Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Intervals for posttest probabilities: a comparison of 5 methods.

D Mossman1, J O Berger

  • 1Division of Forensic Psychiatry, Wright State University School of Medicine, Dayton, Ohio, 45401-0927, USA. dmossman@pol.net

Medical Decision Making : an International Journal of the Society for Medical Decision Making
|January 5, 2002
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Malpractice and the psychiatrist : a primer for residents.

Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry·2014
Same author

The -149C>T SNP within the DeltaDNMT3B gene, is not associated with early disease onset in hereditary non-polyposis colorectal cancer.

Cancer letters·2008
Same author

Avoiding errors about 'margins of error'.

The British journal of psychiatry : the journal of mental science·2007
Same author

"A fool for a client": print portrayals of 49 pro se criminal defendants.

The journal of the American Academy of Psychiatry and the Law·2002
Same author

The meaning of malingering data: further applications of Bayes' theorem.

Behavioral sciences & the law·2001
Same author

Conventional and atypical antipsychotics and the evolving standard of care.

Psychiatric services (Washington, D.C.)·2000
Same journal

Flexible Survival Extrapolation with Blended Hazards: Accounting for Treatment Effect Waning in Health Technology Assessment.

Medical decision making : an international journal of the Society for Medical Decision Making·2026
Same journal

A Microsimulation Model for Chronic Kidney Disease Progression in Type 2 Diabetes Patients in the United States: Michigan Model for Diabetes-Chronic Kidney Disease Model.

Medical decision making : an international journal of the Society for Medical Decision Making·2026
Same journal

Cardiovascular Risk Estimation and Statin Adherence: A Historical Cohort Study.

Medical decision making : an international journal of the Society for Medical Decision Making·2026
Same journal

Taste or Scale? Methodological Approach to Health Preferences Comparison across Groups.

Medical decision making : an international journal of the Society for Medical Decision Making·2026
Same journal

Mind the Gap: Impact of New Labels on Public Perceptions and Calculated Risk of Adverse Outcomes after a Melanoma In Situ Diagnosis-A Secondary Analysis of an Online Randomized Experiment.

Medical decision making : an international journal of the Society for Medical Decision Making·2026
Same journal

A Metamodel-Based General-Purpose Autocalibration Tool for Simulation Models.

Medical decision making : an international journal of the Society for Medical Decision Making·2026
See all related articles

Accurate confidence intervals for posttest probabilities are crucial. An objective Bayesian approach effectively generates reliable intervals, especially in small-sample situations.

Area of Science:

  • Biostatistics
  • Medical Informatics
  • Diagnostic Test Evaluation

Background:

  • Limited research exists on confidence intervals for posterior odds or positive predictive value.
  • Existing literature primarily focuses on confidence intervals for single proportions and likelihood ratios.

Purpose of the Study:

  • To systematically study and evaluate methods for constructing confidence intervals for posttest probabilities.
  • To assess the coverage properties of different interval construction methods.

Main Methods:

  • Described and evaluated five distinct methods for confidence interval construction.
  • Utilized empirical data for estimates of sensitivity, specificity, and pretest probability.
  • Assessed interval coverage properties against nominal values.

Related Experiment Videos

Main Results:

  • All five methods demonstrated appropriate coverage when sample sizes exceed 80 and estimates are not near 0 or 1.
  • An objective Bayesian approach, implemented via spreadsheet simulation, performed best under suboptimal conditions (small samples, extreme estimates).

Conclusions:

  • Physicians and researchers can use the objective Bayesian approach to generate accurate confidence intervals for posttest probabilities.
  • This method is particularly valuable for small-sample scenarios in diagnostic test evaluation.