q**t
发帖数: 36 | 1 I met a problem to test a nested design with 4 levels. There are one fixed
effect x1.
random effects are nested A, B(A), C( B*A)
For each subgroup C, there are D repeated measurements.
I need to estimated the variance within each subgroup C. Also
I want to test for each subgroup B, the variance within subgroup C
heterogeneous or not?
To estimate the variance within C, here is my code:
*** I try to test the heterogeneity using covtest;
proc mixed data= data4analysis cl covtest ;
clas... 阅读全帖 |
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s*******e
发帖数: 226 | 3 Below is my SAS code for the problem. As you said, u_i would be
estimated as u_i~N(a,simga)if the intercept is specified as u_i (random)
only, then the coefficient of covariates should not change no matter a
is included or not. But it is not the case in my results.
"
proc mixed data=temp method=reml covtest ;
class permno year;
model loggev= lagq2 compiii softyr hardyr compiii*lagq2 softyr*lagq2
hardyr*lagq2 log_market_value diver pcsale_ratio
stockindexrt/ solution noint;
*noint is specified |
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z**********i
发帖数: 12276 | 4 终于用PROC MIXED 写了个CODE,但没有搞的很清,该怎么解释OUTPUT.
proc mixed data=bmi covtest;
class sex question7 question45 country;
model BMI=age sex question7 question45 HDI age*HDI sex*HDI question7*HDI
question45*HDI/s;
random int /type=un subject=country s;
run;
是个SURVEY的数据,BMI是DEPENDENT VARIABLE. AGE, SEX, QUESTION7, QUESTION45是
STUDENT LEVEL DATA,HDI是COUNTRY LEVEL.
一共有13个国家的数据.
哪里有类似的例子可以参照一下的.
多谢回复! |
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q**t
发帖数: 36 | 5 Design structure is like this:
level A : 1 2 .... 5
level B : a b c d l m
level C: x y z
level D repeat: 1 1 1
2 2 2
3 3 3
So all levels A, B, C are random and D is repeat
I thought the first code is more suitable for estimation of the variance
within each subgroup C ,for each group B. I might messed up here.
2nd one is not assume that A, B, C are random, but it can give me a covtes... 阅读全帖 |
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