Cited by 18Statistical Methods in EpidemiologyMeta-analysis and systematic reviewsClinical Reasoning and Diagnostic Skills

The Dot Plot: A Starting Point for Evaluating Test Performance

Krieg, Arthur F.·1988·JAMA

Abstract

We suggest that evaluations of diagnostic tests start with dot plots that depict multiple test results over multiple clinical states. From this starting point we can calculate posttest probabilities for multiple clinical states at multiple test results. Also, we can project one subset of clinical states as "disease positive" and a second subset as "disease negative" to provide standard analyses such as likelihood ratios, relative operating characteristic curves, posttest/pretest probability plots, sensitivity, specificity, and predictive value. Finally, this starting point provides an excellent basis for comparing multiple studies of diagnostic performance. The advantages of dot plots are illustrated with data on serum ferritin levels over multiple clinical states.

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Crossref · 10.1001/jama.1988.03410220093035

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Authors
Krieg, A. F.
Affiliations
Pennsylvania State University (US)
Corresponding author
Krieg, Arthur F.
Venue
JAMA
Published
1988-12-09
Volume
260
Issue
22
Pages
3309
ISSN
  • 0002-9955 (ISSN-L)
  • 0098-7484
OpenAlex
W1969008688
Cited by
18
References
25
Citations by year
2022: 1 · 2017: 1
FWCI
1.95
Type
journal article
Language
en
Open access
closed
Locations
  • JAMA (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
Keywords
dot plots, diagnostic test evaluation, post-test probability, likelihood ratios, sensitivity and specificity, predictive value, serum ferritin, disease states
MeSH terms
Iron Deficiencies, Ferritins, Humans, Predictive Value of Tests, Probability, ROC Curve

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