Why analysis of variance is inappropriate for multiclinic trials

Area of Science:

• Clinical trials
• Statistical analysis
• Multiclinic studies

Background:

• Analysis of variance (ANOVA) models have specific assumptions.
• Violating these assumptions can impact clinical trial outcomes.
• Multiclinic studies frequently violate ANOVA assumptions.

Purpose of the Study:

• To explore the reduction in statistical power due to assumption violations in clinical trials.
• To investigate the impact of heterogeneity of variance and floor/ceiling effects on trial power.
• To propose alternative statistical methods that preserve power in multiclinic studies.

Main Methods:

• Examining power reduction from heterogeneity of variance.
• Analyzing power reduction from floor and ceiling effects.
• Proposing alternative statistical analyses.

Main Results:

• Violations of ANOVA assumptions decrease statistical power to detect treatment effects.
• Heterogeneity of variance across sites reduces power.
• Floor and ceiling effects also diminish statistical power.

Conclusions:

• Standard ANOVA assumptions are often violated in multiclinic trials, leading to reduced power.
• Alternative statistical methods are necessary to maintain the power of clinical trials.
• Addressing variance heterogeneity and boundary effects is crucial for accurate treatment effect detection.