library("DescTools")
t = "C:\\Users\\Admin\\Google Drive\\ipv.csv"
duy = read.csv(t)
attach(duy)
options(scipen = 999)
head(duy)
## id rejection bk cmv nodat ckd sex age hla relationship time c0
## 1 1 No 0 0 0 No Male 37 6 Deceased 1 3.2
## 2 2 No 0 0 0 No Male 37 2 Living related 2 7.2
## 3 3 No 0 0 0 No Female 24 2 Living related 1 7.2
## 4 4 No 0 0 0 No Male 30 2 Living related 1 18.1
## 5 5 No 0 0 0 No Male 44 5 Living related 1 16.4
## 6 6 No 0 0 0 No Male 41 3 Living unrelated 1 10.8
## mean diff sum.of.diff ipv
## 1 4.700000 1.500000 10.40000 31.61094
## 2 5.233333 1.966667 12.33333 26.18542
## 3 9.500000 2.300000 26.60000 31.11111
## 4 7.029412 11.070588 42.70588 35.73714
## 5 12.285714 4.114286 44.57143 25.91362
## 6 8.721429 2.078571 25.10000 20.55692
Desc(ipv)
## -------------------------------------------------------------------------
## ipv (numeric)
##
## length n NAs unique 0s mean
## 114 114 0 = n 0 25.723385
## 100.0% 0.0% 0.0%
##
## .05 .10 .25 median .75 .90
## 13.244883 15.739531 19.879244 25.986638 30.671506 36.403958
##
## range sd vcoef mad IQR skew
## 43.332901 8.086928 0.314380 8.037092 10.792262 0.023376
##
## meanCI
## 24.222819
## 27.223951
##
## .95
## 39.356093
##
## kurt
## 0.003295
##
## lowest : 3.191489, 7.017544, 7.251908, 12.295665, 12.962963
## highest: 40.672231, 40.988836, 41.547049, 44.884038, 46.52439
Desc(ipv ~ rejection)
## -------------------------------------------------------------------------
## ipv ~ rejection
##
## Summary:
## n pairs: 114, valid: 114 (100.0%), missings: 0 (0.0%), groups: 2
##
##
## No Yes
## mean 25.642 28.719
## median 25.914 28.313
## sd 8.167 3.615
## IQR 10.954 3.597
## n 111 3
## np 97.368% 2.632%
## NAs 0 0
## 0s 0 0
##
## Kruskal-Wallis rank sum test:
## Kruskal-Wallis chi-squared = 0.79914, df = 1, p-value = 0.3714
