## Statistical Methods for Meta-AnalysisThe main purpose of this book is to address the statistical issues for integrating independent studies. There exist a number of papers and books that discuss the mechanics of collecting, coding, and preparing data for a meta-analysis , and we do not deal with these. Because this book concerns methodology, the content necessarily is statistical, and at times mathematical. In order to make the material accessible to a wider audience, we have not provided proofs in the text. Where proofs are given, they are placed as commentary at the end of a chapter. These can be omitted at the discretion of the reader. Throughout the book we describe computational procedures whenever required. Many computations can be completed on a hand calculator, whereas some require the use of a standard statistical package such as SAS, SPSS, or BMD. Readers with experience using a statistical package or who conduct analyses such as multiple regression or analysis of variance should be able to carry out the analyses described with the aid of a statistical package. |

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### Conteúdo

1 | |

15 | |

Chapter 3 Tests of Statistical Significance of Combined Results | 27 |

Chapter 4 VoteCounting Methods | 47 |

Parametric and Nonparametric Methods | 75 |

Chapter 6 Parametric Estimation of Effect Size From a Series of Experiments | 107 |

Categorical Models | 147 |

General Linear Models | 167 |

Chapter 11 Combining Estimates of Correlation Coefficients | 223 |

Chapter 12 Diagnostic Procedures for Research Synthesis Models | 247 |

Chapter 13 Clustering Estimates of Effect Magnitude | 265 |

Chapter 14 Estimation of Effect Size When Not All Study Outcomes Are Observed | 285 |

Chapter 15 MetaAnalysis in the Physical and Biological Sciences | 311 |

Appendix | 327 |

347 | |

Author Index | 361 |

Chapter 9 Random Effects Models for Effect Sizes | 189 |

Chapter 10 Multivariate Models for Effect Sizes | 205 |

### Outras edições - Visualizar todos

Statistical Methods for Meta-Analysis Larry V. Hedges,Larry Vernon Hedges,Ingram Olkin Não há visualização disponível - 1985 |

### Termos e frases comuns

95-percent confidence interval analysis of variance bias calculated Chapter chi-square distribution clustering procedure combined test procedures compute confidence interval control group correlation coefficient covariance matrix degrees of freedom denote disattenuated Education on Student effect magnitude effect size estimates effects of open estimates of effect example exceeds experimental and control experiments F-test function given in Section given in Table homogeneity of effect homogeneity statistic independent ith study large sample approximation linear model maximum likelihood estimator meta-analysis model specification null hypothesis number of studies observations obtained open education open versus traditional outcome outliers p-values parameter percent population correlation posttest predictors proportion random effects models research synthesis sample correlation sample sizes sampling variance scores sex differences significance level significance of combined significant results small sample standard normal distribution standardized mean difference statistic Q statistically significant test statistic transformed treatment effect unbiased estimator variables variance components variates vector yield zero