# Overview of Meta-Analysis, Part 5c (of 7): Primary Meta-Analyses (cont.)

**Posted:**May 13, 2012 |

**Author:**A. R. Hafdahl |

**Filed under:**Overview of Meta-Analysis |

**Tags:**Bayesian analysis, between-studies variance component, dependence, fixed effect, heterogeneity, interval estimation, meta-analysis, meta-regression, model comparison, moderator, multivariate effect size, random effect, significance testing, standardized mean difference | 1 Comment

This is the last of three posts in Part 5 of my overview of meta-analysis. In Part 5a I described six conventional meta-analytic models for effect-size (ES) estimates, and in Part 5b I described estimation and inference for two of those models without covariates. In this post I’ll extend the methods of Part 5b to two **models with covariates** and comment on **extensions and other variants** of these models and procedures, to hint at the wide variety of situations that arise in meta-analysis. In Parts 6 and 7 of the overview, I’ll address follow-up procedures and ways to report results, respectively.

Read the rest of this entry »

# Overview of Meta-Analysis, Part 2 (of 7): Sampling Error

**Posted:**March 11, 2012 |

**Author:**A. R. Hafdahl |

**Filed under:**Overview of Meta-Analysis |

**Tags:**binary outcome, conditional variance, correlation, dependence, effect size, heterogeneity, meta-analysis, missing data, multivariate effect size, primary-study design, sample size, standardized mean difference | Leave a comment

In Part 1 of this seven-part overview of meta-analysis, I introduced Conn, Hafdahl, Cooper, Brown, and Lusk’s (2009) quantitative review of workplace exercise interventions and discussed extracting effect-size (ES) estimates. Building on that material, in this second part I’ll address **obtaining info about an ES’s sampling error**, which plays a critical role in most modern meta-analytic methods. (Part 1 of this overview lists topics in the subsequent five posts.)

Read the rest of this entry »

# Overview of Meta-Analysis, Part 1 (of 7): Effect Sizes

**Posted:**February 27, 2012 |

**Author:**A. R. Hafdahl |

**Filed under:**Overview of Meta-Analysis |

**Tags:**binary outcome, correlation, dependence, effect size, meta-analysis, missing data, multivariate effect size, standardized mean difference, substantive application | Leave a comment

This post is the first in a seven-part overview of common meta-analytic tasks. In this first part I’ll introduce a real-world **substantive application of meta-analysis** and address **estimating effect sizes** (ESs). Subsequent parts will focus on the following topics:

- Part 2: obtaining information about ES sampling error
- Part 3: collecting features of ESs
- Part 4: exploring data
- Part 5: fitting meta-analytic models to ESs (subparts 5a, 5b, and 5c)
- Part 6: checking for potential problems
- Part 7: expressing results informatively