I tried these PROCs in their most simple form and got different t-stats and StdErr. Why so? Here is my data and code:
*Get the dataset;
filename foo1 URL "http://www.kellogg.northwestern.edu/faculty/petersen/htm/papers/se/test_data.txt";
data ds;
infile foo1;
input firmid year x y;
run;
*Now run different methods;
*Normal SE;
proc reg data=ds;
model y = x;
ods output ParameterEstimates=temp0 fitstatistics=fit0;
run;
*Using PROC SURVEYREG with no special specs;
proc surveyreg data=ds;
model y = x / solution;
ods output ParameterEstimates=temp1 fitstatistics=fit1;
run;quit;
I don't think SURVEYREG computes the standard errors the same as REG.
From the documentation (which you should always check first):
PROC SURVEYREG uses elementwise regression to compute the regression coefficient estimators by generalized least squares estimation. The procedure assumes that the regression coefficients are the same across strata and primary sampling units (PSUs). To estimate the variance-covariance matrix for the regression coefficients, PROC SURVEYREG uses either the Taylor series (linearization) method or replication (resampling) methods to estimate sampling errors of estimators, based on complex sample designs.
I don't think SURVEYREG computes the standard errors the same as REG.
From the documentation (which you should always check first):
PROC SURVEYREG uses elementwise regression to compute the regression coefficient estimators by generalized least squares estimation. The procedure assumes that the regression coefficients are the same across strata and primary sampling units (PSUs). To estimate the variance-covariance matrix for the regression coefficients, PROC SURVEYREG uses either the Taylor series (linearization) method or replication (resampling) methods to estimate sampling errors of estimators, based on complex sample designs.
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