Hello fellow SAS-users
I'm working on a research project, where I have to compare if there is any significant change in variables on 5 different times (TIME 1-5) in 2 randomisation groups (Randomisation_code 0 and 1) (see dataset). I need to compare them as change from time 1 to 2, 2 to 3 etc. but also over the time at last.
Variables are defined as continuous and categorical (i.e. A1=continuous, A1_pathological = categorical).
I have, so far, just made counting of variables with 'proc freq' and stratified by randomisation_code, and in addition made testing by chisq.
I am very (as very much!) new to SAS and I do not know how to move forward and manage this problem.
I will appreciate any help and step-by-step explanation.
Thanks in advance!
Sincerely
Mignon
Hi Reeza
Thank you for fast reply!
I do not know how to explain my problem, but I'll try with an example:
1) I need to see if there is change in variable 'A1_patological' from 'time 1' to 'time 2' to 'time 3' to 'time 4' to 'time 5' in total and afterwards stratified by randomisation code (0 or 1).
My participants does not necessary have measured A1 at all 5 time points.
2) as above, just to see if variable 'A1' (continuous value) is changing (raising or falling) at this 5 time points in total and afterwards stratified by randomisation code (0 or 1).
I suppose that I can present data as a diagram.
I hope the data set is visible now with a copy and paste from Excel-file. Wasn't it that I should do?
Sincerely
Mignon
ParticipantID_and_time | Randomisation_code | P_pr_min | A1 | A1_patological | A2 | A2_patological | A3 | A3_patological | A4 | A4_patological | A5 | A5_patological | A_max_dur | A_max_dur_patological | TIME |
ID1time1 | 0 | 73 | -0,25 | 1 | -0,25 | 1 | -3,25 | 1 | 0 | 0 | 0 | 0 | 80 | 1 | 1 |
ID1time2 | 0 | 77 | -0,25 | 1 | -0,5 | 1 | -4 | 1 | 0 | 0 | 0 | 0 | 100 | 1 | 2 |
ID1time3 | 0 | 88 | -0,25 | 1 | -0,25 | 1 | 0 | 0 | 0 | 0 | -0,25 | 1 | 40 | 1 | 3 |
ID1time4 | 0 | 144 | -0,5 | 1 | -0,25 | 1 | -2,5 | 1 | 0 | 0 | -0,25 | 1 | 60 | 1 | 4 |
ID1time5 | 0 | 96 | -0,5 | 1 | 0 | 0 | -2 | 1 | 0 | 0 | -0,25 | 1 | 60 | 1 | 5 |
ID2time1 | 0 | 93 | 0 | 0 | -0,512820513 | 0 | -0,769230769 | 1 | -13,84615385 | 1 | 0 | 0 | 61,53846154 | 1 | 1 |
ID2time2 | 0 | 81 | 0 | 0 | 0 | 0 | 0 | 0 | -7,435897436 | 1 | -0,769230769 | 1 | 102,5641026 | 1 | 2 |
ID3time1 | 0 | 79 | -0,5 | 1 | -0,25 | 1 | 0 | 0 | 0 | 0 | -0,25 | 1 | 80 | 1 | 1 |
ID3time2 | 0 | 54 | 0 | 0 | -0,25 | 1 | -1,25 | 1 | -3 | 1 | 0 | 0 | 80 | 1 | 2 |
ID3time5 | 0 | 67 | 0 | 0 | 0 | 0 | -1 | 1 | -2,5 | 1 | 0 | 0 | 20 | 0 | 5 |
ID4time1 | 1 | 114 | . | . | . | . | . | . | . | . | . | . | 30 | 1 | 1 |
ID4time4 | 1 | 91 | 0 | 0 | -0,75 | 1 | -1,25 | 1 | -7 | 1 | 0 | 0 | 40 | 1 | 4 |
ID4time5 | 1 | 82 | 0 | 0 | -1,25 | 1 | -4 | 1 | 0 | 0 | 0 | 0 | 40 | 1 | 5 |
ID5time1 | 0 | 85 | -0,5 | 1 | -0,5 | 1 | -0,25 | 1 | 0 | 0 | -0,5 | 1 | 80 | 1 | 1 |
ID5time2 | 0 | 59 | 0 | 0 | -1 | 1 | -1 | 1 | 0 | 0 | 0 | 0 | 80 | 1 | 2 |
ID5time3 | 0 | 89 | 0 | 0 | -1 | 1 | -0,5 | 1 | 0 | 0 | 0 | 0 | 60 | 1 | 3 |
ID5time4 | 0 | 104 | 0 | 0 | -1,25 | 1 | 0 | 0 | -7,5 | 1 | 0 | 0 | 60 | 1 | 4 |
1. Switch your data to a long format, it's easier to program your logic that way -> PROC TRANSPOSE or a DATA STEP.
https://stats.idre.ucla.edu/sas/modules/reshaping-data-wide-to-long-using-a-data-step/
https://stats.idre.ucla.edu/sas/modules/how-to-reshape-data-wide-to-long-using-proc-transpose/
2. Use LAG to find the difference between the time points
http://support.sas.com/resources/papers/proceedings09/055-2009.pdf
3. Once you have that, you have the data to do your tests, which I think I answered in another post - you can use PROC MEANS to calculate the total change, or you can use PROC NPAR1WAY to test the values.
Thank you Reeza
I'll try work on it!
Sincerely
Mignon
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