Post hoc after chi square test

General
1

Hi
I have 2 groups in a variable called Diabetes and 4 groups in variable called Activity.
chisquare test given below results

> chisq.test(df$Diabetes,df$Activity)

	Pearson's Chi-squared test

data:  df$Diabetes and df$Activity
X-squared = 129.92, df = 3, p-value < 2.2e-16

Now i want to see the pair wise relation between each group, some thing like TukeyHSD for anova.
what test i can run here for post hoc after chisquare test.

Thank you

2

Hi @sai_matcha,
Here are a couple of options using add-on packages:

library(chisq.posthoc.test)
# Example
M <- as.table(rbind(c(762, 327, 468), c(484, 239, 477)))
dimnames(M) <- list(gender = c("F", "M"),
                    party = c("Democrat","Independent", "Republican"))
M
#>       party
#> gender Democrat Independent Republican
#>      F      762         327        468
#>      M      484         239        477

# Pass data matrix to chisq.posthoc.test function
chisq.posthoc.test(M)
#>   Dimension     Value  Democrat Independent Republican
#> 1         F Residuals  4.502054   0.6994517  -5.315946
#> 2         F  p values  0.000040   1.0000000   0.000001
#> 3         M Residuals -4.502054  -0.6994517   5.315946
#> 4         M  p values  0.000040   1.0000000   0.000001
chisq.posthoc.test(M,method = "bonferroni")
#>   Dimension     Value  Democrat Independent Republican
#> 1         F Residuals  4.502054   0.6994517  -5.315946
#> 2         F  p values  0.000040   1.0000000   0.000001
#> 3         M Residuals -4.502054  -0.6994517   5.315946
#> 4         M  p values  0.000040   1.0000000   0.000001

# Alternative package/function
library(RVAideMemoire)
#> *** Package RVAideMemoire v 0.9-81-2 ***
chisq.theo.multcomp(M, p.method = "bonferroni")
#> 
#>         Pairwise comparisons using chi-squared tests
#> 
#> data:  M and bonferroni
#> 
#>  observed.gender observed.party observed.Freq expected      Chi  Pr(>Chi)    
#>                F       Democrat           762    459.5 238.9717 3.954e-53 ***
#>                M       Democrat           484    459.5   1.5676 1.000e+00    
#>                F    Independent           327    459.5  45.8487 7.665e-11 ***
#>                M    Independent           239    459.5 126.9734 1.130e-28 ***
#>                F     Republican           468    459.5   0.1887 1.000e+00    
#>                M     Republican           477    459.5   0.7998 1.000e+00    
#> 
#> P value adjustment method: bonferroni

Created on 2022-10-07 with reprex v2.0.2

Hope this helps.

3

Thank you very muh @DavoWW . Can i ask you to help me to interpret the results from above .
P values in independent session shows 1 , i am not getting that value is between which two groups.

Thanks