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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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Collecting samples or responses from an entire population takes significant time and effort, so a researcher collects responses from only a sample of that population. Suppose a study needs to collect information about a specific mobile application. After sample collection, the researcher analyzes the data and discovers that most individuals in the sample use that specific mobile application. The sample proportion measures the number of individuals in a sample who either use or don't use the...
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Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
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The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
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A sample size calculator for SMART pilot studies.

Hwanwoo Kim1, Edward Ionides1, Daniel Almirall2

  • 1Department of Statistics, University of Michigan, Ann Arbor, MI 48104.

SIAM Undergraduate Research Online
|October 22, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for calculating the minimal sample size for sequential multiple assignment randomized trials (SMART) pilot studies. This is crucial for the feasibility of adaptive interventions in clinical research.

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Area of Science:

  • Clinical Research Methodology
  • Biostatistics
  • Behavioral Science

Background:

  • Adaptive interventions tailor treatments sequentially based on individual responses.
  • Sequential multiple assignment randomized trials (SMART) are increasingly used to inform adaptive intervention development.
  • SMART and adaptive interventions are novel, necessitating pilot studies for feasibility.

Purpose of the Study:

  • To introduce a novel methodology for determining the minimal sample size for SMART pilot studies.
  • To provide researchers with tools for planning feasible and acceptable SMART pilot investigations.
  • To facilitate the efficient design of adaptive intervention research.

Main Methods:

  • Development of a new statistical methodology for sample size calculation.
  • Focus on minimal sample size requirements specific to SMART pilot studies.
  • Methodology designed to address feasibility and acceptability considerations.

Main Results:

  • A new methodology for calculating minimal sample size for SMART pilots is presented.
  • The methodology aims to ensure adequate planning for early-stage adaptive intervention research.
  • Provides a framework for researchers new to SMART study designs.

Conclusions:

  • Accurate sample size calculation is essential for the success of SMART pilot studies.
  • The proposed methodology supports the practical implementation of adaptive intervention research.
  • This work aids researchers in designing robust and feasible SMART pilot trials.