caa a22 4500 606153330 CHVBK 20210128100553.0 cr unu---uuuuu 210128e20151001xx s 000 0 eng 10.1007/s11121-014-0531-x doi (NATIONALLICENCE)springer-10.1007/s11121-014-0531-x Kadane Joseph Department of Statistics, Carnegie Mellon University, 15213, Pittsburgh, PA, USA aut Bayesian Methods for Prevention Research [Elektronische Daten] [Joseph Kadane] Bayesian statistics represents a paradigm shift in statistical reasoning and an approach to analysis that is applicable to prevention trials with small samples. This paper introduces the reader to the philosophy behind Bayesian statistics. This introduction is followed by a review of some issues that arise in sampling statistics and how Bayesian methods address them. Finally, the article provides an extended illustration of the application of Bayesian statistics to data from a prevention trial that tested a family-focused intervention. Society for Prevention Research, 2014 Causation nationallicence Prediction nationallicence Bayesian statistics nationallicence Counterfactual nationallicence Intervention nationallicence Prevention Science Springer US; http://www.springer-ny.com 16/7(2015-10-01), 1017-1025 1389-4986 16:7<1017 2015 16 11121 https://doi.org/10.1007/s11121-014-0531-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11121-014-0531-x text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Kadane Joseph Department of Statistics, Carnegie Mellon University, 15213, Pittsburgh, PA, USA aut NATIONALLICENCE 773 0- Prevention Science Springer US; http://www.springer-ny.com 16/7(2015-10-01), 1017-1025 1389-4986 16:7<1017 2015 16 11121