Statalist


[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

RE: st: Multiple mean comparisons with complex survey design - Richard


From   "Sven Klingemann" <sklingem@uic.edu>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Multiple mean comparisons with complex survey design - Richard
Date   Tue, 19 Feb 2008 14:11:49 -0600

Thanks Richard. I guess I got confused by the Stata Manual:

" mtest[(opt)] specifies that tests be performed for each condition
  separately.  opt specifies the method for adjusting p-values for
  multiple testing.  Valid values for opt are

                bonferroni    Bonferroni's method
                holm          Holm's method
                sidak         Sidak's method
                noadjust      no adjustment is to be made

        Specifying mtest without an argument is equivalent to
        mtest(noadjust). 
-->	 mtest is not allowed after svy: mean, svy: total,
        or svy: ratio.

(?)
-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Richard Williams
Sent: Tuesday, February 19, 2008 2:09 PM
To: statalist@hsphsun2.harvard.edu; statalist@hsphsun2.harvard.edu
Subject: Re: st: Multiple mean comparisons with complex survey design

At 02:28 PM 2/19/2008, Sven Klingemann wrote:
>Hi,
>
>I would like to compare means across six groups and adjust the significance
>test accordingly. I noticed that the "mtest" command (and associated
>Bonferroni option) is not allowed after the svy:mean command. Is there any
>recommended alternative for multiple group comparisons using a complex
>survey design?
>
>Thank you!

At the risk of being accused of plagiarizing someone else's words - 
Yes You Can  :).  Example:

. webuse nhanes2f, clear

. svy: mean health, over(race)
(running mean on estimation sample)

Survey: Mean estimation

Number of strata =      31          Number of obs    =   10335
Number of PSUs   =      62          Population size  = 1.2e+08
                                     Design df        =      31

         White: race = White
         Black: race = Black
         Other: race = Other

--------------------------------------------------------------
              |             Linearized
         Over |       Mean   Std. Err.     [95% Conf. Interval]
-------------+------------------------------------------------
health       |
        White |   3.663833   .0252884      3.612257    3.715409
        Black |   3.117221   .0379095      3.039904    3.194538
        Other |   3.510359    .080302      3.346582    3.674136
--------------------------------------------------------------

. test [#1]White = [#1]Black = [#1]Other, mtest(b)

Adjusted Wald test

  ( 1)  [health]White - [health]Black = 0
  ( 2)  [health]White - [health]Other = 0

---------------------------------------
        |    F(df,30)     df       p
-------+-------------------------------
   (1)  |      141.48      1     0.0000 #
   (2)  |        3.65      1     0.1304 #
-------+-------------------------------
   all  |       69.05      2     0.0000
---------------------------------------
          # Bonferroni adjusted p-values




-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME:   (574)289-5227
EMAIL:  Richard.A.Williams.5@ND.Edu
WWW:    http://www.nd.edu/~rwilliam

*
*   For searches and help try:
*   http://www.stata.com/support/faqs/res/findit.html
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/


*
*   For searches and help try:
*   http://www.stata.com/support/faqs/res/findit.html
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/



© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index