R Markdown
n1<-24
n2<-54
dat1<- dat_raw[1:n1,1:4]
dat2<- dat_raw[1:n2,7:10]
dat1<-as.data.frame(dat1)
dat2<-as.data.frame(dat2)
apply(dat1,2,mean)
## absorbed dose for G1 type patients (N=24)
## 3.870382
## ...2
## 3.040409
## ...3
## 2.766789
## ...4
## 2.693954
apply(dat2,2,mean)
## (absorbed dose for G2 type patients N=54)
## 4.328074
## ...8
## 2.694393
## ...9
## 2.079948
## ...10
## 2.001328
apply(dat1,2,median)
## absorbed dose for G1 type patients (N=24)
## 3.264360
## ...2
## 2.671812
## ...3
## 2.553889
## ...4
## 2.647505
apply(dat2,2,median)
## (absorbed dose for G2 type patients N=54)
## 2.844449
## ...8
## 2.158470
## ...9
## 1.574767
## ...10
## 1.437463
record_mean<-rep(0,4)
for(ii in 1:4){
(res1<-t.test(x=dat1[,ii],y=dat2[,ii]))
record_mean[ii] <- res1$p.value
}
record_mean
## [1] 0.57508410 0.40041379 0.08270138 0.08641712
library(RVAideMemoire)
## *** Package RVAideMemoire v 0.9-81-2 ***
record_median<-rep(0,4)
for(ii in 1:4){
tmp<-data.frame(y = c(dat1[,ii],dat2[,ii]),
grp = rep(1:2,c(length(dat1[,ii]),length(dat2[,ii]))))
res_median_1<- mood.medtest(y ~ grp,
data = tmp,
exact = TRUE)
record_median[ii] <- res_median_1$p.value
}
record_median
## [1] 0.80656115 0.46219750 0.21961620 0.08484881
for(ii in 1:4){
plot(density(dat1[,ii]),main = "black=1,red=2")
lines(density(dat2[,ii]),col=2)
}
