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Sample size considerations for split-mouth design.

Hong Zhu1, Song Zhang1, Chul Ahn1

  • 1Division of Biostatistics, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.

Statistical Methods in Medical Research
|August 26, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces generalized estimating equation (GEE) methods for calculating sample sizes in split-mouth dental trials. These formulas enhance efficiency by accounting for within-subject correlations, crucial for accurate treatment effect estimation.

Keywords:
Continuous and binary outcomesdental clinical trialgeneralized estimating equationsample sizesplit-mouth

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Area of Science:

  • Dental Clinical Research
  • Biostatistics
  • Experimental Design

Background:

  • Split-mouth designs are common in dental research, reducing inter-subject variability.
  • Existing statistical methods are well-developed, but sample size considerations are lacking.
  • Efficiency of split-mouth over parallel-group designs depends on substantial within-subject correlation.

Purpose of the Study:

  • To propose sample size calculation methods for split-mouth trials using the generalized estimating equation (GEE) approach.
  • To provide closed-form sample size formulas for continuous and binary outcomes.
  • To account for within-subject correlations in split-mouth study designs.

Main Methods:

  • Utilized the generalized estimating equation (GEE) approach for statistical analysis.
  • Developed closed-form sample size formulas for exchangeable and "nested exchangeable" correlation structures.
  • Employed large sample approximation for statistical inference under GEE.
  • Conducted simulation studies to evaluate the performance of the GEE sample size formulas.

Main Results:

  • Introduced novel closed-form sample size formulas for split-mouth designs.
  • Demonstrated the utility of GEE for assessing treatment effects while accounting for correlations.
  • Simulation studies confirmed the finite-sample performance of the proposed GEE sample size formulas.

Conclusions:

  • The proposed GEE approach and sample size formulas are valuable tools for designing efficient split-mouth dental trials.
  • Accurate sample size determination is critical for reliable treatment effect estimation in these designs.
  • The methods presented address a significant gap in the design phase of split-mouth clinical research.