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Related Concept Videos

Sample Size Calculation01:19

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Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
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The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
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When the population standard deviation is unknown and the sample size is large, the sample standard deviation s is commonly used as a point estimate of σ. However, it can sometimes under or overestimate the population standard deviation. To overcome this drawback, confidence intervals are determined to estimate population parameters and eliminate any calculation bias accurately. However, this only applies to random samples from normally distributed populations. Knowing the sample mean and...
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Sample Size Calculation for an Individual Stepped-Wedge Randomized Trial.

Aude Allemang-Trivalle1,2, Annabel Maruani1,2,3, Bruno Giraudeau1,2

  • 1Université de Tours, Université de Nantes, INSERM, SPHERE U1246, Tours, France.

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Summary

Researchers developed a sample size formula for individual stepped-wedge randomized trials (ISW-RTs). This new formula provides reliable power estimates for ISW-RTs, aiding in efficient trial design.

Keywords:
clinical trialsindividual autocorrelationindividual stepped‐wedge randomized trialsample size calculationstepped‐wedge cluster randomized trial

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Epidemiology

Background:

  • Individual stepped-wedge randomized trials (ISW-RTs) are increasingly used but lack validated sample size calculation methods.
  • Existing methods for stepped-wedge cluster randomized trials (SW-CRTs) are not directly applicable to individual randomization.

Purpose of the Study:

  • To adapt the sample size formula from SW-CRTs for use in ISW-RTs.
  • To validate the adapted formula using Monte Carlo simulations.

Main Methods:

  • Adapted the SW-CRT sample size formula for individual randomization.
  • Conducted Monte Carlo simulations to assess the empirical power of the proposed formula.
  • Evaluated formula performance across various scenarios, including different numbers of periods and autocorrelation coefficients.

Main Results:

  • The proposed sample size calculation formula demonstrated satisfactory empirical power in most tested scenarios.
  • Performance was less reliable under boundary conditions, such as minimal periods or extreme autocorrelation.

Conclusions:

  • The adapted formula offers a valuable tool for sample size estimation in ISW-RTs.
  • Researchers should exercise caution when applying the formula in scenarios with extreme operating characteristics.