Bayesian Methods for Statistical Analysis byBorek Puza Publisher:ANU Press2015 ISBN-13:9781921934254 Number of pages:697 Description: A book on statistical methods for analysing a wide variety of data. Topics: bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Mark...
Bayesian Methods: An Analysis for Statisticians and Interdisciplinary Researchers - Leonard, Hsu - 1999 () Citation Context ...lysis are potentially overcome by using what is known as the Laplacian approximation to the marginal probability (see, for example, Carlin & Louis, 2000, pp.122–129; ...
Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. This book focuses on Bayesian methods applied routinely in practice including multiple linear regression, mixed effects models and generalized linear models (GLM). The...
This article presents a previously unplanned reanalysis of the prespecified primary end point conducted using Bayesian methods. The aim was to estimate the posterior probabilities that the treatment effect exceeded a range of potential ...
Because Bayesian statistical methods can be applied to any data, regardless of the type of cognitive model (Bayesian or otherwise) that motivated the data collection, Bayesian methods for data analysis will continue to be appropriate even if Bayesian models of mind lose their appeal. View article ...
This paper presents a conceptual introduction to Bayesian methods, without the use of equations. It would be a good initial piece to introduce to students new to the topic, or those who are from more of a nontechnical background. It is written for developmental psychologists, but students and...
By contrast,Bayesian analysisprovides coherent methods for computing the power and replication probability. Bayesian power analysis uses the posterior distribution to sample many different plausible parameter values, and for each parameter value generates plausible data that simulate a repetition of the exper...
simpleandeasytounderstand,thecorrespondingmethodshasbeenfully developedandapplied.However,researchersmayencountermore complexstructures,suchasmultiplemediationvariables,measurementsof multipledimensionsandincludingconfoundingvariables,whichrequired moregeneralstatisticalmethodsformodelfitness.Themediationanalysis ...
“The book is a good introductory treatment of methods of Bayes analysis. It should especially appeal to the reader who has had some statistical courses in estimation and modeling, and wants to understand the Bayesian interpretation of those methods. Also, readers who are primarily interested in ...
Bayesian methods provide a complete paradigm for statistical inference under uncertainty. These may be derived from an axiomatic system and provide a coherent methodology which makes it possible to incorporate relevant initial information, and which solves many of the difficulties that frequentist methods ...