What is publication bias?

Positive results are more likely to be published than null results. This systematically inflates estimated effect sizes in literature and meta-analyses.

How large is publication bias inflation?

Studies estimate that published effect sizes are inflated by 20-100% in many fields. Highly selective journals and underpowered studies create the worst publication bias.

Publication Bias Meta-Analysis Inflation Calculator

Formula Definitions

The Publication Bias Meta-Analysis Inflation Calculator works by applying a well-defined formula to the values you enter. Understanding the formula behind the calculation helps you interpret the result and check that your inputs are correct. Below we break down the key components that drive the Publication Bias.

The core formula used by this calculator is:

Result = f(inputs, settings)

Each variable in the formula has a specific meaning:

inputs — Values entered into the Publication Bias.
settings — Options, units, or parameters that adjust how the calculation is performed.
Result — Computed output for the chosen inputs and settings.

How to Use This Calculator

Enter the required values. Enter the required values into the Publication Bias Meta-Analysis Inflation Calculator input fields.
Adjust settings. Adjust any settings, select applicable options, or choose units as needed.
Calculate the result. Press Calculate to compute the result using the underlying formula.
Interpret the output. Review and interpret your result using the provided context, reference ranges, or explanatory notes.

Glossary and Definitions

Input: A value entered into the calculator to be processed.
Output: The computed result returned by the calculator for the given inputs.
Setting: An option that adjusts how the calculation is performed, such as unit selection or mode.
Publication bias: A key concept referenced by the Publication Bias: Calculate the inflation in meta-analytic effect sizes due to publication bias. Apply funnel plot asymmetry analysis and trim-and-fill correction to estimate the true underlying effect size adjusting for missing null results.
Meta-analysis inflation: A key concept referenced by the Publication Bias: Calculate the inflation in meta-analytic effect sizes due to publication bias. Apply funnel plot asymmetry analysis and trim-and-fill correction to estimate the true underlying effect size adjusting for missing null results.
Funnel plot asymmetry: A key concept referenced by the Publication Bias: Calculate the inflation in meta-analytic effect sizes due to publication bias. Apply funnel plot asymmetry analysis and trim-and-fill correction to estimate the true underlying effect size adjusting for missing null results.
File drawer problem: A key concept referenced by the Publication Bias: Calculate the inflation in meta-analytic effect sizes due to publication bias. Apply funnel plot asymmetry analysis and trim-and-fill correction to estimate the true underlying effect size adjusting for missing null results.

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