Which way to do a post hoc test in SAS?

[monsterpie]

Hi all, 

I have a dataset (see example below) of the number of social media posts by platform type and account type. I've run a Fisher's exact test which has turned out to be significant and now I want to determine where the actual differences in proportion lie. For example, I'd like to determine if the proportion of posts by Account 1 on Platform1 are significantly different in comparison to all other account types. I've performed a post hoc test where I made a new dichotomous variable, 1=Account 1, 0=all other accounts and then run a Fisher's exact on this 3x2 table.

EXAMPLE TABLE:

Frequency of Posts

	Account1	Account2	Account3	Account4	Account5
Platform1
Platform2
Platform3

QUESTIONS:

1) I'm wondering if based on my aims, it's correct to group the columns as I have for a post hoc test. Most examples of pairwise comparisons as post hoc tests that I've seen tend to group the rows rather than the columns. 

EXAMPLE PAIRWISE COMPARISON

	Account1	All other accounts
Platform1
Platform2
Platform3

Bonferroni p<0.0001

2) From my output, I get 5 p values (1 per each account type). For example, if the p value of my first pairwise comparison (see example above) is significant, then does this mean that there is a significant difference in the proportion of posts for Account1 compared to all other accounts for each of the 3 platforms? Is there a way in SAS to determine which exact cells within one row are significantly different between account types?

[StatDave]

See this note. You might want to fit a Poisson model and then use LSMESTIMATE statements as shown in the log linear model section there to make the comparisons. If desired, you could then gather all of the p-values in a data set and then use PROC MULTTEST to do an adjustment for multiple testing as shown earlier in the note.