我有一套数据,我想做逻辑回归建模二元结果变量(治疗)的几率,阶段作为序数解释变量(0,1,2,3 ,4)。 Hba1c是一个连续变量。逻辑回归与序数解释变量
我的课堂陈述是否正确?
我该如何计算序数变量每个级别的比值比?
PROC LOGISTIC data=new;
class EyeID Therapy (ref ="0") Stage (param = ordinal) Gender (ref="M") Ethnicity (ref="C")/ param = ref;
model Therapy = Stage Gender age A1c Ethnicity;
oddsratio Stage;
run;
这是输出:
Odds Ratio Estimates and Wald Confidence Intervals
Odds Ratio Estimate 95% Confidence Limits
Stage 1 vs 0 0.873 0.547 1.394
Stage 2 vs 0 2.434 0.895 6.620
Stage 3 vs 0 0.915 0.431 1.941
Stage 4 vs 0 0.356 0.132 0.961
Stage 2 vs 1 2.788 0.980 7.935
Stage 3 vs 1 1.048 0.465 2.360
Stage 4 vs 1 0.408 0.144 1.156
Stage 3 vs 2 0.376 0.113 1.249
Stage 4 vs 2 0.146 0.038 0.567
Stage 4 vs 3 0.389 0.117 1.288
如果我在报告阶段为序变量,那么它是正确的,我创建这样一个表?
Stage 1 vs 0 0.873 0.547 1.394
Stage 2 vs 1 2.788 0.98 7.935
Stage 3 vs 2 0.376 0.113 1.249
Stage 4 vs 3 0.389 0.117 1.288
我不应该这样报告,对吗?这是如果阶段是绝对的?
Stage 1 vs 0 0.873 0.547 1.394
Stage 2 vs 0 2.434 0.895 6.62
Stage 3 vs 0 0.915 0.431 1.941
Stage 4 vs 0 0.356 0.132 0.961
序数模型的累积概率,与参考水平相比并非如此。那是你在找什么? – Reeza
@Reeza我已更新该帖子。我是否正确解释输出? – ybao