Is score data as count vs continuous

[lboyd]

I have data from a pre-assessment and a post-assessment.  Each question/statement was coded as dichotomous (yes/no).  I took the sum of the questions for both pre (shown below) and post using an array:

array xst_itp [12] xst_1 xst_2 xst_3 xst_4 xst_5 xst_6 xst_7 xst_8 xst_9 xst_10 xst_11 xst_12;
        pre_tot = sum(of xst_itp[*]);
        pre_miss_n = cmiss(of xst_itp[*]);
        if st_miss_n  = 12 then st_complete =  0;
        if st_miss_n  < 12 then st_complete =  1;

I then ran a simple paired ttest:

proc ttest data = all_data;
paired pre_tot*post_tot;

run;

My question is, is it okay to treat this data as continuous data?  Do I need to treat it as count/discrete instead? If so, what analysis would you suggest in SAS?

My other question is, do I need to check the normality of both pre_tot and post_tot? And if one is not normal, do I need to use a Wilcoxon signed-rank test instead?

[Reeza]

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@lboyd wrote:

My question is, is it okay to treat this data as continuous data?  Do I need to treat it as count/discrete instead? If so, what analysis would you suggest in SAS?

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That's more of a subject specific question in my opinion. 

It depends on how you coded things and such. It's more counts really than a continuous distribution. 

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My other question is, do I need to check the normality of both pre_tot and post_tot? And if one is not normal, do I need to use a Wilcoxon signed-rank test instead?

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You should check the normality, but I think the assumption still holds if the distributions are the same.