V. Sample Size

Abstract

In clinical research it is impossible and inefficient to study all patients with a specific pathology; therefore, it is necessary to focus on a sample. Estimating the size of a sample warrants the stability of the results and allows for feasibility of the study to be foreseen, depending on cost and patient availability. The basic structure for estimating the sample size is based on the premise that tries to demonstrate —among other things— that the difference between two or more maneuvers in the subsequent state is real. For this, it is necessary to know the value of the expected difference (δ) and the dispersion measure of the data that gave rise to it (standard deviation), which usually are obtained from previous studies. Afterwards, other components are considered: α, which is percentage of type I error accepted in the claim that the difference between means is real, generally of 5 %; and β, which is the percentage of type II error accepted in the claim that the non-difference between means is real, generally from 15 to 20 %. These values are substituted in the formula or in some sample size estimation electronic program. Although summary and dispersion measures may vary according to the outcome measure and, consequently, the formula, the principle is the same.