Abstract
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.
Highlights
Statistical analysis is a crucial part of a research
Scientists have understood the importance of statistical analysis for researchers, a significant number of researchers admit that they lack adequate knowledge about statistical concepts and principles [1]
In a study by West and Ficalora, more than two-thirds of the clinicians emphasized that “the level of biostatistics education that is provided to the medical students is not sufficient” [2]
Summary
Statistical analysis is a crucial part of a research. A scientific study must include statistical tools in the study, beginning from the planning stage. In addition to the statistical significance (P value interpretation), different evaluation criteria are important for the assessment of the effect size These include precision, accuracy, coefficient of variation (CV), standard deviation, total allowable error, bias, biological variation, and standard deviation index, etc. For method comparison studies to be conducted using patient samples; sample size estimation, and power analysis methodologies, in addition to the required number of replicates are defined in CLSI document EP31-A-IR. Lu et al used maximum allowed differences for calculating sample sizes that would be required in Bland Altman comparison studies This type of sample size estimation, which is critically important in laboratory medicine, can be performed using Medcalc software [70]. Three critical aspects should be determined for sample size determination in survey studies:
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
