Power calculations are a statistical tool to help compute sample size, power, or minimum detectable effect size (MDES).
Sampling & Power Calculations
Multi-stage (cluster) sampling is a common sampling design in which the unit of randomization differs from the unit of observation. In other words, the unit at which the treatment is assigned (i.e.
Optimal Design is free software designed by University of Michigan. It provides a useful platform on which researchers can visualize the relationship between different elements of the sample size formula when conducting power calculations during the research design stage. This page provides a general overview of and additional resources for Optimal Design.
The minimum detectable effect is the effect size set by the researcher that an impact evaluation is designed to estimate for a given level of significance. The minimum detectable effect is a critical input for power calculations and is closely related to power, sample size, and survey and project budgets.
Sampling is the process of randomly selecting units from a population of interest to represent the characteristics of that population. Sampling in a statistically valid, representative manner is a crucial step in conducting high quality randomized control trials.
Power calculations indicate the minimum sample size needed to provide precise estimates of the program impact; they can also be used to compute power and minimum detectable effect size.
Stratification is an ex-ante statistical technique that ensures that sub-groups of the population are represented in the final sample and treatment groups. In addition to ensuring representativeness, stratification allows researchers to disaggregate by subgroup during analysis. Stratification takes place when defining the sample and treatment assignments during research design.