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Editorial: Bayesian benefits for child psychology and psychiatry researchers / Albertine J. OLDEHINKEL in Journal of Child Psychology and Psychiatry, 57-9 (September 2016)
[article]
Titre : Editorial: Bayesian benefits for child psychology and psychiatry researchers Type de document : Texte imprimé et/ou numérique Auteurs : Albertine J. OLDEHINKEL, Auteur Article en page(s) : p.985-987 Langues : Anglais (eng) Mots-clés : Statistical methods probability Bayesian analysis hypothesis testing statistical data interpretation Index. décimale : PER Périodiques Résumé : 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. En ligne : http://dx.doi.org/10.1111/jcpp.12619 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=292
in Journal of Child Psychology and Psychiatry > 57-9 (September 2016) . - p.985-987[article] Editorial: Bayesian benefits for child psychology and psychiatry researchers [Texte imprimé et/ou numérique] / Albertine J. OLDEHINKEL, Auteur . - p.985-987.
Langues : Anglais (eng)
in Journal of Child Psychology and Psychiatry > 57-9 (September 2016) . - p.985-987
Mots-clés : Statistical methods probability Bayesian analysis hypothesis testing statistical data interpretation Index. décimale : PER Périodiques Résumé : 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. En ligne : http://dx.doi.org/10.1111/jcpp.12619 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=292