An info-gap approach to power and sample size calculations

Abstract

Power and sample size calculations are an important but underutilised component of many ecological investigations. A key problem with these calculations is the need to estimate or guess the effect size and error variance (the design parameters) prior to the actual data collection. Furthermore, calculations associated with statistical power and sample size are invariably predicated on normal distribution theory. While the central limit theorem ensures the applicability of normal-based inference for reasonably large sample sizes, the impact of violations of this assumed distributional form in the context of power and sample size determinations is rarely considered. This paper uses information-..