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A key issue in science is assessing robustness to data analysis choices,while avoiding selective reporting and providing valid inference. SpecificationCurve Analysis is a tool intended to prevent selective reporting. Alas, whenused for inference it can create severe biases and false positives, due towrongly adjusting for covariates, and mask important treatment effectheterogeneity. As our motivating application, it led an influential study toconclude there is no relevant association between technology use and teenagermental well-being. We discuss these issues and propose a strategy for validinference. Bayesian Specification Curve Analysis (BSCA) uses Bayesian ModelAveraging to incorporate covariates and heterogeneous effects acrosstreatments, outcomes and sub-populations. BSCA gives significantly differentinsights into teenager well-being, revealing that the association withtechnology differs by device, gender and who assesses well-being (teenagers ortheir parents).

Specification analysis for technology use and teenager well-being: statistical validity and a Bayesian proposal