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Cited by 921

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Statistical Methodology: I. Incorporating the Prevalence of Disease into the Sample Size Calculation for Sensitivity and Specificity

Buderer, Nancy M. Fenn·1996·Academic Emergency Medicine

Abstract

Careful consideration of statistical issues related to the choice of a sample size is critical for achieving meaningful results in research studies designed to evaluate diagnostic tests. When assessing the ability of a diagnostic test to screen for disease, the parameters sensitivity, specificity, and predictive values are of interest. Study sample size requirements can be calculated based on a clinically acceptable degree of precision, the hypothesized values of sensitivity and specificity, and the estimated prevalence of disease in the target population. The simple methods and tables in this paper guide the researcher when deciding how many subjects to sample in a study designed to estimate both the sensitivity and the specificity of a diagnostic test, given a specified precision and estimated disease prevalence.

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Crossref · 10.1111/j.1553-2712.1996.tb03538.x

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Metadata

Authors
Buderer, N. M. F.
Venue
Academic Emergency Medicine
Publisher
Wiley
Published
1996-09
Volume
3
Issue
9
Pages
895-900
ISSN
  • 1069-6563 (ISSN-L)
  • 1553-2712
OpenAlex
W2022961959
Cited by
921
References
0
FWCI
1.19
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Statistical Methodology: I. Incorporating the Prevalence of Disease into the Sample Size Calculation for Sensitivity and Specificity. https://app.cochat.ai/papers/10.1111/j.1553-2712.1996.tb03538.x
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Buderer, N. M. F. (1996). Statistical Methodology: I. Incorporating the Prevalence of Disease into the Sample Size Calculation for Sensitivity and Specificity. Academic Emergency Medicine. https://doi.org/10.1111/j.1553-2712.1996.tb03538.x

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.