# Overview of Meta-Analysis, Part 3 (of 7): Effect-Size Features

**Posted:**March 19, 2012 |

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

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

**Tags:**coding, effect size, inclusion/exclusion, individual participant data, meta-analysis, missing data, moderator, primary-study quality | Leave a comment

In Part 2 of this seven-part overview, I described obtaining the sample size(s) or conditional variance (CV) associated with an effect-size (ES) estimate to quantify this estimate’s sampling error or (im)precision. Here in Part 3 I’ll address **coding features linked to ESs**. Whereas this overview’s first three parts focus on collecting data used in a research synthesis, its subsequent four parts will address meta-analyzing these data and presenting results. (Part 1 lists the topics for all seven parts.)

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# 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.)

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# 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

# Resources for Learning and Doing Research Synthesis, Part 2

**Posted:**February 15, 2012 |

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

**Filed under:**Uncategorized |

**Tags:**bibliography, book, consulting, meta-analysis, methodology, research synthesis, software | Leave a comment

In Part 1 of this two-part post I mentioned a few major organizations that provide resources for research synthesis and described numerous training opportunities. Here, in Part 2, I’ll discuss the plethora of **publications** on relevant methodology, options for **software**, and potential benefits of involving **collaborators** (e.g., colleagues, consultants).

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# Content of and Plan for ‘Meta-Analysis Sandwich’

**Posted:**February 1, 2012 |

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

**Filed under:**Uncategorized |

**Tags:**consulting, effect size, math notation, meta-analysis, methodology, research synthesis | Leave a comment

Welcome to my first ever blog. In this inaugural post I’ll comment on topics I anticipate covering, a few challenges of blogging about statistics, and my primary reasons for undertaking this endeavor.

## Anticipated Topics

This blog is about meta-analysis methodology and related topics. Let’s break that down:

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