Sample Size in Clinical Researches: Power of the Test and Effect Size

Authors : Adnan ÜNALAN

Pages : 221-227

Doi:10.19127/bshealthscience.866556

View : 57 | Download : 12

Publication Date : 2021-09-01

Article Type : Research Paper

Abstract :The approval of local ethics committees is required for clinical researches. In order to obtain approval, how the sample size is determined, whether power analysis is done or not and under what assumptions these analyses are made, are important questions/problems. In hypothesis tests, it is possible two types of errors insert ignore into journalissuearticles values(type 1 error denoted by α and type 2 error denoted by β);, of which α is the probability of rejecting the null hypothesis that is actually true and is the probability of accepting the actually false null hypothesis. These errors also determine the reliability of the test insert ignore into journalissuearticles values(1-α); and the power of test insert ignore into journalissuearticles values(1-β);. While α is directly determined by the researchers and generally as taken 0.05 insert ignore into journalissuearticles values(in some cases 0.01);, β cannot be determined directly. Because β, hence the power of test insert ignore into journalissuearticles values(1-β); depends on the α insert ignore into journalissuearticles values(negatively correlated with β); the variation in the population insert ignore into journalissuearticles values(positively correlated with β); and sample size insert ignore into journalissuearticles values(n; negatively correlated with β);. In clinical researches, it is required that β does not exceed 0.10 insert ignore into journalissuearticles values(in some cases 0.05); so the power of test should be at least 0.90 and above. In this study, the sample sizes required for some statistical tests insert ignore into journalissuearticles values(independent sample t-test, one-way ANOVA and Chi-square); which are widely used in clinical research, were calculated with the G*Power program and some evaluations were made. As a result, as expected in the statistical tests, it was observed that decreasing both α and effect size and increasing the power of the test significantly increased the required sample size. However, it was also observed that increasing effect on the sample size of increasing the power of test decreased insert ignore into journalissuearticles values(5-11%); in the smaller values of α in the independent sample t-test, decreased insert ignore into journalissuearticles values(nearly 5%); when increasing the number of compared groups in one-way ANOVA and decreased insert ignore into journalissuearticles values(10-15%); when increasing degree of freedom of Chi-square test.
Keywords : Clinical researches, Test of hypothesis, Sample size, Power analysis, Effect size

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