When calculation of minimum sample size is not justified

We read with interest the paper of Estévez, et al, recently published in Hepatitis Monthly (1). That article was a Letter to the Editor on the study conducted by Nikui Nejad et al (2). One of the comments made by Estévez et al was on the adequacy of the size of the studied sample. They believed that the sample size was not adequate based on the provided data and the type of study (1). In the reply from the authors, a familiar mathematical equation which is frequently used for prevalence study designs was presented to explain the way the sample size was calculated in Nikui Nejad’s study (1). In spite of doubts in the statistical analyses used in their study, we should emphasize that the study of Nikui Nejad, et al, was clearly a clinical trial involving comparison between two vaccines. In that study, the sample size did not depend on the prevalence of vaccine response rate in the population—instead, it did depend on the difference between the response rates from the two vaccines. The authors also used an incorrect assumption for the calculation of minimum sample size according the “prevalence approach” and assumed a large d with a small P! We know that in clinical trial, if the sample size is too small, a well-conducted study may fail to answer its research hypothesis or to detect important effects and associations. Therefore, correct assumptions for the calculation of minimum sample size are of paramount importance in conducting research. Approaches for estimatc 2011 Kowsar M.P.Co. All rights reserved. Please cite this paper as: Pourhoseingholi MA, Baghestani AR. When calculation of minimum sample size is not justified. Hepat Mon.2011;11(3):208-209.