Assess risk of bias in research studies using RoB 2, ROBINS-I, QUADAS-2, and QUIPS.
npx skills add https://github.com/astoreyai/ai_scientist --skill risk-of-bias
Please help me install this Agent Skill. Skill: risk-of-bias Source: https://github.com/astoreyai/ai_scientist/tree/main/skills/risk-of-bias Command: npx skills add https://github.com/astoreyai/ai_scientist --skill risk-of-bias
This Skill provides a framework for systematic bias assessment across study designs.
Apply RoB 2 to an included RCT and categorize risks by domain.
High-intent search queries and answers about installing and using this skill.
Risk of bias assessment in RCTs uses RoB 2 (Cochrane), evaluating five domains: randomization process, deviations from interventions, missing outcome data, outcome measurement, and selective reporting. The tool produces standardized risk ratings—low, some concerns, or high—to inform study quality judgments and meta-analysis planning.
Each tool targets specific study designs: RoB 2 for randomized controlled trials, ROBINS-I for non-randomized studies, QUADAS-2 for diagnostic accuracy studies, and QUIPS for prognostic studies. Choosing the correct tool ensures domain assessment aligns with study design and supports valid GRADE assessments.
Yes. Beyond RCTs, risk of bias frameworks extend to diagnostic studies via QUADAS-2 and prognostic studies via QUIPS. Both tools assess measurement quality, reporting completeness, and potential sources of bias relevant to their respective study designs.
Bias assessment produces standardized quality ratings and domain-level risk judgments that feed directly into systematic review documentation, GRADE certainty-of-evidence judgments, and meta-analysis sensitivity planning. This integration supports transparent study selection and interpretation.
ROBINS-I evaluation for non-randomized studies covers bias in confounding, participant selection, classification of interventions, deviations from intended interventions, missing data, outcome measurement, and selective reporting. Domain-specific guidance supports standardized judgment across heterogeneous study populations.
AI4EFinEvaluate scientific claims using GRADE and Cochrane risk-of-bias assessments.
lyndonklFormulates PICOT questions and grades evidence certainty using GRADE frameworks.
HolobiomicsLabEvaluate scientific claims by analyzing methodology, biases, and evidence strength.
shaitamam-80Evaluate risk of bias across studies using RoB 2.0, ROBINS-I, NOS, QUADAS-2, and QUIPS.
