# st: crude binary analysis

 From "Sahid Hocine" To statalist Subject st: crude binary analysis Date Sun, 24 Aug 2008 15:29:13 +0100

```Dear Stalister,

I have a question regarding Stata 10 being a newbee on the field.

I am analyzing a DHS data set *(survey) and for  the bivariate crude
analysis I am used to   tabodds  however it is not supported by the
svy , so I guess  I would have to use the logistic command for binary
analysis but the output is not what I want i.e a crude odd ratio by
category. Can I proceed with the svy or the stratification is the only
solution?

Sahid

. svy:logistic sd107 v130
(running logistic on estimation sample)

Survey: Logistic regression

Number of strata   =        35                  Number of obs      =      5600
Number of PSUs     =      4823                  Population size    = 5638.5227
Design df          =      4788
F(   1,   4788)    =      0.77
Prob > F           =    0.3795

------------------------------------------------------------------------------
|             Linearized
sd107 | Odds Ratio   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
v130 |   .5262408   .3844291    -0.88   0.380     .1256632    2.203743
------------------------------------------------------------------------------

. svy:tabodds sd107 v130
tabodds is not supported by svy with vce(linearized); see help svy
estimation for a list of Stata estimation commands
that are supported by svy
r(322);

. :tabodds sd107 v130
unrecognized command:  : invalid command name
r(199);

. tabodds sd107 v130

--------------------------------------------------------------------------
v130  |      cases     controls       odds      [95% Conf. Interval]
------------+-------------------------------------------------------------
muslim |         81         5218    0.01552        0.01246   0.01933
christian |          3          298    0.01007        0.00323   0.03139
--------------------------------------------------------------------------
Test of homogeneity (equal odds): chi2(1)  =     0.55
Pr>chi2  =   0.4602

Score test for trend of odds:     chi2(1)  =     0.55
Pr>chi2  =   0.4602
*
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```