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Open toolMultiple Testing Correction Calculator
Adjust p values using Bonferroni, Holm and Benjamini-Hochberg, preserving the original order. Provide Original-order p values, Significance threshold α to compute results directly in your browser. Use 1-1,000 p values in [0,1]. Holm uses a forward cumulative maximum, BH a reverse cumulative minimum. A method rejects when its adjusted p ≤ supplied alpha; dependence assumptions and study design remain the user’s responsibility. Numeric output uses up to 12 significant digits; floating-point rounding can occur. Common search workflows supported include "bonferroni adjustment calculator".
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Enter the inputs, then select Calculate.
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How the Multiple Testing Correction Calculator Works & Core Formula
The Multiple Testing Correction Calculator evaluates Original-order p values, Significance threshold α in client-side JavaScript using the deterministic rule below and updates the output panel immediately without uploading data to a server.
Adjust p values using Bonferroni, Holm and Benjamini-Hochberg, preserving the original order.
Use 1-1,000 p values in [0,1]. Holm uses a forward cumulative maximum, BH a reverse cumulative minimum. A method rejects when its adjusted p ≤ supplied alpha; dependence assumptions and study design remain the user’s responsibility. Numeric output uses up to 12 significant digits; floating-point rounding can occur.
Multiple Testing Correction Calculator Quick Reference & Input Guide
Review the input parameters, allowed value ranges, and worked reference cases for the Multiple Testing Correction Calculator below before running your calculation.
| Parameter / Scenario | Default / Sample Value | Rule or Allowed Range | Output / Usage Note |
|---|---|---|---|
| Input: Original-order p values | 0.01,0.04,0.2 | Separate finite decimal values with commas, spaces or newlines; at most 1,000 values, each within ±1e12. | Required workspace parameter |
| Input: Significance threshold α | 0.05 | Range: 0 to 1 | Required workspace parameter |
| Worked Case 1: Baseline run (Original-order p values = 0.01,0.04,0.2) | Preloaded / test values | Adjust p values using Bonferroni, Holm and Benjamini-Hochberg, preserving the original order | Original-order p values = 0.01,0.04,0.2; Significance threshold α = 0.05. Output: Results in original order: 1: p=0.01; Bonferroni=0.03 (reject); Holm=0.03 (reject); BH=0.03 (reject); 2: p=0.04; Bonferroni=0.12 (retain); Holm=0.08 (retain); BH=0.06 (retain); 3: p=0.2; Bonferroni=0.6 (retain); Holm=0.2 (retain); BH=0.2 (retain); Alpha: 0.05. |
| Worked Case 2: Comparison scenario (Comparison original-order p values check) | Preloaded / test values | Adjust p values using Bonferroni, Holm and Benjamini-Hochberg, preserving the original order | Original-order p values = 0,0.5,1; Significance threshold α = 0.1. Output: Results in original order: 1: p=0; Bonferroni=0 (reject); Holm=0 (reject); BH=0 (reject); 2: p=0.5; Bonferroni=1 (retain); Holm=1 (retain); BH=0.75 (retain); 3: p=1; Bonferroni=1 (retain); Holm=1 (retain); BH=1 (retain); Alpha: 0.1. |
Step-by-Step Guide to Using the Multiple Testing Correction Calculator
Follow these three steps to configure Original-order p values, Significance threshold α, verify unit and boundary rules, and export your Multiple Testing Correction Calculator output.
Enter the inputs
Start with original-order p values. Separate finite decimal values with commas, spaces or newlines; at most 1,000 values, each within ±1e12.
Input and settings
Check units and mode
Use 1–1,000 p values in [0,1]. Holm uses a forward cumulative maximum, BH a reverse cumulative minimum. A method rejects when its adjusted p ≤ supplied alpha; dependence assumptions and study design remain the user’s responsibility. Numeric output uses up to 12 significant digits; floating-point rounding can occur.
Tool result
Calculate and save
Select Calculate, check the labelled result, then use Copy result or Download result.txt.
Review the details
Practical Worked Examples for Multiple Testing Correction Calculator
These concrete scenarios illustrate how the Multiple Testing Correction Calculator processes baseline inputs, comparison checks, and boundary constraints.
Baseline run (Original-order p values = 0.01,0.04,0.2)
Original-order p values = 0.01,0.04,0.2; Significance threshold α = 0.05. Output: Results in original order: 1: p=0.01; Bonferroni=0.03 (reject); Holm=0.03 (reject); BH=0.03 (reject); 2: p=0.04; Bonferroni=0.12 (retain); Holm=0.08 (retain); BH=0.06 (retain); 3: p=0.2; Bonferroni=0.6 (retain); Holm=0.2 (retain); BH=0.2 (retain); Alpha: 0.05.
Comparison scenario (Comparison original-order p values check)
Original-order p values = 0,0.5,1; Significance threshold α = 0.1. Output: Results in original order: 1: p=0; Bonferroni=0 (reject); Holm=0 (reject); BH=0 (reject); 2: p=0.5; Bonferroni=1 (retain); Holm=1 (retain); BH=0.75 (retain); 3: p=1; Bonferroni=1 (retain); Holm=1 (retain); BH=1 (retain); Alpha: 0.1.
Boundary & unit check (Bonferroni Adjustment Calculator)
When solving for 'bonferroni adjustment calculator', verify that Original-order p values, Significance threshold α use consistent units and stay within the documented scope: Use 1-1,000 p values in [0,1]. Holm uses a forward cumulative maximum, BH a reverse cumulative minimum. A method rejects when its adjusted p ≤ supplied alpha; dependence assumptions and study design remain the user’s responsibility. Numeric output uses up to 12 significant digits; floating-point rounding can occur.
How to Read and Verify the Multiple Testing Correction Calculator Output
The output panel reports the exact result derived from Original-order p values, Significance threshold α alongside any unit or formatting notes.
Every calculation follows the rule: Adjust p values using Bonferroni, Holm and Benjamini-Hochberg, preserving the original order. Because JavaScript uses IEEE 754 double-precision floating-point arithmetic, numeric outputs display up to 12 significant digits where applicable.
Always cross-check the displayed result against the scope note (Use 1-1,000 p values in [0,1]. Holm uses a forward cumulative maximum, BH a reverse cumulative minimum. A method rejects when its adjusted p ≤ supplied alpha; dependence assumptions and study design remain the user’s responsibility. Numeric output uses up to 12 significant digits; floating-point rounding can occur) before applying the value to production specifications, financial models, or lab records.
Scope Limits, Accuracy Assumptions & Related Everyday Math Tools
Review these boundary constraints and validation rules before relying on the Multiple Testing Correction Calculator output.
Operational scope: Use 1-1,000 p values in [0,1]. Holm uses a forward cumulative maximum, BH a reverse cumulative minimum. A method rejects when its adjusted p ≤ supplied alpha; dependence assumptions and study design remain the user’s responsibility. Numeric output uses up to 12 significant digits; floating-point rounding can occur. Inputs that violate minimum/maximum bounds or required format rules are rejected with a clear diagnostic prompt.
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Open toolFrequently Asked Questions About Multiple Testing Correction Calculator
Answers about using Multiple Testing Correction Calculator and understanding its results.
How do I calculate bonferroni adjustment calculator using the Multiple Testing Correction Calculator?
The Multiple Testing Correction Calculator applies the rule: Adjust p values using Bonferroni, Holm and Benjamini-Hochberg, preserving the original order. Enter Original-order p values, Significance threshold α into the workspace and the tool computes the exact output in your browser.
What input parameters and units are required for Multiple Testing Correction Calculator?
Yes. Provide Original-order p values, Significance threshold α using the documented units and format shown in the quick reference table above. Preloaded default values let you test the workflow immediately.
What are the accuracy limits and boundary assumptions for Multiple Testing Correction Calculator?
Use 1-1,000 p values in [0,1]. Holm uses a forward cumulative maximum, BH a reverse cumulative minimum. A method rejects when its adjusted p ≤ supplied alpha; dependence assumptions and study design remain the user’s responsibility. Numeric output uses up to 12 significant digits; floating-point rounding can occur. Confirm that your inputs fall within the allowed ranges before exporting the result.
Is the Multiple Testing Correction Calculator free and does it keep my inputs private?
Yes. All calculations for the Multiple Testing Correction Calculator execute 100% locally in your browser's JavaScript runtime. No inputs or results are uploaded to any external server.
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