BANOVA: An R Package for Hierarchical Bayesian ANOVA

被引:16
|
作者
Dong, Chen [1 ]
Wedel, Michel [2 ]
机构
[1] Univ Maryland, Dept Math, Math Bldg, College Pk, MD 20742 USA
[2] Univ Maryland, Dept Mkt, Robert H Smith Sch Business, 3303 Van Munching Hall, College Pk, MD 20742 USA
来源
JOURNAL OF STATISTICAL SOFTWARE | 2017年 / 81卷 / 09期
关键词
hierarchical Bayes regression; ANOVA; BANOVA; MCMC; BUGS modeling; MAXIMUM-LIKELIHOOD-ESTIMATION; MIXED MODELS; VARIANCE; TRANSFORMATIONS; DISTRIBUTIONS; ERRORS;
D O I
10.18637/jss.v081.i09
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, we develop generalized hierarchical Bayesian ANOVA, to assist experimental researchers in the behavioral and social sciences in the analysis of experiments with within- and between-subjects factors. The method alleviates several limitations of classical ANOVA, still commonly employed in those fields of research. An accompanying R Package for BANOVA is developed. It offers statistical routines and several easy-to-use functions for estimation of hierarchical Bayesian ANOVA models that are tailored to the analysis of experimental research. MCMC simulation is used to simulate posterior samples of the parameters of each model specified by the user. The core program is written in R and JAGS. After preparing the data in the required format, users simply select an appropriate model, and can estimate it without any advanced coding being required. The main aim of the R package is to offer freely accessible resources for hierarchical Bayesian ANOVA analysis, which makes it easy to use for applied researchers.
引用
收藏
页码:1 / 46
页数:46
相关论文
共 50 条
  • [41] parallelMCMCcombine: An R Package for Bayesian Methods for Big Data and Analytics
    Miroshnikov, Alexey
    Conlon, Erin M.
    [J]. PLOS ONE, 2014, 9 (09):
  • [42] brms: An R Package for Bayesian Multilevel Models Using Stan
    Buerkner, Paul-Christian
    [J]. JOURNAL OF STATISTICAL SOFTWARE, 2017, 80 (01): : 1 - 28
  • [43] BayesGmed: An R-package for Bayesian causal mediation analysis
    Yimer, Belay J.
    Lunt, Mark
    Beasley, Marcus
    Macfarlane, Gary
    McBeth, John
    [J]. PLOS ONE, 2023, 18 (06):
  • [44] bayesassurance: An R Package for Calculating Sample Size and Bayesian Assurance
    Pan, Jane
    Banerjee, Sudipto
    [J]. R JOURNAL, 2023, 15 (03): : 138 - 158
  • [45] BDgraph: An R Package for Bayesian Structure Learning in Graphical Models
    Mohammadi, Reza
    Wit, Ernst C.
    [J]. JOURNAL OF STATISTICAL SOFTWARE, 2019, 89 (03): : 1 - 30
  • [46] BayLum - An R package for Bayesian analysis of OSL ages: An introduction
    Philippe, Anne
    Guerin, Guillaume
    Kreutzer, Sebastian
    [J]. QUATERNARY GEOCHRONOLOGY, 2019, 49 : 16 - 24
  • [47] spatsurv: An R Package for Bayesian Inference with Spatial Survival Models
    Taylor, Benjamin M.
    Rowlingson, Barry S.
    [J]. JOURNAL OF STATISTICAL SOFTWARE, 2017, 77 (04): : 1 - 32
  • [48] A Guide to the Bayesian Analysis of Consumer Behavior Experiments With BANOVA Using Worked Examples
    Wedel, Michel
    Kopyakova, Anna
    [J]. AUSTRALASIAN MARKETING JOURNAL, 2022, 30 (01): : 3 - 9
  • [49] Bayesian hierarchical models for spatially misaligned data in R
    Finley, Andrew O.
    Banerjee, Sudipto
    Cook, Bruce D.
    [J]. METHODS IN ECOLOGY AND EVOLUTION, 2014, 5 (06): : 514 - 523
  • [50] RWTY (R We There Yet): An R Package for Examining Convergence of Bayesian Phylogenetic Analyses
    Warren, Dan L.
    Geneva, Anthony J.
    Lanfear, Robert
    [J]. MOLECULAR BIOLOGY AND EVOLUTION, 2017, 34 (04) : 1016 - 1020