The International Centre for Statistical Education based in the School of Computing, Electronics and Mathematics has invited Dr Michael A Posner - Associate Professor of Statistics, Villanova University, USA to give a talk entitled 'Making Valid Inferences in Observational Studies using Propensity Score Analysis'.
Randomised controlled trials are considered the gold standard in research studies. However, situations often arise which make them unfeasible, unethical, too restrictive in their generalisability, or just too time consuming and expensive.
A common alternative is using observational or natural studies where subjects self-select into modalities. In the era of data science and big data, some have termed this “found data.” However, observational data presents challenges in making valid inferences due to the presence of selection bias and confounding variables. The propensity score method is frequently used for analysis of observational data in fields including medicine, psychology, education, and survey research.
It is essentially stratification on multiple factors using a single summary measure and is performed by calculating the conditional probability (propensity) of being in the treated group given a set of covariates, weighting (or sampling) the data based on these propensity scores, and then making statistical inferences using the weighted data.
In this colloquium, Michael provides an overview of propensity score analysis and review methods of data selection or allocation of weights, including proposing an alternative weighting method – weighting within strata. This new method is compared to existing ones using empirical analysis and via an application on sending patients to respite care. Simulations are then described and discussed to compare the existing and new methods.
All are welcome to this talk. Please book your place in advance by emailing the ICSE on email@example.com.
Dr Michael A Posner is an Associate Professor of Statistics in the Department of Mathematics and Statistics at Villanova University, where he has been since 2005 after completing his PhD in biostatistics at Boston University. His publications and research span the fields of statistics education research, biostatistics, public health, healthcare research, statistics and the law, educational research, and analysis of observational studies.
Dr Posner is the Associate Director for Professional Development for the Consortium for the Advancement of Undergraduate Statistics Education (CAUSE), is on the Executive Committee of the Section on Statistics Education for the American Statistical Association (ASA), and is the past-chair of the Special Interest Group of the Mathematical Association of America (SIGMAA) for Statistics Education.
His research grants, totalling over $3 million, have come from the National Science Foundation, the Agency for Healthcare Research and Quality, and the Villanova Center for Nursing Research. Dr Posner won the 2010 Villanova University Faculty Award for Innovative Teaching, the MAA's 2012 Alder Award for Distinguished Teaching, and the ASA's 2012 Waller Education Award. He is the founding director of the Center for Statistics Education, a Center for Excellence in the College of Liberal Arts and Sciences at Villanova University.