Reducing Selection Bias Inverse Probability Weighting and Bin Bootstrapping скачать в хорошем качестве

Reducing Selection Bias Inverse Probability Weighting and Bin Bootstrapping

Reducing selection bias is a concern when analyzing observational datasets. IPW (inverse probability weighting) and PSBB (propensity score bin bootstrapping) are two methods used to address selection bias. This presentation will demonstrate how IPW and PSBB capture information from all patients with balance achieved for measured confounders via propensity score adjustment. Dr. Zugui Zhang is the lead Biostatistician for the Value Institute of Christiana Care Health System and research assistant professor at Thomas Jefferson University. He has a broad background in health outcomes research, public health, epidemiology, and biostatistics. He has worked extensively on large international and national, multi-center, randomized clinical trials and observational studies.