[R] HLM Model
Belle
ping.yi at gmail.com
Fri Jan 28 00:52:13 CET 2011
Hi Harold:
I know the outputs are different between SAS and R, but the results that I
got have big difference.
Here is part of the result based on the SAS code I provided earlier:
Cov Parm Subject Estimate Error
Value Pr > Z
UN(1,1) team 177.53 273.66
0.65 0.2583
Residual 2161.15
67.1438 32.19 <.0001
Solution for Fixed
Effects
Standard
Effect pairs grade school Estimate Error
DF t Value Pr > |t|
Intercept 638.82 4.6127
5 138.49 <.0001
trt -0.2955
3.4800 5 -0.08 0.9356
pairs 1 0.1899 7.1651
5 0.03 0.9799
pairs 2 31.1293 6.0636
5 5.13 0.0037
.
.
.
In R:
library(lme4)
mixed<- lmer(Pre~trt+pairs+grade+school+(1|team), test)
result:
Random effects:
Groups Name Variance Std.Dev.
team (Intercept) 568.61 23.846
Residual 2161.21 46.489
Fixed effects:
Estimate Std. Error t value
(Intercept) 540.402 43.029 12.559
trt 7.291 13.084 0.557
pairs -3.535 6.150 -0.575
In random effect, the variance of team in SAS is 177.53, but it is 568.61 in
R. Also I have negative estimate for trt in SAS but positive estimate for
trt in R. I am wondering how this happened, and how can I solve this problem
so that I can get similar result from both software.
Also does R provides result for fixed effect of each level? For example, the
result of pair1, pair2,pair3,..., and grade1, grade2, grade3,...
--
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