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https://www.statalist.org/forums/forum/general-stata-discussion/general/1402010-psmatch2-number-of-observations-under-common-support-different-with-ate-option
Jul 17, 2017 · Hello, I'm using Stata 14 and have two problems when I use the "ate" option and omit the option from psmatch2. When I run the psmatch2 command using the following options ", logit noreplacement common neighbor(1) ate" I get an equal number of treated and untreated participants "on support" (as expected):
https://econpapers.repec.org/RePEc:boc:bocode:s432001
PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. Edwin Leuven and Barbara Sianesi () . Statistical Software Components from Boston College Department of Economics. Abstract: psmatch2 implements full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance …Cited by: 2660
https://www.stata.com/meeting/italy14/abstracts/materials/it14_grotta.pdf
Italian Stata Users Group Meeting - Milano, 13 November 2014. Outline Theoretical background Application in Stata A.Grotta - R.Bellocco A review of propensity score in Stata. Some history A.Grotta - R.Bellocco A review of propensity score in Stata. Causal inference framework ID T Y 1 0 21
http://repec.org/bocode/p/psmatch2.html
When evaluating multiple outcomes psmatch2 reduces to the min common number of observations with non-missing values on ALL outcomes, because otherwise the matching weigths will not sum to the right number. ... Imposition of common support. ... E. Leuven and B. Sianesi. (2003). "PSMATCH2: Stata module to perform full Mahalanobis and propensity ...
https://www.stata.com/statalist/archive/2014-03/msg00088.html
The answer is to use the -ties- option in -psmatch2-. -psmatch2- drops ties, while -teffects- keeps the ties following the recommendation of Abadie and Imbens (2006). Scott's second question was about how to replicate the results from -psmatch2- using -teffects- with caliper matching.
https://www.bgsu.edu/content/dam/BGSU/college-of-arts-and-sciences/center-for-family-and-demographic-research/documents/Workshops/2013-workshop-PSA-brief-Stata-example.pdf
Note: the common support option has been selected The region of common support is [.00574559, .78324625] Description of the estimated propensity score in region of common support Estimated propensity score ----- Percentiles Smallest
http://www.pep-net.org/sites/pep-net.org/files/typo3doc/pdf/Training_Material/statadoc.pdf
psmatch2 creates a number of variables for the convenience of the user: _treated is a variable that equals 0 for control observations and 1 for treatment observations. _support is an indicator variable with equals 1 if the observation is on the common support and 0 if the observation is off the support.
https://www.researchgate.net/publication/4794420_PSMATCH2_Stata_Module_to_Perform_Full_Mahalanobis_and_Propensity_Score_Matching_Common_Support_Graphing_and_Covariate_Imbalance_Testing
PSMATCH2: Stata Module to Perform Full Mahalanobis and Propensity Score Matching, Common Support Graphing, and Covariate Imbalance Testing. Article (PDF Available) · May 2003 ...
https://www.youtube.com/watch?v=7RT8zFC5Rac
Mar 11, 2018 · A quick example of using psmatch2 to implement propensity score matching in Stata. A quick example of using psmatch2 to implement propensity score matching in Stata. Skip navigation Sign in. Search.Author: F. Chris Curran
https://www.researchgate.net/post/How_do_I_identify_the_matched_group_in_the_propensity_score_method_using_STATA2
How do I identify the matched group in the propensity score method using STATA? ... (be sure to include the common support option). Once that's done, you should be able to separate out those obs ...
https://www.statalist.org/forums/forum/general-stata-discussion/general/1402010-psmatch2-number-of-observations-under-common-support-different-with-ate-option
Jul 17, 2017 · Hello, I'm using Stata 14 and have two problems when I use the "ate" option and omit the option from psmatch2. When I run the psmatch2 command using the following options ", logit noreplacement common neighbor(1) ate" I get an equal number of treated and untreated participants "on support" (as expected):
https://econpapers.repec.org/RePEc:boc:bocode:s432001
PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. Edwin Leuven and Barbara Sianesi () . Statistical Software Components from Boston College Department of Economics. Abstract: psmatch2 implements full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance …Cited by: 2667
https://www.stata.com/meeting/italy14/abstracts/materials/it14_grotta.pdf
Italian Stata Users Group Meeting - Milano, 13 November 2014. Outline Theoretical background Application in Stata A.Grotta - R.Bellocco A review of propensity score in Stata. Some history A.Grotta - R.Bellocco A review of propensity score in Stata. Causal inference framework ID T Y 1 0 21
http://repec.org/bocode/p/psmatch2.html
When evaluating multiple outcomes psmatch2 reduces to the min common number of observations with non-missing values on ALL outcomes, because otherwise the matching weigths will not sum to the right number. ... Imposition of common support. ... E. Leuven and B. Sianesi. (2003). "PSMATCH2: Stata module to perform full Mahalanobis and propensity ...
https://www.stata.com/statalist/archive/2014-03/msg00088.html
The answer is to use the -ties- option in -psmatch2-. -psmatch2- drops ties, while -teffects- keeps the ties following the recommendation of Abadie and Imbens (2006). Scott's second question was about how to replicate the results from -psmatch2- using -teffects- with caliper matching.
https://www.bgsu.edu/content/dam/BGSU/college-of-arts-and-sciences/center-for-family-and-demographic-research/documents/Workshops/2013-workshop-PSA-brief-Stata-example.pdf
Note: the common support option has been selected The region of common support is [.00574559, .78324625] Description of the estimated propensity score in region of common support Estimated propensity score ----- Percentiles Smallest
http://www.pep-net.org/sites/pep-net.org/files/typo3doc/pdf/Training_Material/statadoc.pdf
psmatch2 creates a number of variables for the convenience of the user: _treated is a variable that equals 0 for control observations and 1 for treatment observations. _support is an indicator variable with equals 1 if the observation is on the common support and 0 if the observation is off the support.
https://www.researchgate.net/publication/4794420_PSMATCH2_Stata_Module_to_Perform_Full_Mahalanobis_and_Propensity_Score_Matching_Common_Support_Graphing_and_Covariate_Imbalance_Testing
PSMATCH2: Stata Module to Perform Full Mahalanobis and Propensity Score Matching, Common Support Graphing, and Covariate Imbalance Testing. Article (PDF Available) · May 2003 ...
https://www.youtube.com/watch?v=7RT8zFC5Rac
Mar 11, 2018 · A quick example of using psmatch2 to implement propensity score matching in Stata. A quick example of using psmatch2 to implement propensity score matching in Stata. Skip navigation Sign in. Search.Author: F. Chris Curran
https://www.researchgate.net/post/How_do_I_identify_the_matched_group_in_the_propensity_score_method_using_STATA2
How do I identify the matched group in the propensity score method using STATA? ... (be sure to include the common support option). Once that's done, you should be able to separate out those obs ...
http://www.pep-net.org/sites/pep-net.org/files/typo3doc/pdf/Training_Material/statadoc.pdf
psmatch2 creates a number of variables for the convenience of the user: _treated is a variable that equals 0 for control observations and 1 for treatment observations. _support is an indicator variable with equals 1 if the observation is on the common support and 0 if the observation is off the support.
https://ideas.repec.org/c/boc/bocode/s432001.html
psmatch2 implements full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. This routine supersedes the previous 'psmatch' routine of B. Sianesi. The April 2012 revision of pstest changes the syntax of that command.
https://thomasgstewart.github.io/propensity-score-matching-in-stata/
PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. (link) . Version 4.0.11.
https://www.stata.com/statalist/archive/2012-02/msg00942.html
Feb 21, 2012 · -psmatch2- ( a user written program found on ssc) generates a new variable called _wt. If you run -tab treat _wt- (for 1:1 matching), you should see the count of treated vs controls who were matched. You may have to stipulate - if _support==1 - if there were those who fell off of common support.
https://www.bgsu.edu/content/dam/BGSU/college-of-arts-and-sciences/center-for-family-and-demographic-research/documents/Workshops/2013-workshop-PSA-brief-Stata-example.pdf
Note: the common support option has been selected The region of common support is [.00563074, .78917042] Description of the estimated propensity score in region of common support Estimated propensity score -----
https://www.researchgate.net/post/How_do_I_identify_the_matched_group_in_the_propensity_score_method_using_STATA2
I would say before using psmatch2, run the pscore command to generate the scores first (be sure to include the common support option). Once that's done, you should be able to separate out those ...
http://fmwww.bc.edu/EC-C/S2013/823/EC823.S2013.nn12.slides.pdf
Propensity score matching Requirements for PSM validity The common support assumption 0 < P(D = 1jX ) < 1 implies that the probability of receiving treatment for each possible value of the vector X is strictly within the unit interval: as is the probability of not receiving treatment. This assumption of common
https://www.youtube.com/watch?v=7RT8zFC5Rac
Mar 11, 2018 · A quick example of using psmatch2 to implement propensity score matching in Stata. A quick example of using psmatch2 to implement propensity score matching in Stata. Skip navigation Sign in. Search.Author: F. Chris Curran
https://www.bristol.ac.uk/media-library/sites/cmm/migrated/documents/prop-scores.pdf
In general, the choice of covariates to insert in the propensity score model should be based on theory and previous empirical ndings; formal (statistical) tests (e.g. Heckman et al. , 1998, Heckman and Smith, 1999 and Black and Smith, 2004) The model for the propensity scores does not need a …
https://www.stata.com/statalist/archive/2006-10/msg00738.html
Oct 18, 2006 · * Make sure that you have not selected a "common support" option in one command and not in the other. * When there are if or in clauses in the commands, make sure that …
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4213057/
Apr 30, 2014 · Methods for Constructing and Assessing Propensity Scores. Melissa M Garrido, 1, 2 Amy S Kelley, M.D., ... (called “common support”). No inferences about treatment effects can be made for a treated individual for whom there is not a comparison individual with a similar propensity score. ... “PSMATCH2: Stata Module to Perform Full ...
http://scorreia.com/demo/psmatch2.html
psmatch2 creates a number of variables for the convenience of the user: _treated is a variable that equals 0 for control observations and 1 for treatment observations. _support is an indicator variable with equals 1 if the observation is on the common support and 0 if the observatio is off the support.
http://www.ssc.wisc.edu/sscc/pubs/stata_psmatch.htm
Propensity Score Matching in Stata using teffects For many years, the standard tool for propensity score matching in Stata has been the psmatch2 command, written by Edwin Leuven and Barbara Sianesi. However, Stata 13 introduced a new teffects command for estimating treatments effects in a variety of ways, including propensity score matching.
https://www.stata.com/meeting/germany10/germany10_sianesi.pdf
2. To give it empirical content: Common Support (we observe participants and non-participants with the same characteristics): ATT: P(D=1 X) < 1 ATNT: 0 < P(D=1 X) ATE: 0 < P(D=1 X) <1 ⇒ can use the (observed) mean outcome of the non-treated to estimate the mean (counterfactual) outcome the treated would have had they not been treated.
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