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Calculator · deterministic

Sample size: sensitivity above a threshold

Showing a test's sensitivity exceeds a clinical threshold: cases from the expected value and the threshold.

Calculator

No AI, no sign-up — the arithmetic runs in the server-side deterministic solver, validated against G*Power and R pwr.

The value you expect the test to actually reach (0–1).
The lower bound for calling the test clinically useful; must be below the expected value.

When to use it

If the question is not "what is the sensitivity?" but "is sensitivity above 80%?", you are here: a one-sided single-proportion test. If there is no threshold and the aim is simply to measure, the precision-based calculator is the right tool — the two questions give different samples.

Where the inputs come from

  • Threshold (p₀): comes from a guideline, a regulatory requirement or clinical consensus; cite it.
  • Expected value (p₁): the closer it sits to the threshold, the larger the sample; that gap is this test's "effect size".

Worked example

With an expected sensitivity of 0.90 against a threshold of 0.80, the solver requires 77 diseased cases at 80% power; with 20% unevaluable exams the target becomes 97. Try moving the expected value to 0.85 (closer to the threshold) and watch the sample grow.

How to write it in the protocol

Fill-in methods sentence

“The primary hypothesis is that sensitivity exceeds the threshold of [threshold, with source]. Assuming an expected sensitivity of [value] [with source], the single-proportion test required [n] diseased cases at 80% power; allowing [x]% losses, [N] were targeted.”

Sources

  1. Cohen J. Statistical Power Analysis for the Behavioral Sciences, 2nd ed. Lawrence Erlbaum; 1988.
  2. Faul F, Erdfelder E, Lang A-G, Buchner A. G*Power 3: a flexible statistical power analysis program. Behav Res Methods. 2007;39:175–191.
  3. Champely S. pwr: Basic Functions for Power Analysis (R package).

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