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Manolov, Rumen; Solanas, Antonio – Psychological Methods, 2012
There is currently a considerable diversity of quantitative measures available for summarizing the results in single-case studies. Given that the interpretation of some of them is difficult due to the lack of established benchmarks, the current article proposes an approach for obtaining further numerical evidence on the importance of the results,…
Descriptors: Sampling, Probability, Statistical Significance, Case Studies
Bonett, Douglas G. – Psychological Methods, 2009
The fixed-effects (FE) meta-analytic confidence intervals for unstandardized and standardized mean differences are based on an unrealistic assumption of effect-size homogeneity and perform poorly when this assumption is violated. The random-effects (RE) meta-analytic confidence intervals are based on an unrealistic assumption that the selected…
Descriptors: Intervals, Effect Size, Meta Analysis, Statistical Analysis
Curran, Patrick J.; Hussong, Andrea M. – Psychological Methods, 2009
There are both quantitative and methodological techniques that foster the development and maintenance of a cumulative knowledge base within the psychological sciences. Most noteworthy of these techniques is meta-analysis, which allows for the synthesis of summary statistics drawn from multiple studies when the original data are not available.…
Descriptors: Psychology, Sciences, Statistical Analysis, Meta Analysis
Cooper, Harris; Patall, Erika A. – Psychological Methods, 2009
The authors describe the relative benefits of conducting meta-analyses with (a) individual participant data (IPD) gathered from the constituent studies and (b) aggregated data (AD), or the group-level statistics (in particular, effect sizes) that appear in reports of a study's results. Given that both IPD and AD are equally available,…
Descriptors: Data Analysis, Meta Analysis, Databases, Coordination
Sanchez-Meca, Julio; Marin-Martinez, Fulgencio – Psychological Methods, 2008
One of the main objectives in meta-analysis is to estimate the overall effect size by calculating a confidence interval (CI). The usual procedure consists of assuming a standard normal distribution and a sampling variance defined as the inverse of the sum of the estimated weights of the effect sizes. But this procedure does not take into account…
Descriptors: Intervals, Monte Carlo Methods, Meta Analysis, Effect Size
Cheung, Mike W.-L. – Psychological Methods, 2008
Meta-analysis and structural equation modeling (SEM) are two important statistical methods in the behavioral, social, and medical sciences. They are generally treated as two unrelated topics in the literature. The present article proposes a model to integrate fixed-, random-, and mixed-effects meta-analyses into the SEM framework. By applying an…
Descriptors: Structural Equation Models, Effect Size, Meta Analysis, Models
Honekopp, Johannes; Becker, Betsy Jane; Oswald, Frederick L. – Psychological Methods, 2006
Four types of analysis are commonly applied to data from structured Rater [times] Ratee designs. These types are characterized by the unit of analysis, which is either raters or ratees, and by the design used, which is either between-units or within-unit design. The 4 types of analysis are quite different, and therefore they give rise to effect…
Descriptors: Meta Analysis, Effect Size, Data Analysis, Evaluators
Valentine, Jeffrey C.; McHugh, Cathleen M. – Psychological Methods, 2007
Using meta-analysis, randomized experiments in education that either clearly did or clearly did not experience student attrition were examined for the baseline comparability of groups. Results from 35 studies suggested that after attrition, the observed measures of baseline comparability of groups did not differ more than would be expected given…
Descriptors: Sampling, Effect Size, Student Attrition, Educational Research
Hsu, Louis M. – Psychological Methods, 2005
One version of r-sub(equivalent), calculated from Fisher's exact test p values and recommended for small samples, is considered "a more realistic... [and] a more accurate estimate of the population correlation than... the sample correlation, r-sub(sample)" (R. Rosenthal & D. B. Rubin, 2003, p. 494). Small sample properties of r-sub(sample) and of…
Descriptors: Correlation, Meta Analysis, Error of Measurement, Effect Size
Vevea, Jack L.; Woods, Carol M. – Psychological Methods, 2005
Publication bias, sometimes known as the "file-drawer problem" or "funnel-plot asymmetry," is common in empirical research. The authors review the implications of publication bias for quantitative research synthesis (meta-analysis) and describe existing techniques for detecting and correcting it. A new approach is proposed that is suitable for…
Descriptors: Bias, Synthesis, Meta Analysis, Effect Size
Hedges, Larry V.; Pigott, Therese D. – Psychological Methods, 2004
Calculation of the statistical power of statistical tests is important in planning and interpreting the results of research studies, including meta-analyses. It is particularly important in moderator analyses in meta-analysis, which are often used as sensitivity analyses to rule out moderator effects but also may have low statistical power. This…
Descriptors: Goodness of Fit, Multiple Regression Analysis, Effect Size, Statistical Analysis
Field, Andy P. – Psychological Methods, 2005
One conceptualization of meta-analysis is that studies within the meta-analysis are sampled from populations with mean effect sizes that vary (random-effects models). The consequences of not applying such models and the comparison of different methods have been hotly debated. A Monte Carlo study compared the efficacy of Hedges and Vevea's…
Descriptors: Meta Analysis, Correlation, Effect Size, Models