What is wrong with propensity score matching?
Matching treated subjects to untreated subjects using the propensity score then amounts to essentially randomly picking a control. As such, it is argued that propensity score matching can increase confounder imbalance, thereby leading to estimates of exposure effects with greater bias.
When do you use propensity score matching?
Propensity score matching (PSM) has been widely used to reduce confounding biases in observational studies. Its properties for statistical inference have also been investigated and well documented.
Can a person be matched by their propensity score?
Note that only a subset of observed individuals can be paired to form matched samples. The only exposed individuals which can be matched by their propensity score to an unexposed individual are those with propensity scores between 0.3 and 0.8.
How is propensity score matching used in observational studies?
2 To explain further, IF propensity score matching was used in a randomized experiment comparing two groups, then the propensity score for each participant in the study would be 0.50. This is because each participant would be randomly assigned to either the treatment or the control group with a 50% probability.
How are Propensity scores used in health care?
“Analysis of Observational Health Care Data Using SAS®”, which is published by the SAS Institute, is used to analyze how a health care treatment impacted an associated health care outcome. It details how propensity scores are created and how propensity score matching is used to balance covariates between treated and untreated observations.
When is a match too far away from an exposed individual?
If an exposed individual’s propensity score is less than 0.3, this score is too far away from any unexposed individual for a match to form. Similarly, if an exposed individual’s propensity score is greater than 0.8, this score is too far away from any unexposed individual for a match to form.