PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration

Karel G M Moons, Robert F Wolff, Richard D Riley, Penny F Whiting, Marie Westwood, Gary S Collins, Johannes B Reitsma, Jos Kleijnen, Sue Mallett

Research output: Contribution to journalArticleAcademicpeer-review

Original languageEnglish
Pages (from-to)W1-W33
Number of pages33
JournalAnnals of Internal Medicine
Volume170
Issue number1
DOIs
Publication statusPublished - 1 Jan 2019

Keywords

  • Bias
  • Decision Support Techniques
  • Diagnosis
  • Humans
  • Models, Statistical
  • Prognosis
  • Research Design/standards
  • Systematic Reviews as Topic
  • DIAGNOSTIC-TEST ACCURACY
  • PARTIAL VERIFICATION
  • INTERNAL VALIDATION
  • PROGNOSTIC MODELS
  • LOGISTIC-REGRESSION ANALYSIS
  • EXTERNAL VALIDATION
  • INDIVIDUAL PARTICIPANT DATA
  • CARDIOVASCULAR-DISEASE
  • EMPIRICAL-EVIDENCE
  • MULTIPLE IMPUTATION

Cite this

Moons, K. G. M., Wolff, R. F., Riley, R. D., Whiting, P. F., Westwood, M., Collins, G. S., Reitsma, J. B., Kleijnen, J., & Mallett, S. (2019). PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration. Annals of Internal Medicine, 170(1), W1-W33. https://doi.org/10.7326/M18-1377