Dear Daniel,
Dear R-experts,
I really thank you a lot Daniel. Nobody had answered to me offline. So, thanks.
I have tried in the same vein for the Goodman-Kruskal gamma for ordinal data.
There is an error message at the end of the code. Thanks for your help.
##############################
library(ryouready)
library(boot)
shopping1<-c("très important","important","pas important","pas important","important","très important","important","pas important","très important","très important","important","pas important","pas important","important","très important","très important","important","pas important","pas
important","important","très important","très important","important","pas important","pas important","important","très important","très important","important","pas important","pas important","important","très important","très important","important","pas important","pas
important","important","très important","important")
statut1<-c("riche","pas riche","moyennement riche","moyennement riche","riche","pas riche","moyennement riche","moyennement riche","riche","pas riche","moyennement riche","riche","pas riche","pas riche","riche","moyennement riche","riche","pas riche","pas riche","pas
riche","riche","riche","moyennement riche","riche","riche","moyennement riche","moyennement riche","moyennement riche","pas riche","pas riche","riche","pas riche","riche","pas riche","riche","moyennement riche","riche","pas riche","moyennement riche","riche")
shopping2<-c("important","pas important","très important","très important","important","très important","pas important","important","pas important","très important","important","important","important","important","pas important","très important","très important","important","pas
important","très important","pas important","très important","pas important","très important","important","très important","important","pas important","pas important","important","pas important","très important","pas important","pas important","important","important","très important","très
important","pas important","pas important")
statut2<-c("moyennement riche","pas riche","riche","moyennement riche","moyennement riche","moyennement riche","pas riche","riche","riche","pas riche","moyennement riche","riche","riche","riche","riche","riche","pas riche","moyennement riche","moyennement riche","pas
riche","moyennement riche","pas riche","pas riche","pas riche","moyennement riche","riche","moyennement riche","riche","pas riche","riche","moyennement riche","blue","moyennement riche","pas riche","pas riche","riche","riche","pas riche","pas riche","pas riche")
f1 <- data.frame(shopping=shopping1,statut=statut1,group='grp1')
f2 <- data.frame(shopping=shopping2,statut=statut2,group='grp2')
f3 <- rbind(f1,f2)
G <- function(x, index) {
# calculate goodman for group 1 bootstrap sample
g1 <-x[index,][x[,3]=='grp1',]
goodman_g1 <- cor(data[index,][1,2])
# calculate goodman for group 2 bootstrap sample
g2 <-x[index,][x[,3]=='grp2',]
goodman_g2 <- cor(data[index,][3,4])
# calculate difference
goodman_g1-goodman_g2
}
# use strata parameter in function boot to resample within each group
results <- boot(data=f3,statistic=G, strata=as.factor(f3$group),R=2000)
results
boot.ci(results)
##############################
Le samedi 4 juin 2022 à 09:31:36 UTC+2, Daniel Nordlund <djnordl...@gmail.com>
a écrit :
On 5/28/2022 11:21 AM, varin sacha via R-help wrote:
Dear R-experts,
While comparing groups, it is better to assess confidence intervals of those
differences rather than comparing confidence intervals for each group.
I am trying to calculate the CIs of the difference between the two Cramer's V
and not the CI to the estimate of each group’s Cramer's V.
Here below my toy R example. There are error messages. Any help would be highly
appreciated.
##############################
library(questionr)
library(boot)
gender1<-c("M","F","F","F","M","M","F","F","F","M","M","F","M","M","F","M","M","F","M","F","F","F","M","M","M","F","F","M","M","M","F","M","F","F","F","M","M","F","M","F")
color1<-c("blue","green","black","black","green","green","blue","blue","green","black","blue","green","blue","black","black","blue","green","blue","green","black","blue","blue","black","black","green","green","blue","green","black","green","blue","black","black","blue","green","green","green","blue","blue","black")
gender2<-c("F","F","F","M","M","F","M","M","M","F","F","M","F","M","F","F","M","M","M","F","M","M","M","F","F","F","M","M","M","F","M","M","M","F","F","F","M","F","F","F")
color2<-c("green","blue","black","blue","blue","blue","green","blue","green","black","blue","black","blue","blue","black","blue","blue","green","blue","black","blue","blue","black","black","green","blue","black","green","blue","green","black","blue","black","blue","green","blue","green","green","blue","black")
f1=data.frame(gender1,color1)
tab1<-table(gender1,color1)
e1<-cramer.v(tab1)
f2=data.frame(gender2,color2)
tab2<-table(gender2,color2)
e2<-cramer.v(tab2)
f3<-data.frame(e1-e2)
cramerdiff=function(x,w){
y<-tapply(x[w,1], x[w,2],cramer.v)
y[1]-y[2]
}
results<-boot(data=f3,statistic=cramerdiff,R=2000)
results
boot.ci(results,type="all")
##############################
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
I don't know if someone responded offline, but if not, there are a
couple of problems with your code. First, the f3 dataframe is not what
you think it is. Second, your cramerdiff function isn't going to
produce the results that you want.
I would put your data into a single dataframe with a variable
designating which group data came from. Then use that variable as the
strata variable in the boot function to resample within groups. So
something like this:
f1 <- data.frame(gender=gender1,color=color1,group='grp1')
f2 <- data.frame(gender=gender2,color=color2,group='grp2')
f3 <- rbind(f1,f2)
cramerdiff <- function(x, ndx) {
# calculate cramer.v for group 1 bootstrap sample
g1 <-x[ndx,][x[,3]=='grp1',]
cramer_g1 <- cramer.v(table(g1[,1:2]))
# calculate cramer.v for group 2 bootstrap sample
g2 <-x[ndx,][x[,3]=='grp2',]
cramer_g2 <- cramer.v(table(g2[,1:2]))
# calculate difference
cramer_g1-cramer_g2
}
# use strata parameter in function boot to resample within each group
results <- boot(data=f3,statistic=cramerdiff,
strata=as.factor(f3$group),R=2000)
results
boot.ci(results)
Hope this is helpful,
Dan
