Semken, ChristophRossell Ribera, David2024-01-092024-01-092022Semken C, Rossell D. Specification analysis for technology use and teenager well-being: statistical validity and a bayesian proposal. J R Stat Soc Ser C Appl Stat. 2022;71(5):1330-55. DOI: 10.1111/rssc.125780035-9254http://hdl.handle.net/10230/58648A key issue in science is assessing robustness to data analysis choices, while avoiding selective reporting and providing valid inference. Specification Curve Analysis is a tool intended to prevent selective reporting. Alas, when used for inference it can create severe biases and false positives, due to wrongly adjusting for covariates, and mask important treatment effect heterogeneity. As our motivating application, it led an influential study to conclude there is no relevant association between technology use and teenager mental well-being. We discuss these issues and propose a strategy for valid inference. Bayesian Specification Curve Analysis (BSCA) uses Bayesian Model Averaging to incorporate covariates and heterogeneous effects across treatments, outcomes and subpopulations. BSCA gives significantly different insights into teenager well-being, revealing that the association with technology differs by device, gender and who assesses well-being (teenagers or their parents).application/pdfengThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2022 The Authors. Journal of the Royal Statistical Society: Series C (Applied Statistics) published by John Wiley & Sons Ltd on behalf of Royal Statistical Societyinfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1111/rssc.12578adolescentsBayesian model averagingmental healthselective reportingsocial mediatreatment effect inferenceinfo:eu-repo/semantics/openAccess