version 1.1.1

Fixes

• inability to fit a model without specifying a seed
• inability to produce individual model plots due to incompatibility with the newer versions of ggplot2

version 1.1.0

Features

• parallel within and between model fitting using the parallel package with ‘parallel = TRUE’ argument

version 1.0.5

Fixes:

• models being fitted automatically until reaching R-hat lower than 1.05 without setting max_rhat and autofit control parameters
• bug preventing to draw a bivariate plot of mu and tau
• range for parameter estimates from individual models no containing 0 (or 1 in case of OR measured effect sizes)
• inability to fit a model with only null mu distributions if correlation or OR measured effect sizes were specified
• ordering of the estimated and observed effects when both of them are requested simultaneously
• formatting of this file (NEWS.md)

Improvements:

• priors plot: parameter specification, default plotting range, clearer x-axis labels in cases when the parameter is defined on transformed scale
• parameters plots: probability scale always ends at the same spot as is the last tick on the density scale
• adding warnings if any of the specified models has Rhat higher than 1.05 or the specified value
• grouping the same warnings messages together

version 1.0.4

Fixes:

• inability to run models without the silent = TRUE control

version 1.0.3

Features:

• x-axis rescaling for the weight function plot (by setting ‘rescale_x = TRUE’ in the ‘plot.RoBMA’ function)
• setting expected direction of the effect in for RoBMA function

Fixes:

• marginal likelihood calculation for models with spike prior distribution on mean parameter which location was not set to 0
• some additional error messages

CRAM requested changes:

• changing information messages from ‘cat’ to ‘message’ from plot related functions
• saving and returning the ‘par’ settings to the user defined one in the base plot functions

version 1.0.2

Fixes:

• the summary and plot function now shows quantile based confidence intervals for individual models instead of the HPD provided before (this affects only ‘summary’/‘plot’ with ‘type = “individual”’, all other confidence intervals were quantile based before)

version 1.0.1

Fixes:

• summary function returning median instead of mean

version 1.0.0 (vs the osf version)

Fixes:

• incorrectly weighted theta estimates
• models with non-zero point prior distribution incorrectly plotted using when “models” option in case that the mu parameter was transformed

Additional features:

• analyzing OR
• distributions implemented using boost library (helps with convergence issues)
• ability to mute the non-suppressible “precision not achieved” warning messages by using “silent” = TRUE inside of the control argument
• vignettes

Notable changes:

• the way how the seed is set before model fitting (the simulation study will not be reproducible with the new version of the package)