Propensity Score Matching (PSM)

Du måste hänvisa till denna webbsida om du använder informationen någon annanstans.
Hur detta skall se ut beror på var du återanvänder informationen. Det kan exempelvis se ut så här:
Ronny Gunnarsson. "Propensity Score Matching (PSM)" [på INFOVOICE.SE]. Tillgänglig på: https://infovoice.se/propensity-score-matching/. Informationen hämtad November 27, 2021.
Suggested pre-reading What this web page adds
  1. Introduction to statistics
  2. Observations and variables
  3. Inferential statistics
  4. Choosing statistical analysis
This web-page provides an introduction to propensity score matching. Reading this will give you an understanding of when this statistical test is appropriate and what it does.

Comparing groups, and especially comparing outcome of different interventions, require some kind of randomisation. The main purpose of the randomization is to eliminate the possibility that there is some kind of selection bias guiding allocation to groups and that this bias is also related to the outcome. Any selection bias will distort the results and the main purpose of randomization is to eliminate this. Consequently randomized controlled trials are considered to be the best way to evaluate effects of different treatments. However, randomization is not always ethical or possible and the only way is to use existing retrospective observations.

Traditionally retrospective observations has been analysed using multivariable regression where treatment allocation has been one of many independent variables. Propensity score matching (PSM) is a new technique allowing retrospective data to be used for group comparisons estimating effect of a treatment. PSM can be done in several different ways . It has been argued that PSM is slightly better than multivariate regression for the purpose of comparing effect between different interventions .

The main downside with PSM is that it can only adjust for effect modifiers or confounding variables that has been measured and registered. There may be other effect modifiers and confounding variables at play that was never measured in the retrospective data set. Hence, caution is required when interpreting data from studies using PSM.

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References

1.
Austin PC. An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies. Multivariate Behavioral Research [Internet]. 2011 May 31 [cited 2018 Jan 28];46(3):399–424. Available from: https://doi.org/10.1080/00273171.2011.568786
Du måste hänvisa till denna webbsida om du använder informationen någon annanstans.
Hur detta skall se ut beror på var du återanvänder informationen. Det kan exempelvis se ut så här:
Ronny Gunnarsson. "Propensity Score Matching (PSM)" [på INFOVOICE.SE]. Tillgänglig på: https://infovoice.se/propensity-score-matching/. Informationen hämtad November 27, 2021.

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