Environmental impact assessment and monitoring
The role of statistical power analysis
Bibliographic Data
| ID | 21153669 |
|---|---|
| Authors | Bonnie L Antcliffe (Fisheries and Oceans Canada, corresponding author) |
| Year | 1999 |
| Volume | 17 |
| Issue | 1 |
| Pages | 33-43 |
| Publication date | 1999-03-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Impact Assessment and Project Appraisal (JOURNAL) |
| Journal identifiers | ISSN: 1461-5517 • E-ISSN: 1471-5465 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.3152/147154699781767954 |
| OpenAlex | W2044600874 |
| Language | EN |
| References cited | 37 |
Statistical power is an important part of traditional hypothesis testing, yet, until recently, it has been given relatively little attention in this field. It is recommended that practitioners use power analysis to determine the sample size required by quantitative impact assessments, explore the effect of different estimates of sample variance and important effect size on the sample size required, and not take action as if there is ‘no effect’ when a test fails to reject the zero hypothesis, unless the power of the test is high. Managers should encourage research into what constitutes an important effect, take steps to ensure study designs for impact assessments are evaluated a priori, and include power analysis in standard protocols for designing quantitative impact assessments
A priori and a posteriori · Business · Computer security · Econometrics · Impact assessment · Power analysis · Reliability engineering · Sample size determination · Statistical analysis · Statistical hypothesis testing · Statistical power · Statistics · Computer Science · Engineering · Environmental and Social Impact Assessments · Mathematics · Accounting
| Highly cited | No |
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