Causal Inferences in Health Services Research
*Xiao-Hua Andrew Zhou, University of Washington
Workshop Objectives Although randomized clinical trials are a gold standard in medical research, many violations to randomization can occur in health service research, such as non-compliance and missing data. In addition, clinical trials with observational data are often seen in health services research. One main challenge in causal inference with observational data is selection bias where the intervention of interest is often provided for those who have an indication for the treatment, for example, more severely ill. The objective of this workshop is to introduce and discuss different methods in handling protocol violations in randomized clinical trials and selection bias in using observational data where comparative inference is of interest. Target Audience: The workshop is intended for health services researchers and statisticians who are interested in understanding causal inferences in comparative inferences. Assumed Audience Familiarity with Topic: The workshop is designed for the broad health services research audience with moderate levels of statistical understanding.
Important Dates & Deadlines
- October 9 - 11, 2013