Educational Resources

The following Educational Resources, include three online tools for comparative effectiveness and causal inference (including two online self-guided courses in PCOR Studies and Propensity Score-Based Methods, and another tool for more general causal inference methods called DECODE CER).  Additional links are also provided for resources from the Teaching of Statistics in the Health Sciences Section of the American Statistical Association and a link to Software for Matching and Propensity Score Methods (created by Dr. Elizabeth Stuart).

The Online Self-Guided Course for PCOR Studies, titled "Writing a Successful Concept Proposal in Patient-Centered Outcomes Research", was created in conjunction with the ENACT Network, and development was funded by the Agency for Healthcare Research and Quality through R25HS023185.
The DECODE CER Tool titled "The Decision Tool for Causal Inference and Observational Data Analysis Methods in Comparative Effectiveness Research", was funded by the Patient-Centered Outcomes Research Institute. Its purpose is to provide insight on formulating questions, recognizing assumptions, conducting analysis, and interpreting results.This work was supported through a Patient-Centered Outcomes Research Institute (PCORI) award (Contract # R-IMC-1306-03827).

Online Self-Guided Course: Propensity-Score Based Methods

An Online Self-Guided Course in Propensity-Score Based Methods for Causal Inference­­, was developed from funding by an administrative supplement to the National Libraries of Medicine-funded University of Pittsburgh Biomedical Informatics Training Program (5 T15 LM007059-32). It helps describe potential outcomes with a different perspective and a different set of methods.

The Teaching of Statistics in Health Sciences is an active community of researchers and innovators, leaders in the dissemination of modern resources for the practice and teaching of statistics in health sciences, and professionals providing support and mentorship to new teachers of statistics in the health sciences. 
A website dedicated to provide information for matching methods and propensity scores in R, Stata, SAS & SPSS, was created by Dr. Elizabeth A. Stuart from John Hopkins Bloomberg School of Health. 
A website created for non-statisticians that helps medical and public health researchers and professionals learn more about biostatistics.