Korean J Anesthesiol.  2020 Apr;73(2):114-120. 10.4097/kja.19497.

Tips for troublesome sample-size calculation

Affiliations
  • 1Department of Anesthesiology and Pain Medicine, Dongguk University Ilsan Hospital, Goyang, Korea
  • 2Department of Anesthesiology and Pain Medicine, Chung-Ang University College of Medicine, Seoul, Korea
  • 3Department of Anesthesiology and Pain Medicine, Daegu Catholic University School of Medicine, Daegu, Korea
  • 4Department of Anesthesiology and Pain Medicine, Yangsan Hospital, Pusan National University School of Medicine, Busan, Korea
  • 5Department of Anesthesiology and Pain Medicine, Inje University Seoul Paik Hospital, Inje University College of Medicine, Seoul, Korea
  • 6Department of Anesthesiology and Pain Medicine, Guro Hospital, Korea University School of Medicine, Seoul, Korea
  • 7Department of Anesthesiology and Pain Medicine, Sanggye Paik Hospital, Inje University College of Medicine, Seoul, Korea
  • 8Department of Anesthesiology and Pain Medicine, Inje University Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea

Abstract

Properly set sample size is one of the important factors for scientific and persuasive research. The sample size that can guarantee both clinically significant differences and adequate power in the phenomena of interest to the investigator, without causing excessive financial or medical considerations, will always be the object of concern. In this paper, we reviewed the essential factors for sample size calculation. We described the primary endpoints that are the main concern of the study and the basis for calculating sample size, the statistics used to analyze the primary endpoints, type I error and power, the effect size and the rationale. It also included a method of calculating the adjusted sample size considering the dropout rate inevitably occurring during the research. Finally, examples regarding sample size calculation that are appropriately and incorrectly described in the published papers are presented with explanations.

Keyword

Biostatistics; Effect size; Power; P value; Sample size; Independent t-test
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