diff --git a/R/powerAnalysis.R b/R/powerAnalysis.R
index 6bbb903..e4a0ccd 100644
--- a/R/powerAnalysis.R
+++ b/R/powerAnalysis.R
@@ -56,7 +56,8 @@ powerCheck <- function(n, nSims) { #run a power calculation on the dataset given
     simData <- makeDataNew(n)       # make some data
     ## outcome goes here --v
     # e.g. simData$up.fac.mean <- (usefuleffsizeA * mmt) + (usefuleffsizeB * milestones) + rnorm(n=1, mean=0, sd=1) ##plus some noise
-    simData$up.fac.mean <- (-2.075 * simData$mmt) + (0.4284  * simData$milestones) + rnorm(n=1, mean=0, sd=1)
+    #simData$up.fac.mean <- (-2.075 * simData$mmt) + (0.4284  * simData$milestones) + rnorm(n=1, mean=0, sd=1)
+    simData$up.fac.mean <- (0.4284  * simData$milestones) + rnorm(n=1, mean=0, sd=1)
     #have updated for kkex through here, now need to look at the underproduction work
     #m1.sim <- lm(up.fac.mean ~ ((mmt)/ (milestones/age)), data=simData)
     ## could leave age out for now?
@@ -64,13 +65,13 @@ powerCheck <- function(n, nSims) { #run a power calculation on the dataset given
     m1.sim <- lm(up.fac.mean ~ mmt + milestones, data=simData)
     p0 <- coef(summary(m1.sim))[1,4] #intercept
     p1 <- coef(summary(m1.sim))[2,4] #mmt
-    p2 <- coef(summary(m1.sim))[3,4] #milestones
+    #p2 <- coef(summary(m1.sim))[3,4] #milestones
     #p3 <- coef(summary(m1.sim))[4,4] #age
     signif0[s] <- p0 <=.05
     signif1[s] <- p1 <=.05
-    signif2[s] <- p2 <=.05
+    #signif2[s] <- p2 <=.05
     #signif3[s] <- p3 <=.05
-    signifM[s] <- p0 <=.05 & p1 <=.05 & p2 <=.05 #& p3 <=.05
+    signifM[s] <- p0 <=.05 & p1 <=.05 #& p2 <=.05 #& p3 <=.05
   }  
   power <- c(mean(signif0), mean(signif1), mean(signif2), mean(signif3), mean(signifM))
   return(power)