Diagnostic Accuracy Calculator
Calculates the proportion of all reference outcomes classified correctly. The form displays (TP+TN)/total beside diagnostic accuracy, using a worked condition that can be recalculated with the labeled inputs.
Set the labeled inputs
Diagnostic Accuracy
The question behind diagnostic accuracy
The diagnostic accuracy page calculates the proportion of all reference outcomes classified correctly.
Diagnostic Accuracy is limited to the statistical quantity named by the result panel. The diagnostic accuracy calculation does not silently add a population, time horizon, causal direction, or decision threshold that is absent from the fields.
How the inputs shape diagnostic accuracy
- True positives: For diagnostic accuracy, the worked value for true positives is 80 cases. Treat the true positives entry (80 cases) explicitly as a count, proportion, rate, estimate, or model parameter before comparing diagnostic accuracy conditions. The form enforces minimum 0.
- True negatives: For diagnostic accuracy, the worked value for true negatives is 90 cases. Treat the true negatives entry (90 cases) explicitly as a count, proportion, rate, estimate, or model parameter before comparing diagnostic accuracy conditions. The form enforces minimum 0.
- False positives: For diagnostic accuracy, the worked value for false positives is 10 cases. Treat the false positives entry (10 cases) explicitly as a count, proportion, rate, estimate, or model parameter before comparing diagnostic accuracy conditions. The form enforces minimum 0.
- False negatives: For diagnostic accuracy, the worked value for false negatives is 20 cases. Treat the false negatives entry (20 cases) explicitly as a count, proportion, rate, estimate, or model parameter before comparing diagnostic accuracy conditions. The form enforces minimum 0.
The entries used for diagnostic accuracy must refer to one coherent analysis condition. Combining incompatible populations, periods, or measurement definitions can produce valid diagnostic accuracy arithmetic for a nonexistent study.
How diagnostic accuracy is calculated
For diagnostic accuracy, match every symbol in the relationship to a labeled field before substituting numbers. Diagnostic Accuracy is reported in the scale implied by the inputs and formula.
While checking diagnostic accuracy, inspect every denominator in (TP+TN)/total. For diagnostic accuracy, a zero or near-zero denominator can make diagnostic accuracy undefined or unstable.
Worked values for diagnostic accuracy
The default diagnostic accuracy condition is True positives = 80 cases, True negatives = 90 cases, False positives = 10 cases, False negatives = 20 cases.
170 correct classifications out of 200 give accuracy .85.
The live calculator reports Diagnostic accuracy 0.85. Repeating one intermediate step from (TP+TN)/total provides a fixed diagnostic accuracy reference check for later code changes.
The surrounding workflow may also require false positive rate.
Assumptions behind diagnostic accuracy
Accuracy can hide asymmetric false-positive and false-negative costs.
For diagnostic accuracy, diagnostic and risk measures are conditional on named denominators, reference definitions, population prevalence, and follow-up time.
A second check on diagnostic accuracy
When interpreting diagnostic accuracy, keep the two-by-two counts or source risks with the result; a ratio alone can hide very different absolute event frequencies.
As a second check for diagnostic accuracy, reversing the numerator and denominator answers a different question, so retain the direction printed in (TP+TN)/total.
A practical stress test for diagnostic accuracy
Change true positives while holding the remaining entries fixed, then state why the direction and size of the diagnostic accuracy change are plausible from (TP+TN)/total.
Repeat the diagnostic accuracy exercise with false negatives. If a modest defensible change materially alters the interpretation, report both conditions rather than presenting that diagnostic accuracy scenario as exact.
Rebuilding this diagnostic accuracy calculation later
Report diagnostic accuracy using (TP+TN)/total, followed by the entered values, units, exclusions, and analysis date. Name the diagnostic accuracy population or dataset boundary instead of leaving it implicit.
Keep the full calculator output with the record, including Diagnostic accuracy 0.85. A later diagnostic accuracy review can then distinguish a changed input from a different convention or software implementation.
Questions about diagnostic accuracy
What should be saved with diagnostic accuracy?
Save the entered values and units for true positives, true negatives, false positives, false negatives, along with the analysis date, exclusions, software or formula version, and the relationship (TP+TN)/total. That record is sufficient to rebuild this specific diagnostic accuracy calculation.
Does diagnostic accuracy establish a causal or population conclusion?
No. The displayed diagnostic accuracy value is conditional on the entered data and named method. The diagnostic accuracy design, measurement process, and assumptions determine what can be concluded beyond those values.
How should diagnostic accuracy be rounded?
Keep the unrounded diagnostic accuracy for subsequent arithmetic, then report only the precision supported by the source measurements and the decision context. Extra digits in diagnostic accuracy do not correct sampling or model error.
Which input deserves the closest boundary check?
For diagnostic accuracy, start with false negatives and then true positives. Confirm the diagnostic accuracy units and allowed domain because a valid-looking entry can still describe the wrong statistical setup.
Why could another program report a different diagnostic accuracy?
A different convention for rounding, tails, ties, interpolation, parameterization, or missing values can change diagnostic accuracy. Compare the printed diagnostic accuracy formula and its input definitions before treating either output as wrong.