    - Set up a data frame containing the study design and sample size.
+    - Set up a data frame containing the study design and sample size
 
-    - Specify the minimum relevant effects.
+    - Specify the minimum relevant effects
 
-    - Set the fixed effects and variance components to plausible values.
+    - Set the fixed effects and variance components to plausible values
 
     - How many participants are required to detect the specified effect
       with a power of 80%?
 
-    - Recover the parameters of the model for one simulated data set.
+    - Recover the parameters of the model for one simulated data set
 
 ### Reference