Propensity scores: Everything you need to know in 5min 

Been reading articles about propensity scoring in multiple different articles but this is by far the most reasonable and down to earth description

Wah, many thanks, Sir. This 5 mins is probably more useful than a paid stats course🙏👍😊

Michael, the man that you’re!! Thank you from the bottom of my heart.

Very informative and concise introduction! Thank you very much!

Excellently lucid explanation!! Great job ✅

Very nice video. Covered the big picture information on why we do it and how we do it in a very concise format. Would be great to get the details on how to Performa matching in a stats package (is it a manual process or can be automated). That would probably make it much longer than 5 mins, but I believe it would be very useful). Another thing: I wanted to watch with subtitle but somehow the closed caption is Vietnamese. Thank you for the video!

wow! Thank you for such a concise and clear explanation! It was pure pleasure to watch!

I am a masters student studying social work and even when the focus of the research is different the process of calculating these scores is more or less similar. This video was a great deal of help and extremely digestible, thank you so much!

Excellent presentation ! very informative and concise. thanks for sharing

Excellent, clear and concise interpretation!

Thank you for the video!! saved me when I got totally lost in my intermediate pharmacoepidemiology class 😂

Omg!! This was perfect thanks!

Thank you so much for making this video!

thank you so much for this video helped me with my journal club!

Many Thanks sir. Your explanation is clear and easy to understand.

Fantastic! Nicest explanation of PSM ever

Thanks for the clear explanation!

Thanks for the video

Nice job. Thank you. 😊

genius! deeply appreciate this video! helpful for med students drowned by statistical terms

Sir we need more and more videos like this. Survival analysis, what test to use in what situation etc.

great video!

thank you, I finally got it (2 days before my exam) :)

Thank you dear teacher. Excellent, in spite of it wasn't in Spanish or without subtitles

Thank for the concise videos that explain the overall concept very well. It was very easy to understand. There are 3 implementation details during the matching phase (at 5:00) hoping you could clarify. 1. After we get the score, if there are two rows with scores 0.5 in control group (where `SGLT2 = No`), should both of them be matched to row 3 in treatment group? 2. In the real world, the score would rarely be exactly the same if we allow infinite decimal. How do you consider a match? Would there be an arbitrary numeric difference allowed? 3. If there are two rows in treatment with score 9.15 and 9.18 (row A and B), and two rows in control with score 9.16 and 9.25 (row C and D). Would row A and B both be matched to C? Or would row A matched to C as they are have the smallest difference, then row B has to be matched to D?

thank you for this

thank you for this great explanation! Is there also a possibility when having 3 treatment groups to calculate propensity scores with the same strategy?

Really helpful, I wanted to ask What is the difference between Propensity score matching and Case control matching (SPSS)?

Can you please explain the slide at 5:10? Why don't we have the same number of persons, means...? Is it just that we do not take into account people without a match?

thanks, great video. what are the pros and cons of weighting vs matching?

Hi Michael, Appreciate this breakdown, despite most of it going over my head. When you say these statistical methods do not mimic RCTs, what exactly does that mean? How closely do we get to the results of a RCT using this method, and has this method been verified against the findings of RCTs? The reason I'm asking this is b/c I came across a cohort article comparing adolescents who took antipsychotic medication vs. those who didn't, and compared how they were doing 5 years later. The article suggests, after using IPTW, that antipsychotic medication in those w/ their first episode of psychosis, actually makes for a worse 5 year outcome. I'm skeptical though b/c it's a cohort study and no randomization was done. The authors acknowledge this weakness, and then state that the Stabilized IPTW is used to eliminate the possibility that those with worse psychosis were the ones who were given an antipsychotic medication. (I think this is the most probable explanation for why those who were given AP medication fared worse. . .simply b/c they already were experiencing more profound psychosis and so we would expect them to be doing worse at a 5 year follow-up). Seems super fishy to me. . .any thoughts here are appreciated, thx.

Can you use mediators in addition to / in place of confounders as your variables when calculating propensity score?

Can one use the propensity score as the probability of death in 14 days (say, using an online calculator like CRASH for traumatic brain injury) and then match patients with similar probabilities of death to see if a particular treatment has lower mortality than another one? If the treatment had an effect, there would be a difference in the actual mortality rates? Is that a valid propensity matched analysis? How does one find the sample size for such an analysis?

kindly guide how to analysis step by step in.spss

how do we get weights as 0.6 and 0.9 ? can you please elaborate

There are 3 scores as 0.6, would it be fair/unbiased to match with random 2 only?

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Didnt't understand anything.

Very good lesson except that you are extremely fast. I wish you could slow down your pace