R help - Nov 2013 - the wilcox.test() and pairwise.wilcox.test are producing different results

Dear list member,



I want to compare if the rank order is significantly different for seven
different measures. So we have same sample but different measures which
reduces the problem to a paired one sample Wilcox test if I understood the
test correctly. In constructed toy examples for my sake of understanding,
but things are not adding up. Basically, the wilcox.test() and
pairwise.wilcox.test are producing different results when they should not
(according to my understanding of course):



#take a vector

daily.intake <- c(5260,5470,5640,6180,6390,6515,

                  + 6805,7515,7515,8230,8770)



#I get desired results when I do the following

daily<-data.frame(pre=daily.intake, post=daily.intake)



#add som differences

daily[1,1]<-5000

daily[2,1]<-5100





#reshape the data for pairwise comparison

library(reshape2)

daily_long<-melt(daily, id=)



#conduct simple test

wilcox.test(daily$pre,daily$post, paired=T) #produces desired results



#do the test again but now in a pairwise, which produces the same p-value
as in the simple test above

pairwise.wilcox.test(daily_long$value,daily_long$variable, paired=T)



#But now I the issues arise when testing more than two vectors.



#take three vectors this time

daily<-data.frame(pre=daily.intake, post=daily.intake, posttwo=daily.intake)



#add some differences

daily[1,1]<-5000

daily[2,1]<-5100

daily[10,3]<-9000

daily[11,3]<-9100



#the wilcox.test() produces a set of p-values

wilcox.test(daily$pre,daily$posttwo, paired=T)

 wilcox.test(daily$pre,daily$post, paired=T)

wilcox.test(daily$post,daily$posttwo, paired=T)



#and the pairwise.wilcox.test produces another set

pairwise.wilcox.test(daily_long$value,daily_long$variable, paired=T)







##And from the manual for pairwise.wilcox we get similar issues



#produces a given set of p-values

attach(airquality)

Month <- factor(Month, labels = month.abb[5:9])

## These give warnings because of ties :

pairwise.wilcox.test(Ozone, Month)

pairwise.wilcox.test(Ozone, Month, p.adj = "bonf")

detach()



#but if we want to test the rank difference between the 6th and 7th month
we get a p-value of 0.5775



testar skillnaden mellan 6e och 7e månaden – observ however that this data
is not paired which makes it different to the example I gave above.

#p-värdet är 0.5775



air<-subset(airquality, airquality$Month < 7)



#p-value is now 0.1925

wilcox.test(air$Ozone~air$Month)





What am I doing wrong here?

Best

Adel

-- 
Adel Daoud, PhD
Visiting researcher (post-doc)

Max Planck Institute for the Study of Societies / Max-Planck-Institut für
Gesellschaftsforschung
Paulstr. 3 | 506 76 Köln | Germany
Tel.: + 49 (0) 221 2767-534
daoud@mpifg.de



Department of Sociology and Work Science,  University of Gothenburg
Box 720
405 30 Göteborg, Sweden
Visiting address: Sprängkullsgatan 25, room K109
+46 031-786 41 73
Adel.daoud@sociology.gu.se




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Hi,

Have you tried p.adjust="none"

?pairwise.wilcox.test(daily_long$value,daily_long$variable,
paired=T,p.adj="none")


pairwise.wilcox.test(Ozone, Month, p.adj = "none")
A.K.


Dear list member,
?
I want to compare if
the rank order is significantly different for seven different measures. So we
have same sample but different measures which reduces the problem to a paired
one sample Wilcox test if I understood the test correctly. In constructed toy
examples
for my sake of understanding, but things are not adding up. Basically, the
wilcox.test()
and pairwise.wilcox.test are producing different results when they should not
(according to my understanding of course):
?
#take a vector
daily.intake <-
c(5260,5470,5640,6180,6390,6515,
????????????????? + 6805,7515,7515,8230,8770)
?
#I get desired results
when I do the following
daily<-data.frame(pre=daily.intake,
post=daily.intake)
?
#add som differences
daily[1,1]<-5000
daily[2,1]<-5100
?
?
#reshape the data for
pairwise comparison
library(reshape2)
daily_long<-melt(daily,
id=) 
?
#conduct simple test
wilcox.test(daily$pre,daily$post,
paired=T) #produces desired results
?
#do the test again but
now in a pairwise, which produces the same p-value as in the simple test above
pairwise.wilcox.test(daily_long$value,daily_long$variable,
paired=T) 
?
#But now I the issues
arise when testing more than two vectors.
?
#take three
vectors this time
daily<-data.frame(pre=daily.intake,
post=daily.intake, posttwo=daily.intake)
?
#add some differences
daily[1,1]<-5000
daily[2,1]<-5100
daily[10,3]<-9000
daily[11,3]<-9100
?
#the wilcox.test()
produces a set of p-values 
wilcox.test(daily$pre,daily$posttwo,
paired=T)
?wilcox.test(daily$pre,daily$post, paired=T) 
wilcox.test(daily$post,daily$posttwo,
paired=T) 
?
#and the
pairwise.wilcox.test produces another set
pairwise.wilcox.test(daily_long$value,daily_long$variable,
paired=T) 
?
?
?
##And from the manual
for pairwise.wilcox we get similar issues
?
#produces a given set
of p-values
attach(airquality)
Month <- factor(Month, labels month.abb[5:9])
## These give warnings because of ties :
pairwise.wilcox.test(Ozone, Month)
pairwise.wilcox.test(Ozone, Month, p.adj "bonf")
detach()
?
#but if we want to test the rank difference between
the 6th and 7th month we get a p-value of 0.5775
?
testar skillnaden mellan 6e och 7e m?naden ? observ
however that this data is not paired which makes it different to the example I
gave above.
#p-v?rdet ?r?0.5775
?
air<-subset(airquality,
airquality$Month < 7)
?
#p-value is now 0.1925
wilcox.test(air$Ozone~air$Month)
?
?
What am I doing wrong
here? 
Best
Adel
-- 
Adel Daoud, PhD
Visiting researcher
(post-doc)


Max Planck Institute for the Study of Societies / Max-Planck-Institut f?r
Gesellschaftsforschung
Paulstr. 3 | 506 76 K?ln | Germany
Tel.: + 49 (0) 221 2767-534
[hidden email]
?Department of
Sociology and Work Science, ?University of Gothenburg
Box 720
405 30 G?teborg, Sweden
Visiting address: Spr?ngkullsgatan 25, room K109
+46 031-786 41 73
[hidden email]