title: Editorial: Bayesian benefits for child psychology and psychiatry researchers.
abstract: For many scientists, performing statistical tests has become an almost automated routine. However, p-values are frequently used and interpreted incorrectly; and even when used appropriately, p-values tend to provide answers that do not match researchers' questions and hypotheses well. Bayesian statistics present an elegant and often more suitable alternative. The Bayesian approach has rarely been applied in child psychology and psychiatry research so far, but the development of user-friendly software packages and tutorials has placed it well within reach now. Because Bayesian analyses require a more refined definition of hypothesized probabilities of possible outcomes than the classical approach, going Bayesian may offer the additional benefit of sparkling the development and refinement of theoretical models in our field.
authors.forename: Albertine J
authors.initials: AJ
authors.lastname: Oldehinkel
mesh_terms: D001499:Bayes Theorem; D035843:Biomedical Research / Q000379:methods*; D002665:Child Psychiatry / Q000379:methods*; D003627:Data Interpretation, Statistical; D006801:Humans; D002666:Psychology, Child / Q000379:methods*
keywords: Bayesian analysis; Statistical methods; hypothesis testing; probability; statistical data interpretation