comparison with SAS [🇷 for BE/BA]

posted by yicaoting  – NanKing, China, 2013-02-15 19:58 (4872 d 01:02 ago) – Posting: # 10037
Views: 16,671

subject(sequence) random, n=24/23:

❝ 104.98% (99.83–110.40%), CVintra 9.96%

subject(sequence) fixed, n=24/23:

❝ 104.76% (99.61–110.18%), CVintra 9.95%

subject(sequence) random, n=23/23:

❝ 104.76% (99.61–110.18%) CVintra 9.95%

subject(sequence) fixed, n=23/23:

❝ 104.76% (99.61–110.18%) CVintra 9.95%[/list]


Using the same data with SAS's GLM procedure, results are:
n=24/23
        Least Squares Means for Effect formulation

               Difference
                  Between    90% Confidence Limits for
   i    j           Means       LSMean(i)-LSMean(j)

   1    2        0.046485     -0.003939     0.096910



n=23/23
        Least Squares Means for Effect formulation

               Difference
                  Between    90% Confidence Limits for
   i    j           Means       LSMean(i)-LSMean(j)

   1    2        0.046485       -0.003939     0.096910


Exactly the same. Transform the above results to PE and CI:
PE: 1.047582365
CI: 0.996068748 to 1.101761211

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