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It would be nice to have a propensity score matching implementation.
We can follow the description given at:
Dehejia, Rajeev. “Practical Propensity Score Matching: a Reply to Smith and Todd.” Journ…
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To compare with model-based matching, we should implement propensity score matching.
See https://github.com/statsmodels/statsmodels/issues/858
https://github.com/jburroni/statsmodels/tree/psmatch
po…
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### Description
statistical analysis of observational data that attempts to estimate the effect of a treatment
### Purpose
to construct an artificial control group by matching each treated unit wit…
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Since glm models store the data used to fit them, the use of the `data` argument to `augment()` is not needed when computing propensity scores. The more interesting argument to `broom::augment()` is …
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**토론 주제 또는 질문**
Propensity Score Matching(PSM)과 Endogeneity의 관계
Propensity Score Matching이 Endogeneity를 어떻게 낮출 수 있는가?
**상세 내용**
- PSM으로 Endogeneity를 어떻게 낮출 수 있는건가요?
- PSM말고 다른 방법론을 적용해보신게 있을까요…
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We have identified bugs in the implementation of BART for estimating propensity scores with the matchit function, particularly in handling the seed for reproducibility. How should we create reproducib…
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The matching algorithm and making prediction for users' preference in this unit make me think about treating missing values. I talked to Charles and he suggest looking up "propensity score matching". …
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#858 and PR #2288 propensity score matching
#2443 SUMM issue treatment effects
a few more references to complement #858
in python:
https://github.com/MacHu-GWU/ctmatching-project uses scikit-learn…
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Dear Dr. Greifer and all!
I was trying to learn more about PS Weighting (with WeightIt package) and Matching (with MatchIt package), but I am puzzled by a result, where I tried to estimate the ATE …