Observational studies are often biased by failure to adjust for a covariate that was not measured. A series of studies may replicate an association because the bias that produced this association has been replicated, not because a treatment effect has been demonstrated. To be of value, a replication should remove, or reduce, or at least vary a potential source of bias that resulted in uncertainty in earlier studies. Having defined the goal of replication in this way, we may ask: Can one observational study replicate itself? Can it provide two statistically independent tests of one hypothesis about treatment effects such that the two tests are susceptible to different unobserved biases? Can the sensitivity analyses for these two tests be combined using meta-analytic techniques as if they came from unrelated studies, despite using the same data twice? When this is possible, the study is said to possess two evidence factors. The talk is divided into two parts, a brief, largely conceptual discussion of replication in observational studies, followed by a longer, more technical discussion with results about and practical examples of evidence factors.

Notes, reminders of notation, a quick R session and references: http://www-stat.wharton.upen