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st: svyratio to svylogit


From   Ricardo Ovaldia <ovaldia@yahoo.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: svyratio to svylogit
Date   Wed, 7 Apr 2004 11:12:47 -0700 (PDT)

Dear all,

A colleague has a survey data set of hospital
discharges and is using Stata's -svy- commands for
analysis. He first –svyset-s the data and then he uses
–svyratio- and –lincom- to compare discharge rates for
two different years. The question is how can he set
this up as a –svylogit- model? I am not very familiar
with the –svy- commands but I told him that I would
ask the list. Here is his code and results:

. svyset [pweight=cwt], strata(stratum) psu(psu)
fpc(fpc)
pweight is cwt
strata is stratum
psu is psu
fpc is fpc


. svyratio case/inhosp, by (year)

Survey ratio estimation

pweight:  cwt                                    
Number of obs    =    310076
Strata:   stratum                                
Number of strata =        52
PSU:      psu                                    
Number of PSUs   =      2468
FPC:      fpc                                    
Population size  = 1409426.4

------------------------------------------------------------------------------
Ratio     Subpop. |   Estimate    Std. Err.   [95%
Conf. Interval]        Deff
------------------+-----------------------------------------------------------
case/inhosp       |
       year==1997 |   .0003062    .0000268    .0002536
   .0003589    .4295543
       year==2000 |   .0003311    .0000325    .0002673
   .0003949    .6767698
------------------------------------------------------------------------------
Finite population correction (FPC) assumes simple
random sampling without 
replacement of PSUs within each stratum with no
subsampling within PSUs.
Weights must represent population totals for deff to
be correct when
using an FPC.  Note: deft is invariant to the scale of
weights.

. lincom [1]1 - [1]2

 ( 1)  [1]1997 - [1]2000 = 0

------------------------------------------------------------------------------
       Ratio |   Estimate   Std. Err.      t    P>|t| 
   [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0000249   .0000422    -0.59   0.555 
  -.0001076    .0000578
------------------------------------------------------------------------------

Thank you in advance,
Ricardo.


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