What is meant by sample size calculation?
Abstract
Simply it means the number of participants that should be recruited for your study (both the experimental group and the control group). It is a essential step in any randomized controlled trial to ensure that you will withdraw the best available firm conclusions. The aim is to minimize the probability of failing to detect a real effect, i.e. type II error (false negative). Type II error is indicated in reverse by the power of a study, thus power is the probability of detecting a true effect. You may select a power level of 80% for your study along with the two sided significance level which you intend to use in subsequent analysis. The latter considers type I error, the probability of incorrectly rejecting the null hypothesis (false positive).
Minimum sample sizes are estimated for the comparison of means using Student t tests, the comparison of proportions and for population surveys. You are required to enter a value for power (the probability of detecting a true effect) and alpha (the probability of detecting a false effect). How to do it is simple: you have to do this at the initial phase of the study design (meaning before you start the trial) and have to read the medical literature on the specific topic you are studying to know the proportions of the events in control group and estimate the difference in the experimental group.
Minimum sample sizes are estimated for the comparison of means using Student t tests, the comparison of proportions and for population surveys. You are required to enter a value for power (the probability of detecting a true effect) and alpha (the probability of detecting a false effect). How to do it is simple: you have to do this at the initial phase of the study design (meaning before you start the trial) and have to read the medical literature on the specific topic you are studying to know the proportions of the events in control group and estimate the difference in the experimental group.