st: Confidence intervals for survey data from the estimation matrices

["Darren White" <darrenm.white@health.qld.gov.au>]

Hello,

I am attempting to compile estimate tables directly from STATA's temporary estimate matrices, however none of the listed matrices after command: ereturn list (below) contain the confidence intervals that are displayed using the svy: command in STATA (table below). Also the estimate variance matrix e(V) and the square root e(V) x 1.96 +/- give the estimates in the automatic estimate display ( below at bottom) after some renaming of the e(b) and e(V) matrices but these are different to those returned form the svy: tab command.

Can anyone tell me how STATA arrives at the confidence interval estimates using the svy: tab command and where they could be found in the matrix environment? Alternatively how would I replicate the calculation routine for survey data using the variance provided in the e(V) matrix? The e(b) matrix has the same percentage estimates as returned form the svy: tab agecat bmicat, ci command 

Any help or suggestions would be greatly appreciated

Darren White
Population Epidemiology Unit
Queensland Health
Brisbane
Australia

___________________________________________________________________
. svy: tab  agecat bmicat, ci per
(running tabulate on estimation sample)

Number of strata   =         1                  Number of obs      =         7
Number of PSUs     =         7                  Population size    =         7
                                                Design df          =         6

-------------------------------------------------
   bmicat | percentages           lb           ub
----------+--------------------------------------
        1 |       42.86               9.06        84.95
        2 |       57.14             15.05        90.94
           | 
  Total |         100                          
-------------------------------------------------
_____________________________________________________________________
. ereturn list

scalars:
             e(stages) =  1
             e(census) =  0
          e(singleton) =  0
      e(N_strata_omit) =  0
               e(df_r) =  6
                  e(N) =  7
           e(N_strata) =  1
              e(N_psu) =  7
              e(N_pop) =  7
                  e(r) =  1
                  e(c) =  2
              e(total) =  7
             e(mgdeff) =  .
            e(cvgdeff) =  .
               e(rank) =  1

macros:
            e(cmdline) : "svy : tab  agecat bmicat, ci per"
                e(cmd) : "tabulate"
             e(prefix) : "svy"
            e(cmdname) : "tabulate"
       e(marginsnotok) : "_ALL"
            e(predict) : "_no_predict"
          e(estat_cmd) : "svy_estat"
             e(colvar) : "bmicat"
             e(rowvar) : "agecat"
             e(setype) : "cell"
            e(vcetype) : "Linearized"
                e(vce) : "linearized"
              e(wtype) : "pweight"
               e(wvar) : "weight"
               e(wexp) : "= weight"
         e(singleunit) : "missing"
             e(depvar) : "Mean"
         e(properties) : "b V"

matrices:
                  e(b) :  1 x 2
                  e(V) :  2 x 2
          e(V_srs_col) :  2 x 2
           e(Deft_col) :  1 x 2
           e(Deff_col) :  1 x 2
          e(V_srs_row) :  1 x 1
           e(Deft_row) :  1 x 1
           e(Deff_row) :  1 x 1
              e(V_srs) :  2 x 2
               e(Deft) :  1 x 2
               e(Deff) :  1 x 2
              e(V_col) :  2 x 2
              e(V_row) :  1 x 1
                e(Col) :  1 x 2
                e(Row) :  1 x 1
               e(Prop) :  1 x 2
                e(Obs) :  1 x 2
  e(_N_strata_certain) :  1 x 1
   e(_N_strata_single) :  1 x 1
          e(_N_strata) :  1 x 1
_________________________________________________________________________________________
.	ereturn post b V

.	ereturn display
						
	Coef.	Std. Err.	z	P>z	[95% Conf.	Interval]
						
	p11    .4285714	.2020305	2.12	0.034	.0325989	.8245439
	p12    .5714286	.2020305	2.83	0.005	.1754561	.9674011
						
________________________________________________________________________________________

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