Statistical power and categorical outcomes
Categorical outcomes decrease statistical power and increase the needed sample size
Categorical and nominal variables decrease statistical power and increase the needed sample size to detect significant effects. This is due to categorical measurement possessing decreased precision and accuracy.
Less powerful non-parametric statistics are used with categorical outcomes. Less precision and accuracy of treatment effects is yielded from non-parametric statistics as well.
Categorical outcomes are very prevalent in medicine, so researchers should plan to either measure for large effect sizes or collect larger sample sizes to achieve adequate statistical power.
Less powerful non-parametric statistics are used with categorical outcomes. Less precision and accuracy of treatment effects is yielded from non-parametric statistics as well.
Categorical outcomes are very prevalent in medicine, so researchers should plan to either measure for large effect sizes or collect larger sample sizes to achieve adequate statistical power.
Categorical outcomes decrease statistical power and increase the needed sample size.
Click on the Power and Research Design button to continue.
Hire A Statistician
DO YOU NEED TO HIRE A STATISTICIAN?
Eric Heidel, Ph.D., PStat will provide you with statistical consultation services for your research project at $100/hour. Secure checkout is available with Stripe, Venmo, Zelle, or PayPal.
- Statistical Analysis on any kind of project
- Dissertation and Thesis Projects
- DNP Capstone Projects
- Clinical Trials
- Analysis of Survey Data