Editorial: Bayesian methods for advancing psychological science


The simple act of deciding which among competing theories is most likely - or which is most supported by the data - is the most basic goal of empirical science, but the fact that it has a canonical solution in probability theory is seemingly poorly appreciated. It is likely that this lack of appreciation is not for want of interest in the scientific community; rather, it is suspected that many scientists hold misconceptions about statistical methods. Indeed, many psychologists attach false probabilistic interpretations to the outcomes of classical statistical procedures (p values, rejected null hypotheses, confidence intervals, and the like; Gigerenzer, 1998; Hoekstra, Morey, Rouder, & Wagenmakers, 2014; Oakes, 1986). Because the false belief that classical methods provide the probabilistic quantities that scientists need is so widespread, researchers may be poorly motivated to abandon these practices.


Vandekerckhove, J., Rouder, J., & Kruschke, J. (2018). Editorial: Bayesian methods for advancing psychological science. Psychonomic Bulletin & Review, 25, 1–4.


    title   = {{E}ditorial: {B}ayesian methods for advancing psychological science},
    author  = {Vandekerckhove, Joachim and Rouder, Jeffrey and Kruschke, John},
    year    = {2018},
    journal = {Psychonomic Bulletin \& Review},
    volume  = {25},
    pages   = {1--4}