Hi Abhishek,

After doing some research, I found that conducting a hypothesis test of effects/relationships (power analysis) would be ideal in determining sample size. Studies that attempt to determine an effect such as differences between two treatments or the presence/absence of a certain risk factor need accurate sample size calculations to ensure that the analysis is statistically significant. If the sample size is insufficient, it will be hard to prove that any differences observed is meaningful because it could just be due to sampling variation. Some factors that can affect sample size calculations are:

1. Objective of research – is the research based on an estimation, hypothesis or equivalence testing problem?
2. Are there any covariates or factors for which to control?
3. Research design – is it a simple randomized controlled trial (RCT), cluster randomized trial, equivalence trial, etc.?
4. Is there a desired statistical significance level?
5. Test statistic analysis – will it be a one- or two-tailed test?