Fixed or random effect [🇷 for BE/BA]
Hello All,
Recently we got one query from WHO for 2x2 crossover study "Please take into account that if a mixed effect ANOVA model with the main effects of treatment, period and sequence as fixed effect and subjects nested within sequence as random effect is going to be used, as defined in the protocol, in SAS this refers to PROC MIXED as defined in the FDA guidelines. However, the protocol states at the same time that the sequence effect will be tested using the subjects nested within sequence mean square from the ANOVA as the error term. All other main effects will be tested against the residual error (mean square error/MSE) from the ANOVA as the error term. This refers to PROC GLM of SAS. This inconsistency should be corrected."
As per some experts if we want to keep sub(seq) as a error term for testing seq then it should be random rather than fixed.
But as I understand all effects in the PROC GLM are fixed including sub(seq).
Can anybody help me out?
Thanks in advance.
Recently we got one query from WHO for 2x2 crossover study "Please take into account that if a mixed effect ANOVA model with the main effects of treatment, period and sequence as fixed effect and subjects nested within sequence as random effect is going to be used, as defined in the protocol, in SAS this refers to PROC MIXED as defined in the FDA guidelines. However, the protocol states at the same time that the sequence effect will be tested using the subjects nested within sequence mean square from the ANOVA as the error term. All other main effects will be tested against the residual error (mean square error/MSE) from the ANOVA as the error term. This refers to PROC GLM of SAS. This inconsistency should be corrected."
As per some experts if we want to keep sub(seq) as a error term for testing seq then it should be random rather than fixed.
But as I understand all effects in the PROC GLM are fixed including sub(seq).
Can anybody help me out?
Thanks in advance.
—
Kumar Naidu
Kumar Naidu
Complete thread:
- R code for analyzing classical 2X2 crossover designed bioequivalence data lizhao 2016-01-22 00:13 [🇷 for BE/BA]
- R code for analyzing classical 2X2 crossover designed bioequivalence data ElMaestro 2016-01-22 00:59
- R code for analyzing classical 2X2 crossover designed bioequivalence data lizhao 2016-01-22 01:26
- On random effects and bogus statements ElMaestro 2016-01-22 12:13
- FDA 'own' SAS code for 2x2 d_labes 2016-01-27 09:57
- FDA 'own' SAS code for 2x2 nobody 2016-01-27 10:09
- OT: PM to ElMaestro Helmut 2016-01-27 13:39
- On coffee and such... ElMaestro 2016-01-27 13:47
- FDA 'own' SAS code for 2x2 nobody 2016-01-27 10:09
- Geometric means ± SD Helmut 2016-01-27 13:51
- Geometric means ± SD nobody 2016-01-27 15:20
- Money makes the world go ’round Helmut 2016-01-27 16:11
- Money makes the world go ’round nobody 2016-01-27 16:31
- Fixed or random effectkumarnaidu 2016-11-04 14:05
- PROC GLM fixes Subject mittyri 2016-11-04 23:00
- PROC GLM fixes Subject kumarnaidu 2016-11-05 05:22
- PROC GLM fixes Subject mittyri 2016-11-05 10:13
- PROC GLM fixes Subject kumarnaidu 2016-11-07 06:24
- PROC GLM fixes Subject mittyri 2016-11-07 11:57
- PROC GLM fixes Subject kumarnaidu 2016-11-07 12:42
- PROC GLM fixes Subject mittyri 2016-11-07 11:57
- PROC GLM fixes Subject kumarnaidu 2016-11-07 06:24
- PROC GLM fixes Subject mittyri 2016-11-05 10:13
- PROC GLM fixes Subject kumarnaidu 2016-11-05 05:22
- PROC GLM fixes Subject mittyri 2016-11-04 23:00
- Fixed or random effectkumarnaidu 2016-11-04 14:05
- Money makes the world go ’round nobody 2016-01-27 16:31
- Money makes the world go ’round Helmut 2016-01-27 16:11
- Geometric means ± SD Ben 2016-11-08 21:20
- Misunderstanding Helmut 2016-11-09 15:29
- Misunderstanding Ben 2016-11-14 19:40
- RTFM Helmut 2016-11-14 21:50
- Misunderstanding Ben 2016-11-14 19:40
- Misunderstanding Helmut 2016-11-09 15:29
- Geometric means ± SD nobody 2016-01-27 15:20
- FDA 'own' SAS code for 2x2 d_labes 2016-01-27 09:57
- On random effects and bogus statements ElMaestro 2016-01-22 12:13
- R code for analyzing classical 2X2 crossover designed bioequivalence data lizhao 2016-01-22 01:26
- R code for analyzing classical 2X2 crossover designed bioequivalence data ElMaestro 2016-01-22 00:59