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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "appraise" in publications use:'
type: software
license: GPL-3.0-only
title: 'appraise: Bias-Aware Evidence Synthesis in Systematic Reviews'
version: 0.1.1
doi: 10.32614/CRAN.package.appraise
abstract: Implements a bias-aware framework for evidence synthesis in systematic reviews
  and health technology assessments, as described in Kabali (2025) <https://doi.org/10.1111/jep.70272>.
  The package models study-level effect estimates by explicitly accounting for multiple
  sources of bias through prior distributions and propagates uncertainty using posterior
  simulation. Evidence across studies is combined using posterior mixture distributions
  rather than a single pooled likelihood, enabling probabilistic inference on clinically
  or policy-relevant thresholds. The methods are designed to support transparent decision-making
  when study relevance and bias vary across the evidence base.
authors:
- family-names: Kabali
  given-names: Conrad
  email: conrad.kabali@utoronto.ca
repository: https://cran.r-universe.dev
commit: a5d99254da04bb7d56bb9014e8d5af61aabdbc55
date-released: '2026-02-09'
contact:
- family-names: Kabali
  given-names: Conrad
  email: conrad.kabali@utoronto.ca