Diagnostic Accuracy · SPEC-1S

Sample Size for Testing One Specificity

Plan sample size for testing one diagnostic-test specificity against a fixed benchmark specificity.

1. Planning setup

Planned sampling approach

Known negative participantsRecruit reference-standard-negative participants directly.Consecutive / cross-sectional samplingRecruit from the target population; anticipated prevalence is required.

2. Information obtained from previous studies or literature

Minimum acceptable specificity (%) P0

Enter the benchmark specificity obtained from a previous study, published literature, pilot data, or another defensible source.

3. Information to be decided by the researcher

Expected improvement in specificity (%) Delta = P1 - P0

Decide the expected increase above P0. The specificity under the alternative hypothesis is calculated as P1 = P0 + Delta.

Test direction

Significance level (%)

Desired power (%)

Anticipated dropout/non-response (%)

Expected proportion of reference-standard-negative participants with incomplete or unusable index-test or reference-standard data.

4. Results

Enter the one-specificity testing assumptions and select Calculate.

Formula, assumptions, limitations, and methodological note

Example clinical scenario

A study evaluates whether a cervical-cancer screening test has specificity exceeding a prespecified minimum among participants without cervical disease.

Formula and methodological note

Scope and limitations: Use this calculator only for the diagnostic design named on this page and its stated independent or paired sampling assumptions. It does not cover clustering, repeated lesions, multiple-reader designs, prediction-model development, or non-inferiority/equivalence unless explicitly stated. The implemented normal or binormal approximation may be unsuitable near parameter boundaries or with sparse reference-standard groups. Where prevalence is used, it supports recruitment planning and does not necessarily form part of the core precision or hypothesis-test calculation.

This calculator uses a normal-approximation method for testing one diagnostic-test specificity against a fixed benchmark specificity.

Z alpha = Z(1 - alpha / 2) for a two-sided test, or Z(1 - alpha) for one-sided superiority.

Z power = Z(power)

P1 = P0 + Delta

n raw = [Z alpha x sqrt(P0 x (1 - P0)) + Z power x sqrt(P1 x (1 - P1))]^2 / (P1 - P0)^2

n analysable = ceiling(n raw)

n negative recruitment = ceiling(n analysable / (1 - dropout))

N total recruitment = ceiling(n negative recruitment / (1 - prevalence)), when prevalence is entered.

Method references

Hajian-Tilaki K. Sample size estimation in diagnostic test studies of biomedical informatics. Journal of Biomedical Informatics. 2014;48:193-204.

Suggested citation

Yaacob, Najib Majdi. “Sample Size for Testing One Specificity (SPEC-1S).” Web calculator. NajibMY, 2026. Accessed July 29, 2026. https://najibmy.netlify.app/tools/sample-size/diagnostic-accuracy/one-specificity/.