mgaughan/24_deb_pkg_gov
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

updates to analysis

Browse Source
This commit is contained in:
mjgaughan 2023-11-13 22:30:40 -06:00
parent 7bcf7ac4f8
commit 48d1be7bf8
1 changed files with 6 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
R/calculatePower.R
View File

@ -27,7 +27,7 @@ data2 <- read_csv('../inst_all_packages_full_results.csv')
python_labeled <- as.numeric(data2$up.fac.mean[match(paste('python',tolower(data1$pkg), sep = "-"), data2$pkg)]) python_labeled <- as.numeric(data2$up.fac.mean[match(paste('python',tolower(data1$pkg), sep = "-"), data2$pkg)])
same_labeled <- as.numeric(data2$up.fac.mean[match(tolower(data1$pkg), data2$pkg)]) same_labeled <- as.numeric(data2$up.fac.mean[match(tolower(data1$pkg), data2$pkg)])
data1$up.fac.mean <- pmin(python_labeled, same_labeled, na.rm=TRUE) data1$up.fac.mean <- pmin(python_labeled, same_labeled, na.rm=TRUE)
data1$milestones <- as.numeric(data1$milestones > 0) data1$milestones <- as.numeric(data1$milestones > 0) + 1
# (2) - Run the model on the pilot data # (2) - Run the model on the pilot data
data1$formal.score <- data1$mmt / (data1$milestones/data1$age) data1$formal.score <- data1$mmt / (data1$milestones/data1$age)
table(data1$milestones) table(data1$milestones)
@ -46,7 +46,7 @@ cor.test(data1$mmt, data1$up.fac.mean)
cor.test(data1$milestones, data1$up.fac.mean) cor.test(data1$milestones, data1$up.fac.mean)
cor.test(data1$age, data1$up.fac.mean) cor.test(data1$age, data1$up.fac.mean)
g <- ggplot(data1, aes(x=formal.score, y=up.fac.mean)) + g <- ggplot(data1, aes(x=mmt, y=up.fac.mean)) +
geom_point() + geom_point() +
geom_smooth() geom_smooth()
g g
@ -67,10 +67,10 @@ summary(kmodel2)
# family=gaussian(link='identity'), data=data1) # family=gaussian(link='identity'), data=data1)
summary(pilotM) #we expect effect sizes on this order summary(pilotM) #we expect effect sizes on this order
pilot.b0 <- coef(summary(pilotM))[1,1] pilot.b0 <- coef(summary(kmodel2))[1,1]
pilot.b1 <- coef(summary(pilotM))[2,1] pilot.b1 <- coef(summary(kmodel2))[2,1]
pilot.b2 <- coef(summary(pilotM))[3,1] pilot.b2 <- coef(summary(kmodel2))[3,1]
pilot.b3 <- coef(summary(pilotM))[4,1] pilot.b3 <- coef(summary(kmodel2))[4,1]
# (3) - Set up and run the simulation # (3) - Set up and run the simulation