thanks!
Jade <[email protected]> is analyzing survey data, and wants to know the
> degrees of
> freedom used with the reported t and F tests:
>
>> I'm trying to figure out how to compute the df for t and F in these
>> results (below). I'm not sure what is being used as N? Any direction
>> would be helpful.
>>
>> . svyreg fac_etoh bio_sex age dep_sum
>>
>> Survey linear regression
>>
>> pweight: gswgt1 Number of obs =
>> 1348
>> Strata: region Number of strata =
>> 4
>> PSU: psuscid Number of PSUs =
>> 92
>> Population size =
>> 1138728.8
>> F( 3, 86) =
>> 11.46
>> Prob > F =
>> 0.0000
>> R-squared =
>> 0.0448
>> ------------------------------------------------------------------------------
>> fac_etoh | Coef. Std. Err. t P>|t| [95% Conf.
>> Interval]
>> -------------+----------------------------------------------------------------
>> bio_sex | .3015771 .0693058 4.35 0.000 .1638464
>> .4393079
>> age | -.0744264 .0298961 -2.49 0.015 -.1338386
>> -.0150142
>> dep_sum | -.0153594 .0047195 -3.25 0.002 -.0247383
>> -.0059805
>> _cons | .919665 .5149458 1.79 0.078 -.1036815
>> 1.943011
>
> The numerator and denominator df used in the model F test are reported in
> the
> output.
>
> Numerator: 3 = df_m, one for each indepvar in the model
> Denominator: 86 = (92 - 4) - (3 - 1) = df_r - (df_m - 1)
>
> Here df_r is the design degrees of freedom, which is documented in the
> Survey
> manual to be N - L; number of PSU's minus number of Strata.
>
> For the individual t-tests, df_r is used to compute the p-values.
>
> --Jeff
> [email protected]
> *
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>
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