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what are the advantages and disadvantages of IPTW (Inverse Probability of Treatment Weighting) comparing to PSM (propensity score matching) in dealing with confounding variables?

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Despite some similarities, propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) behave differently, mainly because matching selects some cases/controls and discards others, while IPTW includes all study units.

The scholarly literature suggests indeed that PSM and IPTW have similar accuracy in many cases, but in some specific scenarios PSM behaves better. However, in my experience when there are discrepancies between these methods, eventually the data collection approach and the study itself ends up being less credible and externally valid.

In any case, you can peruse the following works on the subject (it is only a quick selection):

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5564952/

https://elischolar.library.yale.edu/cgi/viewcontent.cgi?referer=https://www.google.com/&httpsredir=1&article=1347&context=ysphtdl

https://www.sciencedirect.com/science/article/pii/S073510971637036X

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