Abstract

One of frequently asked question by health researchers is how many individuals will I need to study. Sample size determination is one of the central canons of health research. A study is always better when planned scientifically and determining the sample size for a study is a prime component as it will help to determine optimum number of subjects so that statistically significant results can be detected. If the sample size is larger than what is needed, the study will become cumbersome and ethically exorbitant. On the converse, using too few subjects’ will eventually result in wasted time, effort and money etc. Literature is full of examples in which sample size is incorrectly determined for health studies thus resulting in bias conclusions. To ensure the reliability of the results, the significance level and power of study must be fixed before the sample size determination. Sample size determination is very important and always a difficult process to handle. It requires the collaboration of a specialist who has good scientific knowledge in the art and practice of medical statistics. There are numerous situations in which sample size is determined that varies from study to study. This article will focus on the sample size determination for hypothesis testing and confidence interval situations commonly used in health studies.

Key words: Hypothesis testing, confidence interval, significance level, power of study, effect size, sample size