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Propensity score matching in JMP
Hi all.
I have a combined dataset (cases and controls). The total number of cases is fixed and controls has double the number compared to cases . Main outcome of the study to see the recurrence of disease after treatment. I would like to run propenisty score matching on this data set. Is there anyway i can run propensity socre in JMP?
Appreicate for your advice and suggestions.
Pablo
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Re: Propensity score matching in JMP
Hello,
While JMP doesn't have Propensity Score Analysis (PSA) platform, you can definitely accomplish PSA in JMP by regressing the Treatment/Control factor on the suspected covariates by using the Fit Model (Logistic) platform. The Pscores are the XB portion of the model. You can use the PScores to identify matches or as weights. Also, given that JMP connects with R, you can take advantage of the PSA algorithms that R has, including the Optimal Matching routine. If you know how to do PSA in a different software, you could try using the platforms that JMP has to reproduce the results.
Cheers,
MG
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Re: Propensity score matching in JMP
Hi Pablo. Did you ever find a solution to your question? I am also trying to do a propensity score matching with cases and controls, but cannot figure out how to do this JMP. Thanks!
lindsey
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Re: Propensity score matching in JMP
This capability is not currently out of the box functionality within JMP. There was a team in Japan who made an add-in to do this as few versions ago (link below but in Japanese).
https://www.jmp.com/content/dam/jmp/documents/jp/support/propensityscore201412.pdf
I would add this request to the Wish List section of the community page.
https://community.jmp.com/t5/JMP-Wish-List/idb-p/jmp-wish-list
Best,
Chris Kirchberg
Data Scientist, Life Sciences - Global Technical Enablement
JMP Statistical Discovery, LLC. - Denver, CO
Tel: +1-919-531-9927 ▪ Mobile: +1-303-378-7419 ▪ E-mail: chris.kirchberg@jmp.com
www.jmp.com
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Re: Propensity score matching in JMP
Hello,
While JMP doesn't have Propensity Score Analysis (PSA) platform, you can definitely accomplish PSA in JMP by regressing the Treatment/Control factor on the suspected covariates by using the Fit Model (Logistic) platform. The Pscores are the XB portion of the model. You can use the PScores to identify matches or as weights. Also, given that JMP connects with R, you can take advantage of the PSA algorithms that R has, including the Optimal Matching routine. If you know how to do PSA in a different software, you could try using the platforms that JMP has to reproduce the results.
Cheers,
MG
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Re: Propensity score matching in JMP
FYI, this recent paper has some cautions about the use of propensity scoring in situations where matching is possible: Why Propensity Scores Should Not Be Used for Matching.
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Re: Propensity score matching in JMP
Hi Xan,
Thanks for the heads up. Gary King is definitely an authority in this space. Observational studies are exciting to say the least.
Sincerely,
Matt
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