NSAPH-Software / CausalGPS

Matching on generalized propensity scores with continuous exposures
https://NSAPH-Software.github.io/CausalGPS/
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Appeal:’Matching on Generalized Propensity Scores with Continuous Exposures‘Raw data for 2000-2016 from the article #245

Open QAZqaz123wkx opened 3 months ago

QAZqaz123wkx commented 3 months ago

Hello, I am interested in your 'Matching on Generalized Propensity Scores with Continuous Exposures' article, I am very interested in your article, now I would like to reproduce the results of the article, where should I get the raw data of the article from 2000-2016, I hope to get your help, thank you. To link to this article: https://doi.org/ 10.1080/01621459.2022.2144737

wxwx1993 commented 3 months ago

@QAZqaz123wkx Thank you for your interest. Are you referring to the raw Medicare data under the data application section? To access the raw data, you might need to go through the following CMS Research Identifiable Request Process (https://resdac.org/cms-research-identifiable-request-process-timeline). I hope it helps.

Alternatively, If you want to test the method, the following Synthetic Medicare Data might be a solution. https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/L7YF2G

QAZqaz123wkx commented 3 months ago

Thank you very much, this helps me a lot, good luck to you. 

------------------ 原始邮件 ------------------ 发件人: "NSAPH-Software/CausalGPS" @.>; 发送时间: 2024年5月16日(星期四) 凌晨3:28 @.>; @.**@.>; 主题: Re: [NSAPH-Software/CausalGPS] Appeal:’Matching on Generalized Propensity Scores with Continuous Exposures‘Raw data for 2000-2016 from the article (Issue #245)

@QAZqaz123wkx Thank you for your interest. Are you referring to the raw Medicare data under the data application section? To access the raw data, you might need to go through the following CMS Research Identifiable Request Process (https://resdac.org/cms-research-identifiable-request-process-timeline). I hope it helps.

Alternatively, If you want to test the method, the following Synthetic Medicare Data might be a solution. https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/L7YF2G

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