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library(tidyr) getwd() setwd() vsl <- read.csv("vsl1314.csv") > vsl ï..year sex dom exp ra1pat ra1time ra5pat ra5time rv1pat rv1time rv5pat 1 2014 M R 7.0 Y 41 Y 35 Y 40 Y 2 2014 M R 3.0 Y 45 Y 55 N 45 Y 3 2014 M R 4.0 Y 70 Y 45 Y 50 Y 4 2014 M R 15.0 N 90 Y 50 Y 70 Y vsl2 = subset(vsl,select=-c(totnum, success,rate)) # to drop the summary stats hist(vsltime$time, main="Anastomosis time (all) 2013-2014 n=512")
Histogram to check shape of distribution –> looks skewed to the right
> shapiro.test(vsltime$time)
Shapiro-Wilk normality test
data: vsltime$time W = 0.91157, p-value = 1.388e-14
Shapiro-Wilk test for normality –> not normal distribution
> hist(vsl$success)
> shapiro.test(vsl$success) Shapiro-Wilk normality test data: vsl$success W = 0.9117, p-value = 0.0002277
Some other analyses:
> plot(vsl$exp,vsl$rate,main="Anastomosis success rate vs experience (in years)") > plot(vsl$exp,vsl$totnum) > plot(vsl$exp,((vsl$totnum/8)+(vsl$rate))/2)
Suggests that the first few years of experience does not seem to make a difference to performance, but many years of experience does (? self-selection or already some training).
Sources: