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Sara’s research interests centre around causal inference. This is the area of statistical methodology concerned with identifying and estimating effects of interventions. She is co-investigator in an MRC project that uses routinely collected medical data in a regression discontinuity design to estimate the effect of drugs in primary care. Methods for making causal inference often involve adjusting for different types of bias: by selection or due to confounding. These in turn can require the use of data from multiple sources to improve inference. Thus evidence synthesis is also an area of research that Sara is interested in. Sara is also a Bayesian and all her research is embedded in this paradigm.
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