Colby J. Vorland

This paper demonstrates how accounting for clustering and nesting effects in lifespan studies improves statistical rigor and reduces Type I error rates using data from the National Institute on Aging's Intervention Testing Program.

The paper evaluates how often studies in behavioral and brain sciences properly test for sex-dependent effects, finding that only 24% of relevant articles use appropriate statistical methods.