50 lines
1.5 KiB
R
50 lines
1.5 KiB
R
|
##############################################################################
|
||
|
|
#
|
||
|
|
# Purpose:
|
||
|
|
# Use pilot project data to calculate power of a full study through simulation
|
||
|
|
#
|
||
|
|
# Parts:
|
||
|
|
# (0) - Setup
|
||
|
|
# (1) - Get the pilot data and clean it
|
||
|
|
# (2) - Run the model on the pilot data and extract effects
|
||
|
|
# (3) - Set up and run the simulation
|
||
|
|
# ====> Set variables at the arrows <====
|
||
|
|
#
|
||
|
|
##############################################################################
|
||
|
|
rm(list=ls())
|
||
|
|
set.seed(424242)
|
||
|
|
|
||
|
|
# (1) - Get the pilot data and clean it
|
||
|
|
source('~/Research/tor_wikipedia_edits/handcoded_edits/inter_coder_reliability_ns0.R')
|
||
|
|
d$nd <- to_logical(d$not.damaging, custom_true=c("Y"))
|
||
|
|
levels(d$source) <- c("IP-based Editors", "New Editors", "Registered Editors", "Tor-based Editors")
|
||
|
|
|
||
|
|
# (2) - Run the model on the pilot data
|
||
|
|
pilotM <- glm(nd ~ source, family=binomial(link="logit"), data=d)
|
||
|
|
summary(pilotM) #we expect effect sizes on this order
|
||
|
|
|
||
|
|
pilot.b0 <- coef(summary(pilotM))[1,1]
|
||
|
|
pilot.b1 <- coef(summary(pilotM))[2,1]
|
||
|
|
pilot.b2 <- coef(summary(pilotM))[3,1]
|
||
|
|
pilot.b3 <- coef(summary(pilotM))[4,1]
|
||
|
|
|
||
|
|
|
||
|
|
# (3) - Set up and run the simulation
|
||
|
|
|
||
|
|
source('powerAnalysis.R') #my little "lib"
|
||
|
|
|
||
|
|
#====>
|
||
|
|
nSims <- 5000 #how many simulations to run
|
||
|
|
n <- 100 #a guess for necessary sample size (per group)
|
||
|
|
#makeData(10) #DEBUGGING CODE -- you can uncomment this if you want to see it work
|
||
|
|
#<====
|
||
|
|
|
||
|
|
print("Levels are:")
|
||
|
|
print(levels(d$source))
|
||
|
|
powerCheck(n, nSims)
|
||
|
|
|
||
|
|
#Sample values
|
||
|
|
powerCheck(50, 100)
|
||
|
|
powerCheck(80, 1000)
|
||
|
|
powerCheck(200, 5000)
|