Beyond Power Calculations
Columbia University · The University of Melbourne · +1 more institution
Abstract
Statistical power analysis provides the conventional approach to assess error rates when designing a research study. However, power analysis is flawed in that a narrow emphasis on statistical significance is placed as the primary focus of study design. In noisy, small-sample settings, statistically significant results can often be misleading. To help researchers address this problem in the context of their own studies, we recommend design calculations in which (a) the probability of an estimate being in the wrong direction (Type S [sign] error) and (b) the factor by which the magnitude of an effect might be overestimated (Type M [magnitude] error or exaggeration ratio) are estimated. We illustrate with…
Citation impact
- FWCI
- 372.99
- Percentile
- 100%
- References
- 33
Authors
2Topics & keywords
- Psychology
- Power (physics)
- Computer science
- Physics
- Quantum mechanics