Hi Community,
I want to know, which procedure is used to find the P value of 2 numeric columns.
Here i attch the sample dataset.
data have;
input ID1 ID2;
cards;
10 15
. 30
20 38
50 20
15 10
80 50
25 40
. 50
;
run;
OP should be like,
ID1 | ID2 | PVAL | |
<20 | % Value ID1 | % Value ID2 | ? |
20 to 30 | % Value ID1 | % Value ID2 | ? |
>30 | % Value ID1 | % Value ID2 | ? |
I evaluated the % value, But I'm looking for Pval
And the one more question is : What is the right format to calculate the pval., (with missing value or only with available value)
Please help me to solve this.
Thanks in advance!
Hi @Sathish_jammy,
There is no such thing as the "P value of 2 numeric columns."
What statistical test do you want to perform? What are the null and alternative hypotheses?
Ideally, you can find this information in your statistical analysis plan.
Dear @FreelanceReinh
Thanks for your suggesstion.
I want to generating a report like the image below.
Here the orange bar is HBA value(Baseline) and the blue bar is HBA Followup
The bar diagrams are performed as %, If u calculate the values it ends up with 100.
I need to evaluate the p value for baseline and followup.
Sorry @Sathish_jammy, this explains nothing, your data does not relate to this diagram, and furthermore, this diagram does not really explain what the p value is that shows on the plot.
Please explain the results you want, in relationship to the actual data you posted. Please explain, as requested by @FreelanceReinh, the exact statistical test you want to perform so we can know how to compute the p-value.
Unlike your initial post, your graph suggests that you want to compare dependent samples (baseline vs. follow up) with ordinal level data in three categories. However, assuming that this is about HBA1c values (i.e. metric values) in diabetic patients (?), it's not clear why you would categorize them rather than compute differences (i.e. change from baseline) and use these as input for a statistical test (e.g. a paired t-test or Wilcoxon signed-rank test). Even if the categorization made sense: Why would you perform three tests (McNemar tests?), one for each of the three categories, although they are not independent?
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