The Essential Guide to Effect Sizes: Statistical Power, Meta-Analysis, and the Interpretation of Research ResultsCambridge University Press, 2010 - 173 pages This succinct and jargon-free introduction to effect sizes gives students and researchers the tools they need to interpret the practical significance of their results. Using a class-tested approach that includes numerous examples and step-by-step exercises, it introduces and explains three of the most important issues relating to the practical significance of research results: the reporting and interpretation of effect sizes (Part I), the analysis of statistical power (Part II), and the meta-analytic pooling of effect size estimates drawn from different studies (Part III). The book concludes with a handy list of recommendations for those actively engaged in or currently preparing research projects. |
Table des matières
Part II The analysis of statistical power | 45 |
Part III Metaanalysis | 87 |
thirty recommendations for researchers | 134 |
Appendix 1 Minimum sample sizes | 138 |
Appendix 2 Alternative methods for metaanalysis | 141 |
| 170 | |
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Expressions et termes fréquents
alpha analysis approach assess associated authors average better bias calculate chance Chapter coding coefficient Cohen’s combined conclusions confidence intervals considered correlation critical detect difference distribution draw editors effect size estimates equation et al evidence example fail-safe false findings first follows four given Hedges Hunter important increase individual interest interpret Journal lead least less levels mean effect measurement meta-analysis methods multiple nonsignificant notes null hypothesis observed obtained odds outcome points population effect positive possibility power analysis practical precision probability procedures Psychology publication published question random-effects ratio reasons refer relative relevant replication reported reviewer risk sample size Schmidt score shows social square standard deviation statistical power statistically significant studies survey Table treatment true Type II error variables variance variation weighted