Journal Information
Journal ID (publisher-id): BM
Journal ID (nlm-ta): Biochem Med (Zagreb)
Title: Biochemia Medica
Abbreviated Title: Biochem. Med. (Zagreb)
ISSN (print): 1330-0962
ISSN (electronic): 1846-7482
Publisher: Croatian Society of Medical Biochemistry and Laboratory Medicine
Article Information
Copyright statement: ©Croatian Society of Medical Biochemistry and Laboratory Medicine.
Copyright: 2020, Croatian Society of Medical Biochemistry
License (open-access):
This is an Open Access article distributed under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Date received: 30 June 2020
Date accepted: 12 November 2020
Publication date (electronic): 15 December 2020
Publication date (print): 15 February 2021
Volume: 31
Issue: 1
Electronic Location Identifier: 010502
Publisher ID: bm-31-1-010502
DOI: 10.11613/BM.2021.010502
Sample size, power and effect size revisited: simplified and practical approaches in pre-clinical, clinical and laboratory studies
Ceyhan Ceran Serdar[1]
Murat Cihan[2]
Doğan Yücel[3]
[1] Medical Biology and Genetics, Faculty of Medicine, Ankara Medipol University, Ankara, Turkey
[2] Ordu University Training and Research Hospital, Ordu, Turkey
[3] Department of Medical Biochemistry, Lokman Hekim University School of Medicine, Ankara, Turkey
[4] Department of Medical Biochemistry, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
Author notes:
[*] Corresponding author: muhittin.serdar@acibadem.edu.tr
Calculating the sample size in scientific studies is one of the critical issues as regards the scientific contribution of the study. The sample size critically affects the hypothesis and the study design, and there is no straightforward way of calculating the effective sample size for reaching an accurate conclusion. Use of a statistically incorrect sample size may lead to inadequate results in both clinical and laboratory studies as well as resulting in time loss, cost, and ethical problems. This review holds two main aims. The first aim is to explain the importance of sample size and its relationship to effect size (ES) and statistical significance. The second aim is to assist researchers planning to perform sample size estimations by suggesting and elucidating available alternative software, guidelines and references that will serve different scientific purposes.
Keywords: biostatistics; effect size; power analysis; sample size
