Alexander Ly

Temp, A.G.M, Ly, A, van Doorn, J, Wagenmakers, E.-J, Tang, Y, Lutz, M.W, & Teipel, S. (2022). A Bayesian perspective on Biogen's aducanumab trial. Alzheimer's and Dementia, 2022, 1–11. doi:10.1002/alz.12615

Heck, D.W, Boehm, U, Böing-Messing, F, Bürkner, P.-C, Derks, K, Dienes, Z, … Hoijtink, H. (2022). A review of applications of the Bayes factor in psychological research. Psychological Methods. doi:10.1037/met0000454

Bartoš, F, Gronau, Q. F, Timmers, B, Otte, W.M, Ly, A, & Wagenmakers, E.-J. (2021). Bayesian model-averaged meta-analysis in medicine. Statistics in Medicine, 2021, 1–19. doi:10.1002/sim.9170

Weigard, A.S, Brislin, S.J, Cope, L.M, Hardee, J.E, Martz, M.E, Ly, A, … Heitzeg, M.M. (2021). Evidence accumulation and associated error-related brain activity as computationally-informed prospective predictors of substance use in emerging adulthood. Psychopharmacology. doi:10.1007/s00213-021-05885-w

Ly, A, & Wagenmakers, E.-J. (2021). A critical evaluation of the FBST ev for Bayesian hypothesis testing: Critique of the FBST ev. Computational Brain and Behavior. doi:10.1007/s42113-021-00109-y

van den Bergh, D, Clyde, M.A, Komarlu Narendra Gupta, A.R, de Jong, T, Gronau, Q. F, Marsman, M, … Wagenmakers, E.-J. (2021). A tutorial on Bayesian multi-model linear regression with BAS and JASP. Behavior Research Methods. doi:10.3758/s13428-021-01552-2

Turner, R.J, Ly, A, ter Schure, J.A, & Grünwald, P.D. (2021). Safe Testing: Online, anytime valid hypothesis tests. In Proceedings of ICT.Open.

Sarafoglou, A, Haaf, J.M, Ly, A, Gronau, Q. F, Wagenmakers, E.-J, & Marsman, M. (2021). Evaluating multinomial order restrictions with bridge sampling. Psychological Methods. doi:10.1037/met0000411

Gronau, Q. F, Ly, A, & Wagenmakers, E.-J. (2020). Informed Bayesian t-Tests. American Statistician, 74(2), 137–143. doi:10.1080/00031305.2018.1562983

van den Bergh, D, van Doorn, J, Marsman, M, Draws, T, Kesteren, E.-J, Derks, K, … Wagenmakers, E.-J. (2020). A tutorial on conducting and interpreting a bayesian ANOVA in JASP Tutoriel pour réaliser et interpréter une analyse de variance bayésienne dans JASP. Annee Psychologique, 120(1), 73–96. doi:10.3917/anpsy1.201.0073