Steven
The primary sampling units (PSUs) are the projects and ultimate sample units
are the households. In the first stage we selected a number of projects. In
the second stage we selected 3 households in each project. We have in the
sample 318 beneficiaries and 404 controls.
My concern is that by not considering the logit model with weights
representing the expansion of the sample to the population, making it more
representative (because the sample is not self-weighted) I will eventually
estimate the average treatment effects with bias. But when I use weights in
logit models estimations the matched samples does not balance. It is very
strange that in the command psmatch2 there is not an option provided for
weighting. In the command pscore this option exists. But the estimation
commands coupled with the latter command (atts, attr) does not have this
option. My question is: is it necessary to use weights in the estimation of
atts when I used this in the balancing tests?
Henrique
-----Mensagem original-----
De: [email protected]
[mailto:[email protected]] Em nome de Steven Samuels
Enviada em: sexta-feira, 25 de abril de 2008 08:57
Para: [email protected]
Assunto: Re: st: using pscore and pstest
-
Henrique, how were the program and beneficiary sub-samples selected?
Are the beneficiary and control sampling units projects or
households? Was there control of the number of the beneficiary and
control units--for example to achieve approximately equal numbers, or
minimum numbers of each?
-Steven
On Apr 24, 2008, at 8:32 PM, Henrique Neder wrote:
> Dear
> 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 fweights form, calculated as the
> ratio -
> 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 in a previous survey (that
> is, the
> second survey was a subsample of the projects in 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 non weighted logit regressions
> 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 logit regressions to estimate the atts?
>
> 2 - It is adequate to test balancing with pstest and pscore without
> weights
> and estimate the atts with propensities scores obtained through
> weighted
> logit regressions?
>
> 3 - I read that a sample proposal is 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 considering the representation of the program effects in the
> universe?
>
> Best regards
>
> Henrique Dantas Neder
> Universidade Federal de Uberl�ndia - Minas Gerais - Brazil
>
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