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st: DHS survey data and Logistic regression - Response from Measure DHS


From   Olalekan Uthman <uthlekan@yahoo.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: DHS survey data and Logistic regression - Response from Measure DHS
Date   Wed, 1 Aug 2007 09:48:27 -0700 (PDT)

Reply from Measure DHS

============
Dear Olalekan,
             Any of these methods are acceptable,
depending on your
knowledge & experience of regressions. 
Some analysts prefer to use the weights while others
do not.  For
example, the main author of WP #31 always uses the DHS
weights, while
the author of the DHS Guide to statistics prefers not
to.
 
I suggest investigating the appropriateness of weights
in regression
analysis to come to a decision that you're comfortable
with.

=============
Method I - From DHS statistics guide:
"Use of sample weights is inappropriate for estimating
relationships, such as regression and correlation
coefficients". 

Reference: 
http://www.measuredhs.com/help/Datasets/sampling_weights.htm

Method II - From WP #31
"For all models, our analysis accounts
for complex DHS survey design to estimate efficient
regression coefficients and robust standard errors
adjusted for intra-cluster correlation, and
sampling weights are applied in accordance with
standard DHS procedures to ensure the
representativeness of the samples."

Reference:
Mishra, Vinod, et al. 2007. A study of the association
of HIV
infection with wealth in sub-Saharan Africa. DHS
working paper no. 31.
Calverton: Macro International.
http://www.measuredhs.com/pubs/pub_details.cfm?ID=638

Olalekan Uthman

--- Emma Slaymaker <Emma.Slaymaker@lshtm.ac.uk> wrote:

> Dear Olalekan,
> 
> You asked about accounting for the survey design
> when analysing DHS
> data. You should account for the stratification and
> the clustering
> whenever you calculate standard errors- if you do
> not, the standard
> errors will not be correct.  I always include the
> weighting information
> since I usually want to know if associations are
> likely to be true of
> the population the survey is designed to represent
> (with weights) and
> not just the survey sample (without weights).  Once
> you have accounted
> for the stratification and clustering you don't
> really lose anything by
> also accounting for the weights since you are
> already working with
> robust standard errors.
> I don't know of a reason why it would be
> inappropriate to use sample
> weights in a regression analysis- but that may well
> be ignorance on my
> part.
> Hope this helps,
> Emma
> 
> >>> Olalekan Uthman <uthlekan@yahoo.com> 30/07/07
> 15:49 >>>
> Dear Stata users,
> 
> I am trying to run a logistic regression using
> Measure
> DHS survey data. Quoting from DHS statistics guide:
> "Use of sample weights is inappropriate for
> estimating
> relationships, such as regression and correlation
> coefficients.
> 
> I am not sure whether to ignore the psu and strata
> also when running the logistic regression.
> 
> 
> Can I just use
> 
> xi: logistic bmi i.edu
> 
> instead of:
> 
> svyset psu [pw=weight], strata(strata)
> 
> xi: svy: logistic bmi i.edu
> 
> 
> 
>
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