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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.
http://cega.berkeley.edu/assets/cega_events/31/Matching_Methods.ppt
PSM: Key Assumptions Key assumption: participation is independent of outcomes conditional on Xi This is false if there are unobserved outcomes affecting participation Enables matching not just at the mean but balances the distribution of observed characteristics across treatment and control Density 0 1 Propensity score Region of common support Density of scores for participants High probability of …
http://ftp.iza.org/dp1588.pdf
lap/Common Support (sec. 3.3) Step 5: Sensitivity Analysis (sec. 4) Step 4: Matching Quality/Effect Estimation (sec. 3.4-3.7) CVM: Covariate Matching, PSM: Propensity Score Matching The aim of this paper is to discuss these issues and give some practical guidance to researchers who want to use PSM for evaluation purposes. The paper is organised as follows.
https://www.statalist.org/forums/forum/general-stata-discussion/general/1456835-common-support-graphs-in-kmatch-psm
Aug 08, 2018 · Common Support Graphs in Kmatch (PSM) 06 Aug 2018, 04:37. Dear all, I work with Ben Jann's kmatch ado and got a question concerning the common support graphs. Basically I do not understand what his graph is supposed to show in contrast to the ones I …
https://onlinelibrary.wiley.com/doi/full/10.1111/j.1467-6419.2007.00527.x
Jan 31, 2008 · Abstract Propensity score matching (PSM) has become a popular approach to estimate causal treatment effects. It is widely applied when evaluating labour market policies, but empirical examples can be found in very diverse fields of study.Cited by: 5122
http://pubdocs.worldbank.org/en/531751446495195365/2a-Matching-and-DiffDiff-Havari.pdf
Quasi-experimental methods: , Propensity Score Matching and , Difference in Differences CIE Training 28/67 Quasi-experimental methods: , Propensity Score Matching and , …
https://en.wikipedia.org/wiki/Propensity_score_matching
In the statistical analysis of observational data, propensity score matching (PSM) is a statistical matching technique that attempts to estimate the effect of a treatment, policy, or other intervention by accounting for the covariates that predict receiving the treatment.
https://stats.stackexchange.com/questions/50635/do-we-need-overlap-common-support-in-case-of-a-parametric-regression
One typically assumes "Common Support" (/"Overlap") - which means that for any value of the confounding variables X a unit i can be potentially observed …
https://www.statalist.org/forums/forum/general-stata-discussion/general/1145219-psmatch2-graph-for-propensity-score-matching
Mar 17, 2016 · There are a few issues with this graph including not having a unit on the vertical axis and also not being what a PSM graph should look like. A PSM graph should show two things: 1) the propensity score of treatment-group observations versus control-group observations and before matching then 2) the same graph after matching.
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