Survival, clinical and meta-analysis

ROC Curve and AUC Calculator

Evaluate how well a continuous score separates two groups, such as a biomarker for disease. You get the AUC with its confidence interval and the cut-off that maximizes Youden’s index.

Free · No sign-upReplaces SPSS · MedCalcWorks with your data

Updated 13 October 2026 · By Bibin Xavier

Data 150 × 4

Paste from Excel, or drop a CSV, TSV or Excel file here.Upload file

Example data 150 rows, 4 variables. Data stays in this browser tab.

Patienttext · 150 levels	Diagnosistext · 2 levels	Biomarkernumeric	Agenumeric
P001	Healthy	4.93	64
P002	Disease	4.5	43
P003	Healthy	4.08	54
P004	Healthy	3.52	63
P005	Healthy	5.36	76
P006	Disease	5.92	61
P007	Healthy	4.4	67
P008	Healthy	3.09	66

Variables and options

Test score

True state

Positive state

Results update automatically when you change an option.

Results

150 rows · example data

AUC.820[.750, .891]

Optimal cut-off (Youden)5.02score ≥ 5.02 = positive

Sensitivity81.5%

Specificity74.1%

Table 1

Area under the curve

AUC	SE	95% CI	z	p (AUC = .5)	Positive · negative
.820	.036	[.750, .891]	8.89	< .001	65 · 85

Note. Hanley-McNeil standard error. Higher scores are treated as more likely positive; an AUC below .5 means the reverse.

Table 2

Coordinates of the curve

Cut-off (≥)	Sensitivity	Specificity	Youden J
0.46	1.000	.012	.012
3.09	.985	.141	.126
3.52	.954	.247	.201
3.92	.908	.388	.296
4.28	.892	.506	.398
4.54	.877	.635	.512
5.00	.815	.718	.533
5.02 ★	.815	.741	.557
5.30	.692	.788	.481
5.71	.600	.871	.471
6.08	.446	.906	.352
6.49	.338	.965	.303
6.84	.185	.988	.173
8.00	.015	1.000	.015

ROC curve

Interpretation

Biomarker shows good discrimination between Disease and the other group (AUC = .820). At the cut-off 5.02, it detects 81.5% of positive cases while correctly clearing 74.1% of negatives.

AUC = .82, 95% CI [.75, .89], p < .001; optimal cut-off 5.02 (sensitivity 81.5%, specificity 74.1%).

How to cite this tool

Using these results in a thesis, journal article, report or class assignment? Please cite this free tool so others can find it. It keeps the site free.

APA 7

Xavier, B. (2026). ROC Curve and AUC Calculator [Web application]. FreeStatisticalTools.com. https://freestatisticaltools.com/roc-curve-auc-calculator/

BibTeX

@software{xavier_roccurve_2026,
  author = {Xavier, Bibin},
  title = {ROC Curve and AUC Calculator},
  publisher = {FreeStatisticalTools.com},
  year = {2026},
  url = {https://freestatisticaltools.com/roc-curve-auc-calculator/},
  note = {Web application}
}

Suggested sentence for your methods section: “The analysis was carried out with the free ROC Curve and AUC Calculator tool on FreeStatisticalTools.com (Xavier, 2026).”

What is an ROC curve?

A receiver operating characteristic (ROC) curve shows how well a continuous score separates two groups across all possible thresholds. The area under the curve summarizes accuracy in one number.

When to use an ROC curve

Use it to judge a diagnostic test or a risk score, and to choose a threshold.

How to use this tool

Enter your data. Paste columns from Excel, Google Sheets or SPSS with variable names in the first row, or upload a CSV or Excel file. The example data shows the expected layout.
Choose the variables. Select the test score, true state and positive state.
Read the results. Results update automatically. Read the plain-English interpretation, then use Copy table to paste APA-style tables into Word and Copy for the results sentence.

How to report an ROC curve in APA style

Report the AUC with its 95% CI, the chosen cut-off and its sensitivity and specificity.

Frequently asked questions

What is a good AUC?

An AUC of .5 is no better than chance, .7–.8 is fair, .8–.9 good and above .9 excellent.

How is the optimal cut-off chosen?

By maximizing Youden’s J = sensitivity + specificity − 1.

What if my AUC is below .5?

Higher scores are treated as more likely positive. An AUC below .5 means lower scores indicate the positive state.

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