NEWS

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TreeBUGS 1.5

• new argument monitorIndividual = TRUE for traitMPT() and betaMPT() allows to disable storing MCMC samples for individual theta parameters
• R code cleaned up with package "styler"
• bug fix for issue #12 by @soelderer (Paul): plotConvergence() uses strange parameter labels for models with more than 10 parameters
• bug fix for issue #11 by @mariusbarth: issues with printing of WAIC() results

TreeBUGS 1.4.9 (2022-09-06)

• fix deprecated << operator in RcppArmadillo
• added references to MPT tutorial (Schmidt et al., 2022)

TreeBUGS 1.4.8 (2022-08-23)

• check issue with HTML5 code (align, hspace)
• improved documentation of the probit regression in traitMPT()
• bugfix for getSamples() by @mariusbarth (GitHub issue #9)

TreeBUGS 1.4.7 (2021-01-08)

• bugfix for computing transformedParameters(..) for more than two parameters at the individual level

TreeBUGS 1.4.6

• Minor bugfix for naming of categories in plotFit() function
• Minor bugfix for BayesFactorMPT()

TreeBUGS 1.4.5 (2020-05-31)

• added standardized regression slopes for latent-trait MPT regression with continuous predictors (i.e., traitMPT with the option predStructure)
• BayesFactorSlope() plots the posterior distribution of the unstandardized (instead of partially standardized) slope parameter
• bugfix: posterior predictive check (PPP) for MPT models with a single tree

TreeBUGS 1.4.4 (2019-12-05)

• Improvements and bugfixes for the C++ MCMC samplers by Marius Barth.
• Bug fixes for issues concerning class(matrix(...)) in R 4.0.0

TreeBUGS 1.4.3 (2019-04-04)

• Thinning within C++ samplers [thanks to Marius Barth]
• New default priors for alpha and beta in betaMPT: "dgamma(1,.1)T(1,)"

TreeBUGS 1.4.2

• License updated to GPL-3
• Standard error for WAIC
• Hexagon sticker added

TreeBUGS 1.4.1 (2018-12-18)

• summarizeMCMC: Batchwise computation of summary statistics to reduce RAM overload
• WAIC implemented (based on a developmental feature of JAGS)

TreeBUGS 1.3.2

• Bugfix: extendMPT() for betaMPT
• New function to extract MCMC samples: getSamples(...)
• Possibility to extract MCMC samples for getGroupMeans(...)

TreeBUGS 1.3.1 (2018-02-23)

• Improved BayesFactorSlope(): JZS prior (=Cauchy) or g-prior(=normal)
• Bugfixes due to uncorrelated traitMPT

TreeBUGS 1.3.0 (2018-02-05)

• New option for the latent-trait MPT model: Independent Cauchy priors instead of a multivariate Wishart prior for the random-effects covariance matrix.

TreeBUGS 1.2.0 (2018-01-19)

• new function BayesFactorSlope() to get Bayes factor for continuous predictors in traitMPT()
• G^2 in PPP()
• option to use mu instead of mean in genTraitMPT()
• Various bugfixes

TreeBUGS 1.1.1 (2017-08-23)

• Various bug fixes

TreeBUGS 1.1.0 (2017-04-01)

• Functions to compute Bayes factors for simple (nonhierarchical, fixed-effects) MPT models: BayesFactorMPT() and marginalMPT()
• Registration of C++ routines

TreeBUGS 1.0.3

• Bugfix in readEQN: treat numeric parameter labels as constants
• Bugfix for traitMPT in priorPredictive()
• Optional arguments (...) for plotting functions

TreeBUGS 1.0.0

• New function correlationPosterior() to estimate the posterior for the population correlation (taking into account the number of participants)
• Second CRAN release

TreeBUGS 0.8.2

• New function probitInverse() to get the bivariate transformation of mean and SD in probability space given a normal distribution in probit space
• Visible function summarizeMCMC() to provide TreeBUGS-specific MCMC summaries
• priorPredictive() allows to sample group-level parameters

TreeBUGS 0.8.1

• Zeros-trick by Smith & Batchelder (2010) for betaMPT() implemented (i.e., by using the argument alpha="zero")
• Parameter constraints result in the same parameter labels for JAGS and C++ samplers (e.g., "b=a=f" will be labeled "b")

TreeBUGS 0.8.0

• New function withinSubjectsEQN() that replicates an MPT model multiple times with different tree, category, and parameter labels for within-subject factorial designs
• plotFreq() uses boxplots instead of lines by default
• Posterior-predictive p-values per participant
• Bugfix: avoid negative "sigma" and reversed "rho" estimates in traitMPT() due to negative scaling parameters "xi"
• Bugfix: posteriorPredictive() always sampled data for new participant (=> false T1+T2 posterior predictive checks!)

TreeBUGS 0.7.1

• New function priorPredictive() to sample data sets from the prior
• New function plotPrior() to plot prior distributions for group mean, SD, and correlations
• Posterior predictive samples for new participants
• Possible to use boxplot in plotFreq()
• Improved data-generating functions to allow for parameter restrictions
• Package testing via 'testthat' added

TreeBUGS 0.7.0

• Possibility to define models directly in R without requiring EQN files (by providing the EQN equations in a character value)
• New function transformedParameters() to obtain posterior samples of transformed parameters for a fitted model (both on the group and individual level)
• Argument "transformedParameters" now accepts a path to a text file with transformations (one per line)
• New argument "posteriorFile" to save fitted model and posterior MCMC samples in RData-file
• Better compatibility of betaMPTcpp() results with plotting functions
• Option to plot median or mean estimates in plotParam()
• Increased stability of extendMPT()
• Fixed bug in plotFreq() if input is given by a matrix/data.frame

TreeBUGS 0.6.2

• Bugfix: betweenSubjects with different number of chains
• Added data "arnold2013" by Arnold, Bayen, Kuhlmann, and Vaterrodt (2013)
• More examples in R help files
• Convergence plots for simpleMPT

TreeBUGS 0.6.1 (2016-09-02)

• First CRAN release
• Fast C++ Gibbs sampler tailored standard (simple fixed-effects) MPT models (simpleMPT)
• Adjusted summary functions to account for standard MPT models

TreeBUGS 0.6.0

• Fast C++ Gibbs sampler tailored to beta-MPT models (betaMPTcpp)

TreeBUGS 0.5.3

• Better weakly-informative priors for continuous predictors on the standardized scale

TreeBUGS 0.5.2

• New function betweenSubjectMPT() that computes between-subject comparisons (e.g., differences) of parameters from two fitted hierarchical models
• Extended plotFit() to fit observed against posterior-predicted covariances
• Hyperpriors matched by vector names
• Split vignette into "Intro" and "Extended"

TreeBUGS 0.5.1

• Tests for participant/person heterogeneity implemented (Smith & Batchelder, 2008)

TreeBUGS 0.5.0

• function fitModel() that fits both trait and beta MPT (avoids duplicated code)
• correlations of parameters are computed in R, not in JAGS anymore (increase in speed)
• argument "covStructure" removed (all correlations computed by default)
• save posterior predictive samples in traitMPT/betaMPT object (i.e., expected/predicted/observed frequencies)
• to get posterior predictive p-values, use ppp=1000 (previously: M.T1=1000)
• getParam() and getGroupMean() allow to save results in .csv-file

TreeBUGS 0.4.9

• T2 statistic implemented (posterior predictive check of covariance structure)
• Posterior predictive checks with parallel computation using multiple cores
• Bug fix for posterior predictive with fixed effects

TreeBUGS 0.4.8

• New function posteriorPredictive() to draw samples of individual frequencies from posterior
• T1 statistic now computed outside of JAGS (more stable, smaller mcmc object, additional argument M.T1 to specifiy the number of posterior samples used)

TreeBUGS 0.4.7

• New function plotPriorPost() to compare prior vs. posterior densities
• Default prior for traitMPT changed to xi="dunif(0,10)" for stability

TreeBUGS 0.4.6

• Parameter-specific hyperpriors for betaMPT (alpha and beta) and traitMPT (mu and xi)

TreeBUGS 0.4.5

• Special case of a single hierarchical parameter in traitMPT() [Wishart reduces to chi^2]
• Allow fixed effect MPT parameters (e.g., a single guessing parameter for all participants). Specified in restrictions = list("g=FE")
• Bayesian p-value in getGroupMeans() to test whether group mean differs from overall mean
• Estimation of correlations of theta parameters in betaMPT (based on the MCMC samples; no explicit prior)

TreeBUGS 0.4.4

• New function extendMPT() to get additional MCMC samples for fitted traitMPT and betaMPT
• Bug fixes if parameter appear twice in model equation (e.g., u*u)

TreeBUGS 0.4.3

• Use own summary function (functions in runjags are slow and unstable)
• Estimation of DIC requries argument "dic=TRUE" or can be estimated afterwards by: fit$dic <- extract(fit$runjags, "dic")

TreeBUGS 0.4.2

• Using the package runjags instead of R2jags (better functionality, e.g., provides progress bar during parallel sampling; max.time for autojags)
• Making the function summarizeMPT() visible to allow users to recompute nice MPT summaries after changing the mcmc object (e.g., after the exclusion of MCMC samples)

TreeBUGS 0.4.1

• new argument "T1group" to compute T1 statistic separately for a grouping factor (e.g., experimental condition; can be one of the predictors in traitMPT)
• changed name of parameter estimate plotting function to "plotParam()"
• new generic plotting function plot() for betaMPT and traitMPT (a convenient wrapper for the convergence plots in coda)

TreeBUGS 0.4.0

• Possible to sample correlations AND predictors in traitMPT (using covStructure vs. predStructure)
• Defaults for traitMPT: No predictors ; correlations for all covariates that are not included in predStructure
• Changed argument name "covType" to "predType" (since it is only relevant for predStructure in traitMPT)
• New argument corProbit to specify whether to compute correlations for probability- or probit-scaled MPT parameters
• Allow to round to specific number of digits, e.g.: summary(fittedModel, round=6)
• New function getParam() to conveniently extract posterior estimates (e.g., posterior mean, median, sd)
• New function getGroupMeans() to get group estimates in traitMPT with discrete predictors (for single factors or combinations)
• Updated vignette

TreeBUGS 0.3.5

• Back to comma-separated data format for 'data.csv' and 'covData.csv'
• Less informative Cauchy prior as default for continuous predictors in traitMPT
• Additional argument IVprec in traitMPT to specify hyperprior for precision of continuous slope paramters
• Data-generating function genMPT using general matrices of individual parameters
• Parameter labels for output in fittedModel$mcmc$BUGSoutput

TreeBUGS 0.3.4

• Support for WinBUGS and OpenBUGS removed
• New function plotFreq to plot individual and mean raw frequencies per tree

TreeBUGS 0.3.3

• autojags fixed
• BCI and R^hat included in individual statistics
• Better checks for input arguments for betaMPT, traitMPT

TreeBUGS 0.3.2

• csv-format for "data" and "covData": semicolon (;) instead of comma (,) to separate cells
• Printing of summary output to "parEstFile" improved

TreeBUGS 0.3.1

• New function plotDistribution() to plot histograms of individual mean estimates

TreeBUGS 0.3.0

• Discrete factors as covariates in traitMPT with fixed and random effects (see argument: covType)
• Improved covariate handling: irrelevant columns are neglected
• Goodness of fit plots for mean frequencies (plotFit)
• Removed default values for arguments that were NULL previously
• Updated vignette
• Various Bugfixes

TreeBUGS 0.2.3

• Predictors can be included in traitMPT (same arguments covData and covStructure as in betaMPT)
• Nice summary for covariates in betaMPT and predictors in traitMPT
• Checked and fixed data generation and fitting for latent trait and beta MPT model
• Remaining issue: SD of parameters in betaMPT not precisely estimated
• Informative error message if N=0 in a tree for a person
• Updated vignette

TreeBUGS 0.2.2

• Covariates can be included in betaMPT (see arguments covData and covStructure)
• Data generation for latent trait MPT model: genTraitMPT()
• Example model files (2HTM and 2HTSM) in library path: /TreeBUGS/MPTmodels/
• Examples for readEQN and data generation (genBetaMPT, genTraitMPT)

TreeBUGS 0.2.0

• Implementation of Beta-MPT and latent-trait MPT model: betaMPT() ; traitMPT()
• Sample and summarize transformed parameters (e.g., "deltaD=d1-d2")
• Posterior predictive checks (T1 statistic for group and individual data)
• Basic summary and plotting functionality
• Functions to generate data according to the Beta-MPT: genBetaMPT()
• Package vignette with examples: vignette("TreeBUGS")
• Checking EQN file for consistency (identifiability etc.): readEQN()