Reliability and statistical power: Conceptual background and practical implications

Area of Science:

• Behavioral Sciences
• Psychometrics
• Statistical Modeling

Background:

• Robust phenomena with large effect sizes and statistical power can be unreliable.
• This challenges the view that power and reliability are similarly dependent on measurement error.
• The concept of a reliability paradox arises from robust yet unreliable phenomena.

Purpose of the Study:

• To review and discuss the influence of measurement error and individual differences on phenomenon reliability and robustness.
• To clarify the relationship between relative reliability and robustness.
• To explore methods for optimizing measured phenomenon reliability and robustness.

Main Methods:

• Review of statistical literature on the relationship between statistical power and reliability.
• Discussion of measurement error and individual differences.
• Analysis of absolute versus relative reliability.

Main Results:

• Statistical power and reliability are not always similarly dependent on measurement error.
• Relative reliability and robustness are partly related but generally independent.
• A common misconception confounds absolute reliability with relative reliability.

Conclusions:

• Measurement error and individual differences significantly impact relative reliability and robustness.
• Understanding the independence of reliability and robustness is crucial.
• Measurement error and group heterogeneity can be manipulated to improve phenomenon robustness.