gistfile1.txt

library(tidyverse)
library(lmerTest)
library(broom)


mu_type1 <- 20
mu_type2 <- 70
sd_both <- 20

pwr <- function(N, mu_type1, mu_type2, sd_both){
  simdata <- data_frame(
      person = 1:N, c1=rnorm(N, mu_type1, sd_both), 
      c2 = rnorm(N, mu_type2, sd_both)
    ) %>% 
    reshape2::melt(id.var="person")
  
  lmer(value~variable+(1|person), data=simdata) %>%  
    tidy %>% 
    mutate(N=N, mu_type1=mu_type1, mu_type2=mu_type2, sd_both=sd_both ) 
}

pwrwrapper <- function(parms){
  parms %>% 
    as.data.frame %>% 
    rowwise() %>% 
    do(pwr(N =.$N, mu_type1=.$mu_type1, mu_type2=.$mu_type2, sd_both=.$sd_both)) %>% 
    filter(term=="variablec2") %>% 
    mutate(sigresult=statistic>1.96)
}


simparms <- expand.grid(N=5:15, mu_type1=25, mu_type2=seq(30,70,5), sd_both=20)
sims <- data_frame(i=1:50) %>% rowwise() %>% do(pwrwrapper(simparms)) 
sims %>% 
  group_by(N, mu_type1, mu_type2) %>% 
  summarise(psigresults=mean(sigresult)) %>% 
  ggplot(aes(mu_type2, psigresults)) + geom_smooth(se=F)+ facet_grid(N~mu_type1)