Dear Mirisage: Did you see this question posted before? I posted it few times, but no answers available yet. So I am not sure if others able to see it. many thanks abou Perform ANOVA and multiple comparisons with PROC surveymeans This question is Not Answered.(Mark as assumed answered) Dear All: I do need helps with how to use both PROC surveyfreq and PROC surveymeans to do the following analysis. I really thank you all for your helps. I have the following variables: Stratum1 (1,2) Months (0,1,2) X1 (1=yes,2=No) ---- nominal categorical X2 ------ interval continuous Weight1 ---- weight variable I need (1) to test the equality of proportions of ones in months (0,1,2), and conduct a multiple comparison test for these proportions. (2) to test the equality of the averages in months(0,1,2) and conduct a multiple comparison test for these means. (3) test for trend: for example if there is increasing or decreasing in averages (X2), if there is increasing or decreasing in proportions of ones (X1). Any helps will be appreciated. Please email me copy of your answer. With many thanks Steve Email: sstoline@gmail.com data1--- as an example ============================= X2 X1 stratum1 months weight1 29.4822 2 2 0 16.61921705 33.2849 2 2 0 16.61921705 16.9370 1 1 0 2.09612124 19.0055 1 1 0 2.09612124 21.1151 1 2 0 16.61921705 25.4055 2 2 0 16.61921705 24.4164 1 1 0 1.56167161 19.0767 1 1 0 1.56167161 23.1562 2 1 0 2.09612124 23.3479 1 1 0 2.09612124 21.7370 1 1 0 2.09612124 24.9726 2 2 0 16.61921705 20.3836 1 2 0 16.61921705 20.0575 1 2 0 20.88637405 17.6603 1 2 0 16.61921705 25.2274 2 2 0 16.61921705 20.9644 1 1 0 2.09612124 32.8055 2 2 0 14.51497509 39.5233 2 1 0 1.56167161 17.7288 1 1 1 2.09612124 18.3096 1 2 1 16.61921705 25.8055 2 2 1 16.61921705 30.0904 1 2 1 16.61921705 27.8082 2 1 1 2.09612124 37.3863 2 1 1 2.09612124 26.2548 2 1 1 2.09612124 17.8795 1 2 1 20.88637405 19.8000 1 2 1 16.61921705 28.6932 2 1 1 1.56167161 27.1041 2 2 1 16.61921705 36.1836 2 2 1 16.61921705 19.8192 1 1 1 2.09612124 31.9644 2 2 1 20.88637405 27.0740 1 1 1 2.09612124 23.5288 2 1 1 2.09612124 21.9068 1 2 1 14.51497509 20.3534 1 2 1 16.61921705 29.4767 2 2 1 14.51497509 22.8274 1 2 1 16.61921705 21.2685 1 2 1 20.88637405 31.8932 1 1 1 1.56167161 31.8795 2 1 1 2.09612124 21.2630 2 1 1 2.09612124 18.7562 2 1 1 2.09612124 16.8822 1 2 1 20.88637405 22.0164 2 2 2 20.88637405 27.4959 2 1 2 2.09612124 27.4904 2 1 2 1.56167161 2.7096 2 2 2 14.51497509 23.0027 1 2 2 16.61921705 19.2767 1 2 2 16.61921705 30.4466 1 2 2 16.61921705 36.5425 2 2 2 16.61921705 32.2521 2 1 2 1.56167161 36.9534 1 2 2 14.51497509 30.4164 2 2 2 14.51497509 20.2767 2 1 2 2.09612124 17.2356 1 2 2 20.88637405 20.8247 2 2 2 16.61921705 20.8795 1 2 2 16.61921705 27.5260 2 2 16.61921705 19.2493 1 2 2 16.61921705 17.8521 1 2 2 16.61921705 19.6822 1 2 2 16.61921705 36.8356 2 1 2 1.5616716
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