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st: nested random effects anova
Dear statalist-participants,
I'm looking for an answer on the following question and hope to find it
here.
I run a two-way nested anova. My dependent variable is f1 and I'm
searching for an effect of the interviewer gender and respondent gender
on the respondent behavior (f1). so respondents are nested within
interviewers.
I get different results depending on the residual error I choose.
Here are my outputs:
. anova f1 sex_int / sex|sex_int /
Number of obs = 3528 R-squared = 0.0138
Root MSE = 2.34259 Adj R-squared = 0.0129
Source | Partial SS df MS F Prob > F
------------+----------------------------------------------------
Model | 269.922069 3 89.9740231 16.40 0.0000
sex_int | 218.147357 1 218.147357 12.56 0.0712
sex|sex_int | 34.7409223 2 17.3704612
------------+----------------------------------------------------
sex|sex_int | 34.7409223 2 17.3704612 3.17 0.0423
Residual | 19338.7718 3524 5.4877332
------------+----------------------------------------------------
Total | 19608.6939 3527 5.55959566
. anova f1 sex_int sex|sex_int
Number of obs = 3528 R-squared = 0.0138
Root MSE = 2.34259 Adj R-squared = 0.0129
Source | Partial SS df MS F Prob > F
------------+----------------------------------------------------
Model | 269.922069 3 89.9740231 16.40 0.0000
|
sex_int | 218.147357 1 218.147357 39.75 0.0000
sex|sex_int | 34.7409223 2 17.3704612 3.17 0.0423
|
Residual | 19338.7718 3524 5.4877332
------------+----------------------------------------------------
Total | 19608.6939 3527 5.55959566
My question is: which output should I take for calculating intraclass
correlation coefficient? In the first case my major effect (interviewer
gender') is not significant. I would prefer the second one. By are there
some rules in this case?
Thank you.
Inna Khousnoullina
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