Hi,
A khi² test of association can inform us about the presence/absence of a significant difference between groups.
Is it possible to add a post-hoc test to identify which group is different from the others (when the size of the table is > 2x2)? Maybe a pairwise.prop.test() or something like that?
Have a nice day.
Romaric
Post-hoc test after a Khi² test of association
Re: Post-hoc test after a Khi² test of association
hi romaric,
this is a good idea. i will try and do this in the next fortnight. you've put in so many good feature requests, and i feel like we haven't got to any of them. anyway, i *will* do this in the next fortnight, so kick up a stink if i don't
with thanks
this is a good idea. i will try and do this in the next fortnight. you've put in so many good feature requests, and i feel like we haven't got to any of them. anyway, i *will* do this in the next fortnight, so kick up a stink if i don't
with thanks
Re: Post-hoc test after a Khi² test of association
Hi Jonothan,
After a little research, maybe a simpler way to implement a post-hoc test for a khi² test would be to use the existing chisq.test from the stats package which gives the khi² value, its significance level and the Pearsons' residues (Xsq$residuals) and the Habermans' residues (Xsq$stdres) ?
Example.
> M <- as.table(rbind(c(212,29,11,2,3), c(318,61,6,11,13), c(160,39,9,6,12)))
> rownames(M) <- c("a1","a2","a3")
> colnames(M) <- c("b1","b2","b3","b4","b5")
> M
b1 b2 b3 b4 b5
a1 212 29 11 2 3
a2 318 61 6 11 13
a3 160 39 9 6 12
> Xsq <- chisq.test(M)
Message d’avis :
In chisq.test(M) : l’approximation du Chi-2 est peut-^etre incorrecte
> Xsq
Pearson’s Chi-squared test
data: M
X-squared = 20.3583, df = 8, p-value = 0.009062
> Xsq$residuals
b1 b2 b3 b4 b5
a1 0.93616090 -1.33963261 1.28206096 -1.48489514 -1.78406400
a2 0.09113804 0.24066234 -1.71501389 0.77521492 0.04505463
a3 -1.12090876 1.10480426 0.93998072 0.54059524 1.84188135
> Xsq$stdres
b1 b2 b3 b4 b5
a1 2.33159333 -1.71672778 1.54215391 -1.77896194 -2.14848117
a2 0.26026470 0.35362027 -2.36537490 1.06489378 0.06221195
a3 -2.72597782 1.38245439 1.10404745 0.63240142 2.16587067
The khi² value gives 1% so every value of Xsq$stdres which sits outside [-2.33;+2.33] flags a significant difference. So here, the signficant differences are found between (a1, b1), (a2, b3) and (a3, b1).
The example comes from http://www.normalesup.org/~carpenti/Not ... esidus.pdf (written in french, sorry). And the 2.33 limit comes from http://www1.udel.edu/FREC/ilvento/FREC408/normhand
I'm not a khi2 specialist at all, so it's just a suggestion. If a stats wizard would be kind enough to step in, his or her advices would be much appreciated
Have a nice day.
After a little research, maybe a simpler way to implement a post-hoc test for a khi² test would be to use the existing chisq.test from the stats package which gives the khi² value, its significance level and the Pearsons' residues (Xsq$residuals) and the Habermans' residues (Xsq$stdres) ?
Example.
> M <- as.table(rbind(c(212,29,11,2,3), c(318,61,6,11,13), c(160,39,9,6,12)))
> rownames(M) <- c("a1","a2","a3")
> colnames(M) <- c("b1","b2","b3","b4","b5")
> M
b1 b2 b3 b4 b5
a1 212 29 11 2 3
a2 318 61 6 11 13
a3 160 39 9 6 12
> Xsq <- chisq.test(M)
Message d’avis :
In chisq.test(M) : l’approximation du Chi-2 est peut-^etre incorrecte
> Xsq
Pearson’s Chi-squared test
data: M
X-squared = 20.3583, df = 8, p-value = 0.009062
> Xsq$residuals
b1 b2 b3 b4 b5
a1 0.93616090 -1.33963261 1.28206096 -1.48489514 -1.78406400
a2 0.09113804 0.24066234 -1.71501389 0.77521492 0.04505463
a3 -1.12090876 1.10480426 0.93998072 0.54059524 1.84188135
> Xsq$stdres
b1 b2 b3 b4 b5
a1 2.33159333 -1.71672778 1.54215391 -1.77896194 -2.14848117
a2 0.26026470 0.35362027 -2.36537490 1.06489378 0.06221195
a3 -2.72597782 1.38245439 1.10404745 0.63240142 2.16587067
The khi² value gives 1% so every value of Xsq$stdres which sits outside [-2.33;+2.33] flags a significant difference. So here, the signficant differences are found between (a1, b1), (a2, b3) and (a3, b1).
The example comes from http://www.normalesup.org/~carpenti/Not ... esidus.pdf (written in french, sorry). And the 2.33 limit comes from http://www1.udel.edu/FREC/ilvento/FREC408/normhand
I'm not a khi2 specialist at all, so it's just a suggestion. If a stats wizard would be kind enough to step in, his or her advices would be much appreciated
Have a nice day.
Re: Post-hoc test after a Khi² test of association
eek, you're right romaric, there seems to be a lot of different ways to do this.
http://pareonline.net/getvn.asp?v=20&n=8
jonathon
http://pareonline.net/getvn.asp?v=20&n=8
jonathon
Re: Post-hoc test after a Khi² test of association
Oh... well, it's less simple than what I thought (i.e. a quick and easy post-hoc test like with an Anova test), my apologies
Re: Post-hoc test after a Khi² test of association
As a solution, there is also the chisq.post.hoc() function
And after reading the link you provided, it seems that the one solution to avoid the post-hoc analysis following à khi² test "is to replace chisquare testing with log-linear analysis" (p.08).
So, a lead to solve this problem would maybe be to use the glm() function?
It's just a suggestion and I'll let the stats wizards debate over this, but a solution or a module (someone interested? ) would be nice so that mere mortals are not stuck with a significant difference (when there are more than two categorical variables) and no way to find its location in the data.
And keep up the godd work
And after reading the link you provided, it seems that the one solution to avoid the post-hoc analysis following à khi² test "is to replace chisquare testing with log-linear analysis" (p.08).
So, a lead to solve this problem would maybe be to use the glm() function?
It's just a suggestion and I'll let the stats wizards debate over this, but a solution or a module (someone interested? ) would be nice so that mere mortals are not stuck with a significant difference (when there are more than two categorical variables) and no way to find its location in the data.
And keep up the godd work
Re: Post-hoc test after a Khi² test of association
Hello,
Is there a post hoc test for Chi Square available in Jamovi now?
Paige
Is there a post hoc test for Chi Square available in Jamovi now?
Paige
Re: Post-hoc test after a Khi² test of association
hi,
not at this stage. generally we need:
a) a clear idea of the "correct thing to do"
b) a clear idea what R packages can perform that "correct thing"
c) time to do it.
at this stage we're stuck at a)
cheers
jonathon
not at this stage. generally we need:
a) a clear idea of the "correct thing to do"
b) a clear idea what R packages can perform that "correct thing"
c) time to do it.
at this stage we're stuck at a)
cheers
jonathon
Re: Post-hoc test after a Khi² test of association
Hi, guys.
My answer here with Rj:
viewtopic.php?f=12&t=822
The request n. 494 "Adequate residues in chi-square tests" is still open, see here:
https://github.com/jamovi/jamovi/issues/494
Jonathon, do you know this?
Thanks, as always for your work.
Cheers,
Maurizio
My answer here with Rj:
viewtopic.php?f=12&t=822
The request n. 494 "Adequate residues in chi-square tests" is still open, see here:
https://github.com/jamovi/jamovi/issues/494
Jonathon, do you know this?
Thanks, as always for your work.
Cheers,
Maurizio
Re: Post-hoc test after a Khi² test of association
maurizio! have you ever thought about having a go at adding this to jmv yourself?
jonathon
jonathon