→ bmka: outcomes in some subgroups are all zero or one. 10/04 20:30
→ bmka: or the subgoups defined by a covariate are subsets of 10/04 20:35
→ bmka: those defined by another covariate. You might want to 10/04 20:35
→ bmka: pay special attention to PreVac40_B (I suppose this 10/04 20:36
→ bmka: indicates that a subject's baseline antibody titer is 10/04 20:37
→ bmka: >=1:40), and other covariates that may affect antibody 10/04 20:38
→ bmka: level, including gender and age. 10/04 20:38
感謝您的回覆,您提的這兩個問題我們都有想過,
現階段想嘗試解決第一個可能的問題-sparse data
不過查過許多SAS mannual和其他人的code都找不到解決方案...
※ 編輯: tokyo291 (140.116.52.59), 10/05/2014 19:55:01
→ bmka: 如果大部份的observation都是0,為什麼硬是要fit這個model 10/05 22:42
→ bmka: Consider reduce the number of covariates. 10/05 22:43