How big does my sample need to be? A primer on the murky world of sample size estimation

Research output: Contribution to journalArticleResearchpeer-review

55 Citations (Scopus)

Abstract

Background: An explicit justification of sample size is now mandatory for most proposals submitted to funding bodies, ethics committees and, increasingly, for articles submitted for publication in journals. However, the process of sample size estimation is often confusing. Aim: Here, we present a primer of sample size estimation in an attempt to demystify the process. Method: First, we present a discussion of the parameters involved in power analysis and sample size estimation. These include the smallest worthwhile effect to be detected, the Types I and II error rates, and the variability in the outcome measure. Secondly, through a simplified, example 'dialogue', we illustrate the decision-making process involved in assigning appropriate parameter values to arrive at a ballpark figure for required sample size. We adopt a hypothetical, parallel-group, randomized trial design, though the general principles and concepts are transferable to other designs. The illustration is based on a traditional, power-analytic, null hypothesis-testing framework. In brief, we also address sample size estimation methods based on the required precision of the mean effect estimate. Conclusion: Rigorous sample size planning is important. Researchers should be honest and explicit regarding the decisions made for each of the parameters involved in sample size estimation.

Original languageEnglish
Pages (from-to)153-163
Number of pages11
JournalPhysical Therapy in Sport
Volume6
Issue number3
DOIs
Publication statusPublished - 1 Aug 2005

Fingerprint

Sample Size
Ethics Committees
Publications
Decision Making
Research Personnel
Outcome Assessment (Health Care)

Cite this

@article{8cce81591d214c10a63ace5fed9b065f,
title = "How big does my sample need to be? A primer on the murky world of sample size estimation",
abstract = "Background: An explicit justification of sample size is now mandatory for most proposals submitted to funding bodies, ethics committees and, increasingly, for articles submitted for publication in journals. However, the process of sample size estimation is often confusing. Aim: Here, we present a primer of sample size estimation in an attempt to demystify the process. Method: First, we present a discussion of the parameters involved in power analysis and sample size estimation. These include the smallest worthwhile effect to be detected, the Types I and II error rates, and the variability in the outcome measure. Secondly, through a simplified, example 'dialogue', we illustrate the decision-making process involved in assigning appropriate parameter values to arrive at a ballpark figure for required sample size. We adopt a hypothetical, parallel-group, randomized trial design, though the general principles and concepts are transferable to other designs. The illustration is based on a traditional, power-analytic, null hypothesis-testing framework. In brief, we also address sample size estimation methods based on the required precision of the mean effect estimate. Conclusion: Rigorous sample size planning is important. Researchers should be honest and explicit regarding the decisions made for each of the parameters involved in sample size estimation.",
author = "Batterham, {Alan M.} and Greg Atkinson",
year = "2005",
month = "8",
day = "1",
doi = "10.1016/j.ptsp.2005.05.004",
language = "English",
volume = "6",
pages = "153--163",
journal = "Physical Therapy in Sport",
issn = "1873-1600",
publisher = "Elsevier BV",
number = "3",

}

How big does my sample need to be? A primer on the murky world of sample size estimation. / Batterham, Alan M.; Atkinson, Greg.

In: Physical Therapy in Sport, Vol. 6, No. 3, 01.08.2005, p. 153-163.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - How big does my sample need to be? A primer on the murky world of sample size estimation

AU - Batterham, Alan M.

AU - Atkinson, Greg

PY - 2005/8/1

Y1 - 2005/8/1

N2 - Background: An explicit justification of sample size is now mandatory for most proposals submitted to funding bodies, ethics committees and, increasingly, for articles submitted for publication in journals. However, the process of sample size estimation is often confusing. Aim: Here, we present a primer of sample size estimation in an attempt to demystify the process. Method: First, we present a discussion of the parameters involved in power analysis and sample size estimation. These include the smallest worthwhile effect to be detected, the Types I and II error rates, and the variability in the outcome measure. Secondly, through a simplified, example 'dialogue', we illustrate the decision-making process involved in assigning appropriate parameter values to arrive at a ballpark figure for required sample size. We adopt a hypothetical, parallel-group, randomized trial design, though the general principles and concepts are transferable to other designs. The illustration is based on a traditional, power-analytic, null hypothesis-testing framework. In brief, we also address sample size estimation methods based on the required precision of the mean effect estimate. Conclusion: Rigorous sample size planning is important. Researchers should be honest and explicit regarding the decisions made for each of the parameters involved in sample size estimation.

AB - Background: An explicit justification of sample size is now mandatory for most proposals submitted to funding bodies, ethics committees and, increasingly, for articles submitted for publication in journals. However, the process of sample size estimation is often confusing. Aim: Here, we present a primer of sample size estimation in an attempt to demystify the process. Method: First, we present a discussion of the parameters involved in power analysis and sample size estimation. These include the smallest worthwhile effect to be detected, the Types I and II error rates, and the variability in the outcome measure. Secondly, through a simplified, example 'dialogue', we illustrate the decision-making process involved in assigning appropriate parameter values to arrive at a ballpark figure for required sample size. We adopt a hypothetical, parallel-group, randomized trial design, though the general principles and concepts are transferable to other designs. The illustration is based on a traditional, power-analytic, null hypothesis-testing framework. In brief, we also address sample size estimation methods based on the required precision of the mean effect estimate. Conclusion: Rigorous sample size planning is important. Researchers should be honest and explicit regarding the decisions made for each of the parameters involved in sample size estimation.

UR - http://www.scopus.com/inward/record.url?scp=23844453228&partnerID=8YFLogxK

U2 - 10.1016/j.ptsp.2005.05.004

DO - 10.1016/j.ptsp.2005.05.004

M3 - Article

VL - 6

SP - 153

EP - 163

JO - Physical Therapy in Sport

JF - Physical Therapy in Sport

SN - 1873-1600

IS - 3

ER -