{"package":"r-bayesrel","ecosystem":"conda","latest_version":"0.7.8","description":"Functionality for the most common single test reliability estimates: Coefficient alpha, 'Guttman's' lambda-2/-4/-6, the Greatest lower bound and coefficient omega. The Bayesian estimates are provided with credible intervals. The frequentist estimates are provided with bootstrapped confidence intervals The method for the Bayesian estimates, except for omega, is sampling from the posterior inverse 'Wishart' for the covariance matrix based measures (see 'Murphy', 2007, <https://www.seas.harvard.edu/courses/cs281/papers/murphy-2007.pdf>. In the case of omega it is 'Gibbs' Sampling from the joint conditional distributions of a single factor model ('Lee', 2007, <doi:10.1002/9780470024737>). The glb method uses adjusted code from the 'Rcsdp' package by 'Hector Corrada Bravo', <https://CRAN.R-project.org/package=Rcsdp>. This process applies a slightly adjusted solving algorithm from the 'CSDP' library by 'Brian Borchers' <https://github.com/coin-or/Csdp/wiki>, <doi:10.1080/10556789908805765>, but is wrapped in 'RcppArmadillo'. Guttman's Lambda-4 is from 'Benton' (2015) <doi:10.1007/978-3-319-07503-7_19>. The principal factor analysis for a version of frequentist omega is from 'Schlegel' (2017) <https://www.r-bloggers.com/2017/03/iterated-principal-factor-method-of-factor-analysis-with-r/>. The analytic confidence interval of alpha is from 'Bonett' and 'Wright' (2015) <doi:10.1002/job.1960>.","license":"GPL-3.0-only","license_risk":"unknown","commercial_use_notes":"verify manually — license not parseable / not declared.","homepage":"https://github.com/juliuspf/Bayesrel","repository":"","downloads_weekly":334,"health":{"score":49,"risk":"high","breakdown":{"maintenance":10,"popularity":3,"security":25,"maturity":9,"community":2},"deprecated":false,"max_score":100},"vulnerabilities":{"count":0,"critical":0,"high":0,"medium":0,"low":0,"details":[]},"versions":{"latest":"0.7.8","total_count":10,"recent":["0.7.0.7","0.7.1","0.7.4","0.7.4.1","0.7.4.2","0.7.4.3","0.7.4.4","0.7.5","0.7.7","0.7.8"]},"metadata":{"deprecated":false,"deprecated_message":null,"maintainers_count":1,"first_published":"2021-07-10 17:12:59.818000+00:00","last_published":"2025-09-17 22:00:37.989000+00:00","dependencies_count":0,"dependencies":[]},"github_stats":null,"bundle":null,"typescript":null,"known_issues":{"bugs_count":0,"bugs_severity":{},"status_breakdown":{},"link":null,"scope":"none"},"historical_compromise":null,"recommendation":{"action":"use_with_caution","issues":["Moderate health score (49/100) — verify manually"],"use_version":"0.7.8","version_hint":null,"summary":"r-bayesrel@0.7.8 low health (49/100) — consider alternatives"},"version_scoped":null,"_meta":{"endpoint":"check","tier":"full","philosophy":"DepScope is free. Use the cheapest endpoint that answers your real question.","cheaper_alternatives":[{"endpoint":"/api/exists/conda/r-bayesrel","tokens_estimated":12,"use_when":"you only need to know if the package exists (hallucination guard)"},{"endpoint":"/api/health/conda/r-bayesrel","tokens_estimated":80,"use_when":"you only need a 0-100 score for go/no-go (>=70 = safe)"},{"endpoint":"/api/prompt/conda/r-bayesrel","tokens_estimated":280,"use_when":"you want a plain-text LLM-friendly brief instead of JSON"},{"endpoint":"POST /api/check_bulk","tokens_estimated":60,"use_when":"you have 5+ packages to check; sends one round-trip instead of N"}],"docs":"https://depscope.dev/integrate","hint_bulk":"You've called /api/check 30 times in 60s. Save bandwidth + tokens with POST /api/check_bulk (1 round-trip for N pkgs)."},"requested_version":null,"_cache":"miss","_response_ms":501,"_powered_by":"depscope.dev — free package intelligence for AI agents","typosquat":{"is_suspected":false},"maintainer_trust":{"available":false},"malicious":{"is_malicious":false},"scorecard":{"available":false},"quality":{"available":false},"version_history_summary":{"total_versions":10,"first_release_age_days":1757,"last_release_days_ago":227,"avg_days_between_releases":195,"release_velocity":"moderate"}}