bamdit ChangeLog Commitments for the next version * New function "bforest" for forest plot of posteriors of sensitivity and specificity. * Modeling function to analyze comparative test * Meta-regression for sensitivity and specificity * Implement diagnostic function with approximate Bayesian cross-validation * Implement diagnostic functions and depreciate the weights plots Version 3.3.4 -- March 2022 * New function "hyper.posterior" matrix-plot for posteriors of hyper parameters. Version 3.3.3 -- August 2021 * New "summary" function for metadiag(). * The default option for re.model = "SeSp". * New argument "jag.seed" to make results replicable in metadiag(). * New warning message from "metadiag()" when the number of studies is less than 6. Version 3.3.2 -- November 2020 * Function "metadiag()": the argument "r2jags" has been depreciated. * Several bugs in ploting functions had been fixed. * New data frame "skin" for deep-learning diagnostic tests. Version 3.3.1 -- July 2019 * Some keywords are replaced. * Groupping variable "group" is the name (as character) of the data frame column. This change applies to the following function: plotdata; plotw; plotcompare. * Bug in the x-y limits in plotdata() function corrected. * Bug in the x-y limits in the plot.metadiag() function corrected. * The function plotcompare() understands the two.by.two argument from metadiag(). * Title argument for the function plotw(). * The metadiag() function returns the posteriors of "se"" and "sp" for each study. * The metadiag() function collects the studies' names. * The dataframe "ct" has the author and year information. * New data frame "diabetes" for comparative studies. * New data frame "rapt" for comparative studies. Version 3.2.1 -- September 2018. * The CITATION file corresponds to the JSS paper. Version 3.2.0 -- August 2018. * Corrections in the documentation. * Link the package to the JSS paper. * Function plotdata(), the argument max.size is active. Version 3.1.0 -- May 2017 * In metadiag() and plotdata() we allow that the data format is given as 2x2 table with columns' names: TP, FP, TN, FN. * A bug is fixed in the calcuation of the posterior distribution of BAUC. * The BSROC is calculated for parametrization: re.model = "SeSp". * New Summary function for metadiag. * New Print function for metadiag. Version 3.0.0 -- August 2016 * Implementation of S3 OOP in bamdit. * metadiag is now a generic function. * The argument re.model in metadiag allows to specify random effects on sensitivities and specificities. * Priors: hyper parameters mu.S and mu.D based on logistic distributions with mean = 0 and scale = 1 * Priors for the degrees of freedom parameter: df truncated exponential. * The function metadiag calculates the posterior probabilities of outliers. * New functions: print; summary and plot for metadiag objects. * The new plot function summarizes data and model predictions. * The BSROC is only displayed in the range of the observed fpr. If this range is less than 20% the function gives a warning. * We added further documentation and new examples. * Further documentation. * More validation in input arguments. Version 2.0.1 -- June 2015 * minor typos fixed Version 2.0 -- June 2015 * The function bsroc() implements te Bayesian SROC curve * Bayesian Predictive surface added (BPS) * Calculation of the Bayesian area under the curve (BAUC) * Migration of all graphical functions, they use ggplot * The package "coda" is not required Version 1.9 -- 2014 * The function metadiag() has a new implementation with blueprint() function within metadiag() * option of using rjags or R2jags in metadiag() * conflict of evidence analysis in metadiag() by splitting the variable w in w1 and w2 * Added a function for simulation of data (sim.meta) Version 1.4 -- 2014-07-08 * Improvement in the documentation Version 1.3 -- 2013-03-15 * New version of the function metadiag(). This version has main changes: * 1) The number of degrees of freedom in the model are fixed to a default value * 2) The Wishart prior distribution of the variance covariance matrix is replaced * by a conditional model where the priors are given to individual components. * 3) The priors of the variance covariance distribution are design to avoid boundary * problems in the parameter space. * The three adaptation trials are omited in metadiag() Version 1.2 -- 2012-07-31 * Added more graphical functions * We added meta-analysis examples data. * Improved internal model functions Version 1.1.1 -- 2011-12-08 * Examples do not run during testing. Version 1.1 -- 2011-08-30 * Weights are return from the bamdit function when random effects are scale mixed. * Change warning messages when model fails to adapt in JAGS. Version 1.0.1 -- 2011-08-09 * Nothing has to be written to disk anymore. * Models are compiled / adapted now with "first of three" due to an issue where sometimes models don't adapt. * Added ChangeLog * Corrected model adaption process from three to two stages Version 1.0 -- 2011-08-07 * Initial release