I'm trying to compare the estimated SD of "between" and "within" variances
for two groups, a treatment group and a comparison group. Is there a
suggested way to recover the standard errors in order to test the
hypothesis that (estimated SD between effect Treatment group) = (estimated
SD between effect Comparison group) ?
For example:
The output from loneway for the treatment group is:
loneway score00nm schid if std==6 & teso==0 & male==0 & treat==1
One-way Analysis of Variance for score00nm:
Number of obs = 345
R-squared = 0.5995
Source SS df MS F Prob > F
-------------------------------------------------------------------------
Between schid 160.00569 30 5.3335229 15.67 0.0000
Within schid 106.89158 314 .34041906
-------------------------------------------------------------------------
Total 266.89727 344 .77586416
Intraclass Asy.
correlation S.E. [95% Conf. Interval]
------------------------------------------------
0.57069 0.07739 0.41900 0.72238
Estimated SD of schid effect .6727015
Estimated SD within schid .5834544
Est. reliability of a schid mean 0.93617
(evaluated at n=11.03)
and for the comparison group is :
loneway score00nm schid if std==6 & teso==0 & male==0 & treat==0
One-way Analysis of Variance for score00nm:
Number of obs = 404
R-squared = 0.5171
Source SS df MS F Prob > F
-------------------------------------------------------------------------
Between schid 169.09683 33 5.1241465 12.01 0.0000
Within schid 157.89682 370 .42674816
-------------------------------------------------------------------------
Total 326.99365 403 .81139864
Intraclass Asy.
correlation S.E. [95% Conf. Interval]
------------------------------------------------
0.48329 0.07764 0.33111 0.63546
Estimated SD of schid effect .6317745
Estimated SD within schid .6532596
Est. reliability of a schid mean 0.91672
(evaluated at n=11.77)
I want to test that hypothesis that 0.6727 = 0.63177
but don't know how to recover the standard errors.
Thanks,
Rebecca
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