Reports by PCORI and other publications on comparative effectiveness research (CER) highlight the need for observational data as a key tool for CER recommendations. Accomplishing this goal requires optimal application of statistical methods that account for nonrandomized treatment assignment and associated bias. Although numerous approaches exist for this purpose, as does substantial literature on their strengths and limitations, many fundamental questions remain for effectively applying these approaches in practice; 1 such question is, “Should I use propensity score-based methods, and if so, which variation of those methods should I use for my data set and research question?”
