Abstract
In an observational study, researchers are constantly required to distinguish the effects caused by the assignment of treatment. Propensity score methodology is one way to determine the effects of, and their probabilities, given a vector of observed covariates, which is particularly popular in the fields of medical, pharmaceutical and social sciences. However, there are mixed views for the best methodologies to use and an overall understanding of the propensity score methodology. Also, there is minimal literature for propensity score methods being used within the broader scientific community. Propensity score methodology can be suited to determine effects caused by, not only treatment of pharmaceutical medication, but for “treatment” of some external event, proposed event or interaction within the wider community. For example, the effect on a regional community due to business closure, or a road by-pass would be a reasonable case of how propensity score methods can be further used within the wider scientific community.
Original language | English |
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Title of host publication | Statistics for Data Science and Policy Analysis |
Editors | Azizur Rahman |
Place of Publication | Singapore |
Publisher | Springer |
Chapter | 4 |
Pages | 41-53 |
Number of pages | 12 |
ISBN (Electronic) | 9789811517358 |
ISBN (Print) | 9789811517341 |
DOIs | |
Publication status | Published - 1 Apr 2020 |