What are Biostatistics?

Biostatistics is the application of statistical methods to biological and health-related data. It involves collecting, examining, interpreting, and presenting data to understand patterns, make predictions, and inform decisions in fields like medicine, public health, and biology.

How to use the MathCalc Biostatistics calculator?

A quick step-by-step guide:
1. Choose an analysis type from the drop-down lists.
• Survival analysis
• ROC Curve analysis
• Epidemiological measure
• Clinical test design
• Diagnostic test evaluation
• Relative risk & odds ratio
2. Enter True positive.
3. Enter True Negative.
4. Enter False Positive.
5. Enter False Negative.
6. Enter Exposed & Diseased.
7. Enter Exposed & healthy.
8. Enter Unexposed & Diseased.
9. Enter Unexposed & Healthy.
10. Enter the Sample size per group.
11. Enter the expected effect size.
12. Enter statistical power.
13. Enter Alpha level.
14. Enter survival times separated by commas.
15. Enter Censored status (1 = event, 0 = censored).
16. After entering the values, click “calculate”, and in seconds, you will see the result.

Choose Analysis Type “Survival analysis”

Survival times = 3, 5, 8, 12, 15
Censored status = 1, 0, 1, 0, 1

Choose Analysis Type “ROC Curve analysis”

True positive: 50, False positive: 20, True negative: 100, False negative: 30

Choose Analysis Type “Epidemiological Measures”

True Positive: 45, True Negative: 130, False Positive: 15, False Negative: 10, Exposed & Diseased: 40, Exposed & Healthy: 60, Unexposed & Diseased: 15, Unexposed & Healthy: 85

Choose Analysis Type “Clinical trial design”

Expected Effect Size: 0.50, Statistical Power: 0.80, Alpha Level: 0.05, (Leave all other fields blank.)

Choose Analysis Type “Diagnostic test evaluation”

True positive: 80, True negative: 90, False positive: 10, False negative: 20

Solution:
Sensitivity = TP/(TP+FN) = 80/(80+20) = 0.8
Specificity = TN/(TN+FP) = 90/(90+10) = 0.9
PPV = TP/(TP+FP) = 80/(80+10) = 0.8889
NPV = TN/(TN+FN) = 90/(90+20) = 0.8182
Accuracy = (TP+TN)/(TP+TN+FP+FN) = 0.85

Result:
Sensitivity: 0.8
Specificity: 0.9
PPV: 0.8889
NPV: 0.8182
Accuracy: 0.85

Choose Analysis Type “Relative risk & odds ratio”

Exposed & Diseased: 30, Exposed & healthy: 70, Unexposed & diseased = 12, Unexposed & healthy: 88

Solution:
2×2 Contingency Table Analysis:
Risk in exposed = a/(a+b) = 30/(30+70) = 0.3
Risk in unexposed = c/(c+d) = 12/(12+88) = 0.12
Relative Risk = 0.3/0.12 = 2.5
Odds Ratio = (a×d)/(b×c) = (30×88)/(70×12) = 3.1429

Result:
Relative risk: 2.5
Odds ratio: 3.1429
Risk exposed: 0.3
Risk unexposed: 0.12

Why use the MathCalc biostatistics calculator?

Get Quick Results

If you are finding survival analysis, relative risk & odds ratio, ROC Curves, epidemiological measures, clinical trial design, and diagnostic test evaluation by hand, it can be time-consuming, especially when dealing with large values. This MathCalc biostatistics calculator gives you accurate results in seconds.

Reduce Human Error

Manual math can lead to minor mistakes that cost you money or points. This tool provides proven formulas to reduce errors, and your results are always right. To avoid miscalculations, use the MathCalc biostatistics calculator.

User-Friendly

These free biostatistics calculators calculate survival analysis, relative risk & odds ratio, ROC Curves, epidemiological measures, clinical trial design, and diagnostic test evaluation in one calculator. This calculator is helpful for students and teachers.

FAQ

What is the difference between Relative risk and odds ratio?

Relative risk compares risks: exposed risk ÷ unexposed risk. Odds ratio compares odds: (a·d)/(b·c). Relative risk is intuitive for cohorts and is common in case-control studies and logistic regression.

When should I use survival analysis?

Use it when the outcome is “time until event”, and some subjects are censored (they did not experience the event during follow-up).