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Journal ArticleDOI

Meta-Analysis: Literature Synthesis or Effect-Size Surface Estimation?

Donald B. Rubin
- 21 Dec 1992 - 
- Vol. 17, Iss: 4, pp 363-374
TLDR
In contrast to these average effect sizes of literature synthesis, the proper estimand is an effect-size surface, which is a function only of scientifically relevant factors, and which can only be estimated by extrapolating a response surface of observed effect sizes to a region of ideal studies.
Abstract
A traditional meta-analysis can be thought of as a literature synthesis, in which a collection of observed studies is analyzed to obtain summary judgments about overall significance and size of effects. Many aspects of the current set of statistical tools for meta-analysis are highly useful—for example, the development of clear and concise effect-size indicators with associated standard errors. I am less happy, however, with more esoteric statistical techniques and their implied objects of estimation (i.e., their estimands) which are tied to the conceptualization of average effect sizes, weighted or otherwise, in a population of studies. In contrast to these average effect sizes of literature synthesis, I believe that the proper estimand is an effect-size surface, which is a function only of scientifically relevant factors, and which can only be estimated by extrapolating a response surface of observed effect sizes to a region of ideal studies. This effect-size surface perspective is presented and contras...

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Citations
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Journal ArticleDOI

Summing up evidence: one answer is not always enough

TL;DR: Here a more rounded approach to meta-analyses is argued, arguing that their strengths outweigh their weaknesses, although the latter must not be brushed aside.
Journal ArticleDOI

The effects of psychological therapies under clinically representative conditions: a meta-analysis.

TL;DR: This study illustrates the joint use of fixed and random effects models, use of pretest effect sizes to study selection bias in quasi-experiments, and use of regression analysis to project results to an ideal study in the spirit of response surface modeling.
Journal ArticleDOI

Meta-analysis for single-case consultation outcomes: Applications to research and practice

TL;DR: In this article, a meta-analytic method for using within-study treatment effect sizes in reporting consultation outcomes is presented, and the strengths and limitations of traditional group design meta-analysis are examined.
Journal ArticleDOI

The efficacy and effectiveness of marital and family therapy: a perspective from meta‐analysis

TL;DR: In this article, a meta-analysis of the effects of marital and family therapy (MFT) across 163 randomized trials is presented, concluding that MFT demonstrates moderate, statistically significant, and often clinically significant effects.
Journal ArticleDOI

A Meta‐Analytic Review of Child‐Centered Play Therapy Approaches

TL;DR: The authors explored the overall effectiveness of child-centered play therapy approaches through a meta-analytic review of 52 controlled outcome studies between 1995 and 2010, finding a statistically significant moderate treatment effect size for CCPT.
References
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Book

Statistical Power Analysis for the Behavioral Sciences

TL;DR: The concepts of power analysis are discussed in this paper, where Chi-square Tests for Goodness of Fit and Contingency Tables, t-Test for Means, and Sign Test are used.
Book

Statistical Analysis with Missing Data

TL;DR: This work states that maximum Likelihood for General Patterns of Missing Data: Introduction and Theory with Ignorable Nonresponse and large-Sample Inference Based on Maximum Likelihood Estimates is likely to be high.
Book

Statistical Methods for Meta-Analysis

TL;DR: In this article, the authors present a model for estimating the effect size from a series of experiments using a fixed effect model and a general linear model, and combine these two models to estimate the effect magnitude.
Journal ArticleDOI

The file drawer problem and tolerance for null results

TL;DR: Quantitative procedures for computing the tolerance for filed and future null results are reported and illustrated, and the implications are discussed.