Power Analysis Sample Size Calculator Logistic Regression

Introduction & Importance

Power analysis sample size calculation for logistic regression is a crucial step in ensuring your study has enough statistical power to detect an effect of a given size. It helps you determine the appropriate sample size required to achieve a desired level of power and significance.

How to Use This Calculator

1. Enter the effect size (Odds Ratio), significance level (α), and desired power.
2. Click the “Calculate” button.
3. View the results below the calculator, including the required sample size and a chart illustrating power.

Formula & Methodology

The formula used in this calculator is based on the work of Kraemer and Blase (1986). It involves calculating the non-centrality parameter and then solving for the sample size using a numerical method.

Real-World Examples

Data & Statistics

Power Analysis Sample Sizes for Different Effect Sizes and Powers

Effect Size (OR)	Power	Sample Size (n)

Expert Tips

• Always consider the trade-off between power and sample size. Increasing power requires a larger sample size.
• Be mindful of the assumptions of logistic regression, such as linearity of independent variables and absence of multicollinearity.

Interactive FAQ

What is the default significance level (α)?

The default significance level is 0.05, but you can change it using the dropdown menu.

CDC’s Sample Size Calculator and UCLA’s Power Analysis are excellent resources for further learning.