Bayesian significance testing and multiple comparisons from MCMC outputs

DOI10.1016/j.csda.2007.11.009zbMath1452.62556OpenAlexW2063428374MaRDI QIDQ1023691

Takahiro Hoshino

Publication date: 12 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2007.11.009

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Bayesian inference (62F15) Paired and multiple comparisons; multiple testing (62J15) Applications of statistics to psychology (62P15)

Related Items (1)

Multiple hypothesis testing and clustering with mixtures of non-central \(t\)-distributions applied in microarray data analysis

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A Bayesian analysis of the unit root in real exchange rates
• Some contributions to efficient statistics in structural models: Specification and estimation of moment structures
• A Bayesian propensity score adjustment for latent variable modeling and MCMC algorithm
• Statistical decision theory and Bayesian analysis. 2nd ed
• Markov chains for exploring posterior distributions. (With discussion)
• Measurement invariance, factor analysis and factorial invariance
• A propensity score adjustment for multiple group structural equation modeling
• Doubly robust-type estimation for covariate adjustment in latent variable modeling
• Simultaneous factor analysis in several populations
• A STATISTICAL PARADOX
• Testing a Point Null Hypothesis: The Irreconcilability of P Values and Evidence
• A Bayesian significance test of the stationarity of regression parameters
• t Tests and Intervals for Comparisons Suggested by the Data
• A Study of the Powers of Several Methods of Multiple Comparisons
• On closed testing procedures with special reference to ordered analysis of variance
• Stepwise Multiple Comparison Procedures
• Power Differences Between Pairwise Multiple Comparisons
• Analysis of multivariate probit models
• The Large Sample Correspondence between Classical Hypothesis Tests and Bayesian Posterior Odds Tests
• Bayesian Multiple Comparisons Using Dirichlet Process Priors
• Bayesian Analysis of Binary and Polychotomous Response Data
• Rectangular Confidence Regions for the Means of Multivariate Normal Distributions
• A general method for analysis of covariance structures
• Bayesian Factor Analysis for Spatially Correlated Data, With Application to Summarizing Area-Level Material Deprivation From Census Data
• THE DISTRIBUTION OF RANGE IN SAMPLES FROM A NORMAL POPULATION, EXPRESSED IN TERMS OF AN INDEPENDENT ESTIMATE OF STANDARD DEVIATION
• Tools for statistical inference. Methods for the exploration of posterior distributions and likelihood functions.

This page was built for publication: Bayesian significance testing and multiple comparisons from MCMC outputs