Showing 4 of total 4 results (show query)
mcguinlu
robvis:Visualize the Results of Risk-of-Bias (ROB) Assessments
Helps users in quickly visualizing risk-of-bias assessments performed as part of a systematic review. It allows users to create weighted bar-plots of the distribution of risk-of-bias judgments within each bias domain, in addition to traffic-light plots of the specific domain-level judgments for each study. The resulting figures are of publication quality and are formatted according the risk-of-bias assessment tool use to perform the assessments. Currently, the supported tools are ROB2.0 (for randomized controlled trials; Sterne et al (2019) <doi:10.1136/bmj.l4898>), ROBINS-I (for non-randomised studies of interventions; Sterne (2016) <doi:10.1136/bmj.i4919>), and Quality & Applicability of Diagnostic Accuracy Studies V2 (Whiting et al (2011) <doi:10.7326/0003-4819-155-8-201110180-00009>), and QUIPS (Hayden et al (2013) <doi:10.7326/0003-4819-158-4-201302190-00009>.
Maintained by Luke McGuinness. Last updated 2 years ago.
evidence-synthesisrisk-of-biassystematic-reviewsvisualisation
59 stars 7.99 score 67 scripts
danheck
metaBMA:Bayesian Model Averaging for Random and Fixed Effects Meta-Analysis
Computes the posterior model probabilities for standard meta-analysis models (null model vs. alternative model assuming either fixed- or random-effects, respectively). These posterior probabilities are used to estimate the overall mean effect size as the weighted average of the mean effect size estimates of the random- and fixed-effect model as proposed by Gronau, Van Erp, Heck, Cesario, Jonas, & Wagenmakers (2017, <doi:10.1080/23743603.2017.1326760>). The user can define a wide range of non-informative or informative priors for the mean effect size and the heterogeneity coefficient. Moreover, using pre-compiled Stan models, meta-analysis with continuous and discrete moderators with Jeffreys-Zellner-Siow (JZS) priors can be fitted and tested. This allows to compute Bayes factors and perform Bayesian model averaging across random- and fixed-effects meta-analysis with and without moderators. For a primer on Bayesian model-averaged meta-analysis, see Gronau, Heck, Berkhout, Haaf, & Wagenmakers (2021, <doi:10.1177/25152459211031256>).
Maintained by Daniel W. Heck. Last updated 1 years ago.
bayesbayes-factorbayesian-inferenceevidence-synthesismeta-analysismodel-averagingstancpp
28 stars 7.75 score 54 scripts 4 dependents
ropensci
medrxivr:Access and Search MedRxiv and BioRxiv Preprint Data
An increasingly important source of health-related bibliographic content are preprints - preliminary versions of research articles that have yet to undergo peer review. The two preprint repositories most relevant to health-related sciences are medRxiv <https://www.medrxiv.org/> and bioRxiv <https://www.biorxiv.org/>, both of which are operated by the Cold Spring Harbor Laboratory. 'medrxivr' provides programmatic access to the 'Cold Spring Harbour Laboratory (CSHL)' API <https://api.biorxiv.org/>, allowing users to easily download medRxiv and bioRxiv preprint metadata (e.g. title, abstract, publication date, author list, etc) into R. 'medrxivr' also provides functions to search the downloaded preprint records using regular expressions and Boolean logic, as well as helper functions that allow users to export their search results to a .BIB file for easy import to a reference manager and to download the full-text PDFs of preprints matching their search criteria.
Maintained by Yaoxiang Li. Last updated 2 months ago.
bibliographic-databasebiorxivevidence-synthesismedrxiv-datapeer-reviewedpreprint-recordssystematic-reviews
56 stars 7.17 score 44 scripts
boehringer-ingelheim
tipmap:Tipping Point Analysis for Bayesian Dynamic Borrowing
Tipping point analysis for clinical trials that employ Bayesian dynamic borrowing via robust meta-analytic predictive (MAP) priors. Further functions facilitate expert elicitation of a primary weight of the informative component of the robust MAP prior and computation of operating characteristics. Intended use is the planning, analysis and interpretation of extrapolation studies in pediatric drug development, but applicability is generally wider.
Maintained by Christian Stock. Last updated 12 months ago.
bayesian-borrowingbayesian-methodsclinical-trialevidence-synthesisextrapolationpediatricspharmaceutical-developmentprior-elicitationtipping-pointweighting
2 stars 4.38 score 12 scripts