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Sample Size Estimation and Power Analysis for Research Studies Using R
Abstract
Sample size estimation is very crucial in any research design. A research design with less sample size may give a biased result or inconclusive result. A research design with very large sample size than required results is waste of resources, time and energy. So, it is very essential to determine ‘ideal’ or ‘optimum’ sample size. This article gives formulae and R code for determining sample size for single mean, two means, single proportion, two proportions, proportion in survey type data, case control studies, cohort studies, correlation coefficient and difference between correlation coefficients.
Keywords
Sample size, level of significance, one and two tailed tests, statistical power, Superiority study, Equivalence study, Non inferiority study, R code
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This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. This article can be used for non-commercial purposes. Mentioning of the publication source is mandatory while referring this article in any future works.
