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Sample-size calculation for a log-transformed outcome measure.

R Wolfe1, J B Carlin

  • 1Clinical Epidemiology and Biostatistics Unit, Royal Children's Hospital Research Institute, Parkville, Australia.

Controlled Clinical Trials
|December 10, 1999
PubMed
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This study presents a method for calculating sample sizes in clinical trials with log-transformed outcomes. The approach uses relative treatment effects and variability on the original measurement scale for both independent and matched-pair designs.

Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Statistical Analysis

Background:

  • Clinical trial analyses often require log-transformation of outcome measures.
  • Accurate sample-size calculation is crucial for trial efficiency and validity.

Purpose of the Study:

  • To develop and demonstrate sample-size calculation methods for log-transformed outcomes in clinical trials.
  • To provide a framework applicable to both independent-group and matched-pairs designs.

Main Methods:

  • Formulating sample-size calculations based on relative treatment effects and relative variability on the original measurement scale.
  • Defining relative treatment effects as ratios of geometric means (independent groups) or geometric mean of within-pair ratios (matched pairs).
  • Utilizing the coefficient of variation for independent groups and an upper bound on within-pair ratios for matched pairs to define relative variability.

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Main Results:

  • Demonstrated a unified approach for sample-size calculation applicable to log-transformed data in different trial designs.
  • Showcased the practical application of the proposed methods using a motivating clinical study.

Conclusions:

  • The proposed sample-size calculation method simplifies trial planning for log-transformed outcomes.
  • The framework offers flexibility by allowing specification of effects and variability on the original scale.