Cluster-crossover design: a method for limiting clusters level effect in community-intervention studies

Area of Science:

• Clinical Trials Methodology
• Biostatistics
• Epidemiology

Background:

• The cluster-crossover design is suitable for comparative clinical trials in naturally occurring populations (clusters).
• It differs from standard crossover designs by allocating treatment sequences at the cluster level.
• This design can be viewed as a cluster-randomized trial with repeated cluster-level randomization or treatment permutations.

Purpose of the Study:

• To explain the cluster-crossover design for clinical trials.
• To illustrate the impact of statistical models on interpreting results from this design.
• To analyze original data from two hospital infection control field studies.

Main Methods:

• Utilizing a cluster-crossover design for comparative intervention studies.
• Employing hierarchical models with random effects for data analysis.
• Analyzing data from two published field studies on hospital infection control.

Main Results:

• Demonstrating the influence of various statistical models on study interpretation.
• Highlighting the necessity of appropriate analytical approaches for cluster-crossover data.
• Providing practical insights through real-world case studies.

Conclusions:

• The cluster-crossover design offers a robust framework for certain clinical trials.
• Appropriate statistical analysis, particularly hierarchical modeling, is crucial for valid interpretation.
• The study underscores the importance of methodological rigor in complex trial designs.