假设有如下数据集:
data a;
input Treatment y @@;
datalines;
1 17 1 28 1 19 1 21 1 19
1 43 1 30 1 39 1 44 1 44
1 16
2 21 2 21 2 24 2 25
2 39 2 45 2 42 2 47
2 19 2 22 2 16
3 22 3 30 3 33 3 31
3 46
3 26 3 31 3 26 3 33 3 29 3 25
;
proc glm data=a;
class Treatment ;
model y = Treatment/ss3;
lsmeans Treatment/cl alpha=0.05 pdiff stderr;
run;
quit;
结果:
Least Squares Means for effect Treatment
Pr > |t| for H0: LSMean(i)=LSMean(j)
Dependent Variable: y
i/j 1 2 3
1 0.9833 0.8017
2 0.9833 0.8179
3 0.8017 0.8179
Treatment y LSMEAN 95% Confidence Limits
1 29.090909 22.873802 35.308016
2 29.181818 22.964711 35.398925
3 30.181818 23.964711 36.398925
Least Squares Means for Effect Treatment
Difference
Between 95% Confidence Limits for
i j Means LSMean(i)-LSMean(j)
1 2 -0.090909 -8.883227 8.701408
1 3 -1.090909 -9.883227 7.701408
2 3 -1.000000 -9.792317 7.792317
删去数据集中treatment 3 的数据:
data b;
set a;
where treatment=1 or treatment=2;
run;
proc glm data=b;
class Treatment ;
model y = Treatment/ss3;
lsmeans Treatment/cl alpha=0.05 pdiff stderr;
run;
quit;
结果为:
The GLM Procedure
Least Squares Means
H0:LSMean1=
Standard H0:LSMEAN=0 LSMean2
Treatment y LSMEAN Error Pr > |t| Pr > |t|
1 29.0909091 3.4775549 <.0001 0.9854
2 29.1818182 3.4775549 <.0001
Treatment y LSMEAN 95% Confidence Limits
1 29.090909 21.836857 36.344962
2 29.181818 21.927766 36.435871
Least Squares Means for Effect Treatment
Difference
Between 95% Confidence Limits for
i j Means LSMean(i)-LSMean(j)
1 2 -0.090909 -10.349689 10.167870
请问: 同样是treatment 1 和 treatment 2 进行比较,为什么两个结果中的置信区间和P值却不一样?
结果1: (-8.883227 , 8.701408)
结果2: ( -10.349689, 10.167870)
请问LSmeans置信区间的计算方法是什么?
十分感谢!