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st: using pscore and pstest

From   "Henrique Neder" <>
To   <>
Subject   st: using pscore and pstest
Date   Wed, 23 Apr 2008 09:01:56 -0300

Dear Statalists

I have a problem with the use of the pscore and pstest commands. My sample
is a cluster sample in that the sample observations are selected by the
followings steps:

1 - The survey is made in five States and in each State we selected some
number of projects (the primary sample units - PSUs) in all sub-regions of
this State.

2 - In each project we selected a fixed number of households.

The sample weights are of the form fweights calculated as the number of
households in each sub-region (universe) / the number of households
(observations) selected in the sample and inside that same sub-region.
Alternatively, we have a pweight, because the projects were selected with
PPS (with probability proportionate to the number of the households in each
project in the universe). This sample of projects were selected as a
sub-sample of the projects of a previous survey (that is, the second survey
was a subsample of the projects of the first survey). 
We have in the survey two subsamples: a sub-sample of a program
beneficiaries and a control sub-sample.   

I executed the commands pstest and pscore using a logit model with y = dummy
of participation program and yi (covariates) = variables that explain the
participation. In the first execution I executed the commands with
propensities scores obtained through weighted logits and some models are
balanced in the pstest and pscore commands. But when I use the weighted
logits the balancing tests are not satisfied (the pscore command stops and
in the pstest the covariates are unbalanced with small p-values and the
conjoint chi-square test with low p-value, too). 

My questions are:

1 - It is necessary to execute the commands with propensities scores
obtained through weighed logits?

2 - It is adequate to test balance with pstest and pscore without weights
and estimate the atts with weights?

3 - I read that a sample proposal are to weight the treated observations
with the weight = 1 / propensity and the untreated with the weight = 1/(1 -
propensity).  In my case is this solution appropriate? Does it correct the
estimates to consider the representation of the program effects in the

Best regards

Henrique Dantas Neder
Universidade Federal de Uberlandia - Minas Gerais - Brazil

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