Statistical power and sample size calculations: A primer for pediatric surgeons

被引:19
作者
Staffa, Steven J. [1 ]
Zurakowski, David [1 ]
机构
[1] Harvard Med Sch, Boston Childrens Hosp, Dept Surg, Boston, MA 02115 USA
关键词
Statistical power; Sample size; Effect size; alpha level; Study design; Biostatistics; MULTIPLE COMPARISONS; TRIAL;
D O I
10.1016/j.jpedsurg.2019.05.007
中图分类号
R72 [儿科学];
学科分类号
100202 ;
摘要
Background/Purpose: Determining the appropriate sample size is an integral component of any well-designed research study, grant application, or scientific manuscript. Surgeons intuitively understand the concept of statistical power, but have limited knowledge in how to go about performing the calculations correctly. Our goal is to provide a strategy for pediatric surgeons to use when planning a study to determine the sample sizes required for detecting a clinically meaningful effect, which is important for interpreting and validating their results. Methods: We present a general 5 -step approach for performing a sample size justification and statistical power analysis, and illustrate this approach using several surgical research examples. The 5 steps are: 1) Define the primary outcome of interest, 2) Define the magnitude of the effect or effect size and power desired, 3) Determine the appropriate statistics and statistical test that will be considered, 4) Perform the calculations to estimate the required sample size using software or a reference table, 5) Write the formal power and sample size statement for the manuscript, grant application, or project proposal. Conclusions: Understanding sample size considerations and statistical power in the surgical research community will improve the quality of published articles. This primer can be used by pediatric surgeons in the process of determining the appropriate sample sizes for detecting a clinically meaningful effect with sufficient statistical power. Virtually all research studies in pediatric surgery should include a justification of sample size based on a power calculation as this leads to more meaningful inferences from the data and analysis. Type of study: Review article. (C) 2019 Elsevier nc, All rights reserved.
引用
收藏
页码:1173 / 1179
页数:7
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