Abstract
1. The Power of Statistical Tests. 2. A Simple and General Model for Power Analysis. 3. Power Analyses for Minimum-Effect Tests. 4. Using Power Analyses. 5. Correlation and Regression. 6. t-Tests and the Analysis of Variance. 7. Multi-Factor ANOVA Designs. 8. Split-Plot Factorial and Multivariate Analyses. 9. The Implications of Power Analyses. Appendices.
Keywords
Simple (philosophy)Statistical hypothesis testingEconometricsPower (physics)Computer scienceMathematicsStatisticsEpistemologyPhilosophyPhysics
Affiliated Institutions
Related Publications
Experimental Design: Procedures for the Behavioral Sciences
Chapter 1. Research Strategies and the Control of Nuisance Variables Chapter 2. Experimental Designs: an Overview Chapter 3. Fundamental Assumptions in Analysis of Variance Chap...
Quality by Experimental Design.
THE PHILOSOPHY OF EXPERIMENTATION Why Design Experiments? Organizing the Experiment The Neglected Response Variable STATISTICAL EXPERIMENTAL DESIGN The Factorial 2-Level Design ...
Experimental Design and Data Analysis for Biologists
An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data. The text begins with a revision of e...
Mixed‐effects models in psychophysiology
The current methodological policy in Psychophysiology stipulates that repeated‐measures designs be analyzed using either multivariate analysis of variance (ANOVA) or repeated‐me...
The Design and Analysis of Clinical Experiments
Reliability of Measurement. Simple Linear Regression Analysis. The Parallel Groups Design. Special Cases of the Parallel Groups Study. Blocking to Control for Prognostic Variabl...
Publication Info
- Year
- 1998
- Type
- article
- Volume
- 36
- Issue
- 02
- Pages
- 36-1020
- Citations
- 807
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
807
OpenAlex
24
Influential
0
CrossRef
Cite This
Kevin R. Murphy,
Brett Myors
(1998).
Statistical power analysis: a simple and general model for traditional and modern hypothesis tests.
Choice Reviews Online
, 36
(02)
, 36-1020.
https://doi.org/10.5860/choice.36-1020
Identifiers
- DOI
- 10.5860/choice.36-1020