comparison with SAS [🇷 for BE/BA]
❝ • 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
Complete thread:
- bear for imbalanced data set Oiinkie 2013-01-16 16:42 [🇷 for BE/BA]
- bear for imbalanced data set yjlee168 2013-01-16 17:25
- bear for imbalanced data set Oiinkie 2013-01-16 19:18
- bear for imbalanced data set Oiinkie 2013-01-16 19:19
- bear for imbalanced data set yjlee168 2013-01-16 19:43
- bear for imbalanced data set ElMaestro 2013-01-16 22:10
- bear for imbalanced data set Oiinkie 2013-01-22 13:28
- comparison with PHX Helmut 2013-01-22 15:06
- comparison with PHX Oiinkie 2013-01-23 12:58
- comparison with PHX Oiinkie 2013-01-23 15:07
- comparison with SASyicaoting 2013-02-15 18:58
- comparison with PHX Oiinkie 2013-01-23 12:58
- bear for imbalanced data set yjlee168 2013-01-22 19:57
- ANOVA_stat.txt is correct. → bear for imbalanced data set yjlee168 2013-03-01 01:01
- bear for incomplete data set? yjlee168 2013-03-15 07:58
- comparison with PHX Helmut 2013-01-22 15:06
- bear for imbalanced data set yjlee168 2013-01-16 19:43
- imbalanced or incomplete data yicaoting 2013-02-15 18:48
- incomplete data Helmut 2013-02-16 14:41
- bear for imbalanced data set yjlee168 2013-01-16 17:25