From Child Development: A gentle intro to Bayesian stats

This article could be the ground floor for your Bayesian skyscraper: it’s clearly written, conceptually precise, and beautifully illustrated with empirical examples and practical guides (in the supplementary materials).

A Gentle Introduction to Bayesian Analysis: Applications to Developmental Research

Rens van de Schoot, David Kaplan, Jaap Denissen, Jens B. Asendorpf, Franz J. Neyer, Marcel A.G. van Aken

Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First, the ingredients underlying Bayesian methods are introduced using a simplified example. Thereafter, the advantages and pitfalls of the specification of prior knowledge are discussed. To illustrate Bayesian methods explained in this study, in a second example a series of studies that examine the theoretical framework of dynamic interactionism are considered. In the Discussion the advantages and disadvantages of using Bayesian statistics are reviewed, and guidelines on how to report on Bayesian statistics are provided.

“…it is clear that it is not possible to think about learning from experience and acting on it without coming to terms with Bayes’ theorem. Jerome Cornfield” (in De Finetti, 1974a)