There has been a growing interest in using propensity scores in the analysis of observational studies. The propensity score is a balancing mechanism that works to create groups of subjects which have a similar distribution on background covariates. Matching, stratification, inverse propensity treatment weighting and regression adjustment are all strategies that can be used with the propensity score to create balance between groups of subjects. The aim of this paper is to introduce propensity scores and the different techniques which make use of them. We use data obtained from the Women's Health Initiative to demonstrate each of the different methods for propensity score analysis. In the example analysis we examined the association between dog ownership and CVD. The results of our analysis were quite consistent, and demonstrate the propensity score analysis can be used effectively to balance treated and untreated groups within an observational study.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/613406 |
| Date | January 2016 |
| Creators | Cousineau, Valerie Elaine |
| Contributors | Bell, Melanie L., Bedrick, Edward J., Billheimer, David D. |
| Publisher | The University of Arizona. |
| Source Sets | University of Arizona |
| Language | en_US |
| Detected Language | English |
| Type | text, Electronic Thesis |
| Rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. |
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