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Re: st: RE: Ousout problem psmatch2


From   "Jason Zarmulski" <Jason.Zarmulski@mtox.de>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: Ousout problem psmatch2
Date   Tue, 21 Jun 2011 12:22:32 +0200

Hi Jan,

thanks a lot for your support, I changed it and my new output is:
:-)

. psmatch2 reldummy , outcome( stockprice2010) pscore(mypscore) neighbor(10) caliper(0.1) ate
----------------------------------------------------------------------------------------
        Variable     Sample |    Treated     Controls   Difference         S.E.   T-stat
----------------------------+-----------------------------------------------------------
  stockprice2010  Unmatched | 20.6236969   21.7278571  -1.10416018   2.08916252    -0.53
                        ATT | 20.6236969   20.4730466   .150650303   4.16715274     0.04
                        ATU | 21.7278571   17.8625509  -3.86530621            .        .
                        ATE |                          -.513405498            .        .
----------------------------+-----------------------------------------------------------
Note: S.E. does not take into account that the propensity score is estimated.

           | psmatch2:
 psmatch2: |   Common
 Treatment |  support
assignment | On suppor |     Total
-----------+-----------+----------
 Untreated |        84 |        84
   Treated |       424 |       424
-----------+-----------+----------
     Total |       508 |       508


To the attnd problem : I didnt install a package for attnd. Maybe it was with the"nnmatch ado" package

The differences between the psmatch2 and the attnd are still there....

This is the help attnd file:


Calculate the average treatment effect on the treated using nearest neighbor matching

            attnd outcome treatment [varlist] [weight] [if exp] [in range] [ ,
                  pscore(scorevar) logit index comsup detail bootstrap reps(#)
                  noisily dots ]

        fweights, iweights, and pweights are allowed; see help weights.


Description

    attnd estimates the average treatment effect on the treated (ATT) using nearest
    neighbor matching. attnd should be run after the correct propensity score
    specification; i.e., the one satisfying the balancing property has been found
    using, for example, pscore. If users do not provide a variable name for the
    propensity score, the propensity score is estimated based on the specification
    in varlist. Note that in this case the balancing property is not tested.

    It is left under the responsibility of the user to select the comsup option if
    the user provided propensity score has been estimated on a common support for
    treated and controls.  Otherwise, the ATT is estimated using also the
    observations outside the common support for which the propensity score may not
    be balanced.

    To save on computing time, nearest neighbors are not determined by comparing
    treated observations to every single control, but by first sorting all records
    by the estimated propensity score and then searching forward and backward for
    the closest control unit(s). If a treated unit forward and backward matches
    happen to be equally good, this program randomly draws (hence the letters "nd"
    for Nearest neighbor and random Draw) either the forward or backward matches.
    This approach is one of two computationally feasible options to obtain
    analytical standard errors while at the same time exploiting the very fast
    forward and backward search strategy. The second possibility is based on giving
    equal weight to the groups of forward and backward matches in case of equally
    good forward and backward matches and is performed by attnw. In practice, the
    case of multiple nearest neighbors should be very rare. In particular, if the
    set of X's contains continuous variables, in which case, both attnd and attnw
    should give equal results (except for bootstrapped standard errors). The
    likelihood of multiple nearest neighbors is further reduced if the propensity
    score is estimated and saved in double precision, which is what pscore does by
    default.

    The ATT is computed by averaging over the unit-level treatment effects of the
    treated where the control(s) matched to a treated observation is/are those
    observations in the control group that have the closest propensity score. If
    there are multiple nearest neighbors, the average outcome of those controls is
    used.


Options

    pscore(scorevar) specifies the name of the user-provided variable name for the
        estimated propensity score. If no name is provided the propensity score is
        estimated based on the specification in varlist.

    logit uses a logit model to estimate the propensity score instead of the default
        probit model when the option pscore(scorevar) is not specified by the user.
        Otherwise, no effect is produced.

    index requires the use of the linear index as the propensity score when the
        option pscore(scorevar) is not specified by the user.  Otherwise, no effect
        is produced.

    comsup restricts the computation of the ATT to the region of common support.

    detail displays more detailed output documenting the steps performed to obtain
        the final results.

    bootstrap bootstraps the standard error of the treatment effect.

    reps(#) specifies the number of bootstrap replications to be performed.  The
        default is 50.  This option produces an effect only if the bootstrap option
        is specified.

    noisily requests that any output from the replications be displayed.  This
        option produces an effect only if the bootstrap option is specified.

    dots requests that a dot be placed on the screen at the beginning of each
        replication.  This option produces an effect only if the bootstrap option is
        specified.


Remarks

    Please remember to use the update query command before running this program to
    make sure you have an up-to-date version of Stata installed.  Otherwise, this
    program may not run properly.

    The treatment has to be binary.

    When users do not specify their own previously estimated propensity score, the
    bootstrap encompasses the estimation of the propensity score based on the
    specification given by varlist. This procedure is actually recommended to
    account for the uncertainty associated with the estimation of the propensity
    score.  Even more so when the comsup option is specified because in this case
    the region of common support changes with every bootstrap sample, and
    bootstrapped standard errors pick up this uncertainty as well. So, typically
    users would first identify a specification satisfying the balancing property --
    using pscore -- and then provide exactly this specification in varlist and use
    bootstrapped standard errors.


Saved results

    The program stores the estimated treatment effect, its standard error, and the t
    statistic respectively in the scalars r(attnd), r(seattnd), and r(tsattnd).

    The number of treated and the number of controls are stored respectively in the
    scalars r(ntnd) and r(ncnd).

    The bootstrapped standard error and t statistic are stored respectively in the
    scalars r(bseattnd) and r(btsattnd).


Examples

    . attnd wage training age age2 exp exp2

    . attnd wage training age age2 exp exp2, boot reps(100) dots

    . attnd wage training age age2 exp exp2, logit boot reps(100)

    . attnd wage training age age2 exp exp2, comsup boot reps(100)


Authors

        Sascha O. Becker
        Center for Economic Studies, University of Munich

        Andrea Ichino
        Department of Economics, European University Institute, Florence

    Email so.b@gmx.net or andrea.ichino@iue.it if you observe any problems.


Acknowledgments

    The way to implement the propensity score estimation in the bootstrap procedure
    has been adapted from the psmatch program written by Barbara Sianesi (University
    College London and Institute for Fiscal Studies) Email: barbara_s@ifs.org.uk.


Also see

    Online:  help for pscore, atts, attr, attk, attnw (if installed), and bs.

              Further details on the analytical formulas and on the algorithms used
              in these programs can be found under http://www.sobecker.de or
              http://www.iue.it/Personal/Ichino.

Thanks
Jason


--- Ursprüngliche Nachricht ---
Von: Jan Bryla <JBR@finansraadet.dk>
Datum: 20.06.2011 20:14:03
An: "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Betreff: st: RE: Ousout problem psmatch2

> Jason, your first question seems easy to solve: I think your treatment variable
> and the outcome variable are identical. Recall the syntax for psmatch2, see
> -help psmatch2-.
>
> The second point left me a bit confused. Searching for -attnd- using -findit
> attnd- didn't really turn out any hints. Is -attnd- available from SSC? Maybe
> you can clarify your steps there? Maybe differences are due to the issue
> with the first question.
>
> Hope it helps
> Jan Bryla
>
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu]
> On Behalf Of Jason Zarmulski
> Sent: 20. juni 2011 16:45
> To: statalist@hsphsun2.harvard.edu
> Subject: st: Ousout problem psmatch2
>
> Dear Statalists,
> I got two problems, first one:
>
> I have a problem understanding the Output of my psmatch2 results. I'm new
> to
> this so it could be a trivial error, but I'm not sure. I wanted to do a
> nearest neighbor matching with replacement.
> My results are:
>
> . psmatch2 stockprice2010, outcome( stockprice2010) pscore(mypscore)
> neighbor(10) caliper(0.1) ate
> ----------------------------------------------------------------------------------------
>
>         Variable     Sample |    Treated     Controls   Difference
> S.E.   T-stat
> ----------------------------+-----------------------------------------------------------
>
>   stockprice2010  Unmatched |      1.628   .479999997    .99964329
> .000849677  1176.50
>                         ATT |       1.62   .689999992   .930000013
> .399478823     2.33
>                         ATU | .479999997   1.79500002   1.31500002
> .        .
>                         ATE |                           1.05833335
> .        .
> ----------------------------+-----------------------------------------------------------
>
> Note: S.E. does not take into account that the propensity score is
> estimated.
>
>  psmatch2: |   psmatch2: Common
>  Treatment |        support
> assignment | Off suppo  On suppor |     Total
> -----------+----------------------+----------
>  Untreated |         0          2 |         2
>    Treated |         1          4 |         5
>          2 |         0         11 |        11
>          3 |         0         12 |        12
>          4 |         0         17 |        17
>          5 |         0         34 |        34
>          6 |         0         15 |        15
>          7 |         0         19 |        19
>          8 |         0         18 |        18
>          9 |         0         17 |        17
>         10 |         0         18 |        18
>         11 |         0         13 |        13
>         12 |         0         13 |        13
>         13 |         0         20 |        20
>         14 |         0         23 |        23
>         15 |         0         23 |        23
>         16 |         0         10 |        10
>         17 |         0         13 |        13
>         18 |         0         10 |        10
>         19 |         0         11 |        11
>         20 |         0         11 |        11
>         21 |         0         10 |        10
>         22 |         0         10 |        10
>         23 |         0         11 |        11
>         24 |         0         10 |        10
>         25 |         0          7 |         7
>         26 |         0          9 |         9
>         27 |         0          6 |         6
>         28 |         0          7 |         7
>         29 |         0          4 |         4
>         30 |         0          7 |         7
>         31 |         0          6 |         6
>         32 |         0          7 |         7
>         33 |         0          7 |         7
>         34 |         0          5 |         5
>         35 |         0          6 |         6
>         36 |         0          6 |         6
>         37 |         0          6 |         6
>         38 |         0          5 |         5
>         39 |         0          4 |         4
>         40 |         0          4 |         4
>         41 |         0          9 |         9
>         42 |         0          7 |         7
>         43 |         0          5 |         5
>         44 |         0          1 |         1
>         45 |         0          1 |         1
>         46 |         0          1 |         1
>         47 |         0          1 |         1
>         48 |         0          3 |         3
>         49 |         0          4 |         4
>         50 |         0          1 |         1
>         51 |         0          1 |         1
>         52 |         0          1 |         1
>         53 |         0          1 |         1
>         55 |         0          1 |         1
>         56 |         0          3 |         3
>         57 |         0          1 |         1
>         59 |         0          1 |         1
>         60 |         0          2 |         2
>         62 |         0          1 |         1
>         63 |         0          2 |         2
>         69 |         0          1 |         1
>         70 |         0          1 |         1
>         78 |         0          1 |         1
>         83 |         0          1 |         1
>         84 |         0          2 |         2
>         92 |         0          1 |         1
> -----------+----------------------+----------
>      Total |         1        505 |       506
>
> Question: Why arent there only the untreated and treated in the table and
>
> what ist the meaning of the numbers 2-92?
>
>
> Second problem:
>
> I've done the nearest neighbor matching of the same data sample with the
>
> attnd function.
> My results are:
>
> . attnd  stockprice2010 reldummy, pscore(mypscore)
>
>
>  The program is searching the nearest neighbor of each treated unit.
>  This operation may take a while.
>
>
>
> ATT estimation with Nearest Neighbor Matching method
> (random draw version)
> Analytical standard errors
>
> ---------------------------------------------------------
> n. treat.   n. contr.         ATT   Std. Err.           t
> ---------------------------------------------------------
>
>       424          63      -2.255       6.070      -0.371
>
> ---------------------------------------------------------
> Note: the numbers of treated and controls refer to actual
> nearest neighbour matches
>
> Why is this result for ATT so different to the one of psmatch2?
> Is the attnd matching with replacement?
>
> Any suggestions would be much appreciated
>
> Thanks
>
> Jason
>
> --
> View this message in context: http://statalist.1588530.n2.nabble.com/Ousout-problem-psmatch2-tp6496035p6496035.html
>
> Sent from the Statalist mailing list archive at Nabble.com.
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