From 863a35ffb868bc27928fb68c96007696d0b9b5c8 Mon Sep 17 00:00:00 2001 From: Matthew Gaughan Date: Thu, 9 Nov 2023 22:19:59 -0600 Subject: [PATCH] inching towards implementing powerAnalysis --- R/EDA.R | 21 ++++ R/calculatePower.R | 6 +- R/justPowerSims.R | 16 ++++ R/powerAnalysis.R | 30 +++--- power_data_110923_mmt.csv | 196 ++++++++++++++++++++++++++++++++++++++ 5 files changed, 253 insertions(+), 16 deletions(-) create mode 100644 R/justPowerSims.R create mode 100644 power_data_110923_mmt.csv diff --git a/R/EDA.R b/R/EDA.R index 67fd2ce..4a6e44f 100644 --- a/R/EDA.R +++ b/R/EDA.R @@ -1,6 +1,7 @@ library(dplyr) df<-read.csv('~/Research/kkex_repo/power_data_110923.csv') +df1 <- read.csv('/data_ext/users/kcz1100/kaylea_dissertation/collabnetXS/raw_data/inst_all_packages_full_results.csv') hist(df$age/365) #there's a big bump at 9 years, why? hist(df$contributors) #skewed @@ -18,3 +19,23 @@ table(df$uses_milestones) #playing around cor.test(df$contributors, as.numeric(df$uses_milestones)) cor.test(df$collaborators, as.numeric(df$uses_milestones)) +cor.test(df$contributors / df$collaborators, df$age / 365) + +t.test(df$age) +#95 percent confidence interval: +# 2793.638 3066.417 +t.test(df$contributors) +#95 percent confidence interval: +# 27.6519 154.6866 +t.test(df$collaborators) +#95 percent confidence interval: +# 50.01884 96.77090 + +t.test(df1$up.fac.mean) +#95 percent confidence interval: +# -0.1961401 -0.1647757 +df$mmt <- (df$contributors + (2 * df$collaborators)) / (df$contributors + df$collaborators) +t.test(df$mmt) +# 95 percent confidence interval: +# 1.610638 1.684438 +# \ No newline at end of file diff --git a/R/calculatePower.R b/R/calculatePower.R index 4e1668f..58371dd 100644 --- a/R/calculatePower.R +++ b/R/calculatePower.R @@ -19,12 +19,14 @@ library(readr) # (1) - Get the pilot data and clean it #source('~/Research/tor_wikipedia_edits/handcoded_edits/inter_coder_reliability_ns0.R') #source ('/data/users/mgaughan/kkex_data_110823_3') -data1 <- read_csv('/data/users/mgaughan/power_data_110923.csv',show_col_types = FALSE) +data1 <- read_csv('../power_data_110923_mmt.csv',show_col_types = FALSE) + #d$nd <- to_logical(d$not.damaging, custom_true=c("Y")) #levels(d$source) <- c("IP-based Editors", "New Editors", "Registered Editors", "Tor-based Editors") # (2) - Run the model on the pilot data -pilotM <- glm(nd ~ source, family=binomial(link="logit"), data=data1) +pilotM <- glm(up_fac_mean ~ ((mmt)/ (milestones/age)), # give the anticipated regression a try + family=gaussian(link='identity'), data=data1) summary(pilotM) #we expect effect sizes on this order pilot.b0 <- coef(summary(pilotM))[1,1] diff --git a/R/justPowerSims.R b/R/justPowerSims.R new file mode 100644 index 0000000..ed0a872 --- /dev/null +++ b/R/justPowerSims.R @@ -0,0 +1,16 @@ +source('powerAnalysis.R') #my little "lib" + +#====> +nSims <- 5000 #how many simulations to run +n <- 100 #a guess for necessary sample size (per group) +#makeData(10) #DEBUGGING CODE -- you can uncomment this if you want to see it work +#<==== + +print("Levels are:") +#print(levels(d$source)) +powerCheck(n, nSims) + +#Sample values +powerCheck(50, 100) +powerCheck(80, 1000) +powerCheck(200, 5000) \ No newline at end of file diff --git a/R/powerAnalysis.R b/R/powerAnalysis.R index 222032b..16b261f 100644 --- a/R/powerAnalysis.R +++ b/R/powerAnalysis.R @@ -14,17 +14,18 @@ l2p <- function(b) { } -makeData <- function(n) { #make a random dataset of size n - #4 group IDs - tDF <- data.frame( - Group0=rbinom(n=n, size=1, prob=l2p(pilot.b0)), #ASK: what about se in pilot data? - Group1=rbinom(n=n, size=1, prob=l2p(pilot.b0 + pilot.b1)), # shouldn't my probs - Group2=rbinom(n=n, size=1, prob=l2p(pilot.b0 + pilot.b2)), # include se? - Group3=rbinom(n=n, size=1, prob=l2p(pilot.b0 + pilot.b3))) - sDF <- melt(tDF, id.vars = 0) #AKA the index is the unique id, as far as that goes - colnames(sDF) <- c('source', 'nd') - - return(sDF) +#Matt: +makeDataNew <- function(n) { + sDF <- data.frame( + sample(2793.638:3066.417, 1, replace = FALSE), + sample(27.6519:154.6866, 1, replace = FALSE), + sample(50.01884:96.77090, 1, replace = FALSE), + sample(c(1,2), 1, prob=(c(0.5,0.5)), replace = FALSE), + sample(1.610638: 1.684438, 1, replace = FALSE), + sample(-0.1961401:-0.1647757, 1, replace = FALSE) + ) + colnames(sDF) <- c('age', 'contributors', 'collaborators', 'milestones', 'mmt', 'up_fac_mean') + return(sDF) } powerCheck <- function(n, nSims) { #run a power calculation on the dataset given @@ -35,9 +36,10 @@ powerCheck <- function(n, nSims) { #run a power calculation on the dataset given signif3 <- rep(NA, nSims) signifM <- rep(NA, nSims) for (s in 1:nSims) { # repeatedly we will.... - simData <- makeData(n) # make some data - m1.sim <- glm(nd ~ source, # give the anticipated regression a try - family=binomial(link="logit"), data=simData) + simData <- makeDataNew(n) # make some data + #have updated for kkex 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