jarbes ChangeLog Version 2.0.0 -- January-Febrary-March 2022 Commitments for the next version * bmeta: scale mixture random effects * diagnostic bmeta: compare Bayesian cross-validation and scale mixture weights * Vignettes: * bmeta * bcmeta * b3lmeta * metarisk * hmr * bforest: a forest plot for bmeta; bcmeta; b3lmeta. * hmr: Posterior prediction of the treatment effect to an new group of patients * Effective number of studies in bcmeta and bmeta and b3lmeta * Function: betaplot for the regression coefficients of hmr * Binomial and Poisson likelihoods in bmeta, bcmeta and b3lmeta using the arguments "family=...", "link="..." * Tweedy's formula for bias: this is to understand the different bias correction approaches (e.g. bmeta vs. bcmeta vs. b3lmeta vs. bmetareg) * Planned: Meta-regression function........................ * Function: bmetareg * Function: summary.bmetareg * Function: plot for bmetareg * Function: diagnostic for bmetareg * Function: betaplot for the regression coefficients of bmetareg * Publication bias modeling. Done in version 2.0.0 ...................................... * Approximated Bayesian Cross-Validation for bmeta, b3lmeta, bcmeta. * Function: diagnostic for bcmeta (specific model and Bayesian cross-validation) * Function: diagnoistic for bmeta (Bayesian cross-validation) * Function: diagnoistic for b3lmeta (Bayesian cross-validation) * Include as argument the labels and axis information for plot functions: hmr (done) metarisk (done) bcmeta (done) bmeta (done) b3lmeta (done) * plot.bcmeta: add the arrows and the text for the distributions... * summary.b3lmeta: add the means by groups! (done) * Function: plot for bcmeta (done) * Function: plot for bmeta (done) * Function: plot for b3lmeta (done) * Function: bl3meta for three levels hierarchical meta-analysis (done) * Function: summary for bl3meta (done) * The function b3lmeta replaced the function ges * Labels (posterior-prior) in the diagnostic function of hmr (done) * Function bmeta for simple bayesian metaanalysis (done) * Function summary for bmeta (done) * Summary functions: * Include the prior parameters in the object type "hmr" (done) * Include the prior parameters in the object type "bcmeta" (done) * Include the prior parameters in the object type "metarisk" (done) * Include the prior parameters in the object type "bmeta" (done) * Include the prior parameters in the object type "b3lmeta" (done) Version 1.9.6 -- December 2021 * Function: bcmeta implements the "Bias-Corrected" Meta-analysis model * Function: summary for bcmeta * Function: plot for metarisk * Function: summary for metarisk * Function: diagnostic for metarisk * Function: plot for hmr * Function: summary for hmr * Function: diagnostic for hmr * New data frame covid19: meta-analysis of risk factors for complications and death in COVID-19 patients. * The function bcmeta replaced the function gesmix Version 1.8.0 -- Summer 2020 * The function "metamix" is not part of jarbes anymore. It will be replaced by the function "bcmeta" Version 1.7.4 -- November - December 2019 * Preparation for the paper on mixture models Version 1.7.3 -- April - May 2019 * Correction in the example of data ppvcap, metariks(..., two.by.two = TRUE,...) * Typo correction in the example of ges() "ppvipv" must be "ppvipd" Version 1.7.2 -- February-March 2019 * New function: "gesmix"" performs the finite mixture random effects bias analysis of Verde 2017 and Verde and Curcio 2019. * New arguments for the function "ges": EmBi = "Empirical Bias"standing for "penalization of observational studies" ExPe = "Explicit Penalization" for observational studies. * All if()s 've been checked. The reason was: Issue from CRAN compilation: --- failure: length > 1 in coercion to logical --- Version 1.7.1 -- December 2018 * A bug in function hmr() is fixed. Version 1.7.0 -- June 2018 * Implementation of the function "hmr" for combining aggregated data and individual participant data. * New dataset "healing": this dataset corresponds to a systematic review of aggregated data. The primary endpoint is healing without amputation in one year follow up. * New dataset "healingipd": This dataset corresponds to individual participant data for diabetic patients. Version 1.1.0 -- December 2017 * Implementation of the "ges" function for Generalized Evidence Synthesis. * Implementation of Half Cauchy priors for components of variances. * Implementation of Empirical Bias adjustement for Observational Studies. * Implementation of Penalization methods for Observationa Studies. * First prototype of the "hmr" function for combining IPD and AD data. Version 1.0.0 -- September 2017 * Implementation of the "metarisk"" function for bivariate hierarchical meta-regression of aggregated data. * Documentation improved. Version 0.5.0 -- January 2017 * Creation of data examples: * ppv.cap: PPV23 (23-valent pneumococcal polysaccharide vaccine) with 16 Randomized Clinical Trials (RCTs); outcome variable CAP (community-acquired pneumonia). * ppv.ipde: PPV23 with 3 RCTs and observational studies (5 cohorts and 3 case controls); all data types are aggregated results; outcome variable IPD (invasive pneumococcal disease). * stem.cells: 31 randomized controlled trials (RCTs) of two treatment groups of heart disease patients, where the treatment group received bone marrow stem cells and the control group a placebo treatment. * opti: one pragmatic trial, the OPTIMIZE trial, which evaluates the clinical effectiveness of a perioperative, cardiac output–guided hemodynamic therapy algorithm. And 21 small RCTs with evaluation of Risk of Bias. All are studies have aggregated data. * foot.ad: 36 RCTs which investigate adjunctive therapies vs. routine medical care in diabetic patients. The primary outcome is healing without foot amputation. There are aggregated covariates describing studies and patients characteristics. * foot.ipd: A cohort study with 260 diabetic patients, the outcome variable is healing without amputation in a followup of one year. In addition we have 14 potential risk factors.