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Kulinskaya, Elena; Hoaglin, David C. – Research Synthesis Methods, 2023
For estimation of heterogeneity variance T[superscript 2] in meta-analysis of log-odds-ratio, we derive new mean- and median-unbiased point estimators and new interval estimators based on a generalized Q statistic, Q[subscript F], in which the weights depend on only the studies' effective sample sizes. We compare them with familiar estimators…
Descriptors: Q Methodology, Statistical Analysis, Meta Analysis, Intervals
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Lin, Lifeng – Research Synthesis Methods, 2019
Assessing publication bias is a critical procedure in meta-analyses for rating the synthesized overall evidence. Because statistical tests for publication bias are usually not powerful and only give "P" values that inform either the presence or absence of the bias, examining the asymmetry of funnel plots has been popular to investigate…
Descriptors: Meta Analysis, Sample Size, Graphs, Bias
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Li, Xinru; Dusseldorp, Elise; Meulman, Jacqueline J. – Research Synthesis Methods, 2019
In meta-analytic studies, there are often multiple moderators available (eg, study characteristics). In such cases, traditional meta-analysis methods often lack sufficient power to investigate interaction effects between moderators, especially high-order interactions. To overcome this problem, meta-CART was proposed: an approach that applies…
Descriptors: Correlation, Meta Analysis, Identification, Testing
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Hong, Sanghyun; Reed, W. Robert – Research Synthesis Methods, 2021
The purpose of this study is to show how Monte Carlo analysis of meta-analytic estimators can be used to select estimators for specific research situations. Our analysis conducts 1620 individual experiments, where each experiment is defined by a unique combination of sample size, effect size, effect size heterogeneity, publication selection…
Descriptors: Monte Carlo Methods, Meta Analysis, Research Methodology, Experiments
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Burke, Danielle L.; Ensor, Joie; Snell, Kym I. E.; van der Windt, Danielle; Riley, Richard D. – Research Synthesis Methods, 2018
Percentage study weights in meta-analysis reveal the contribution of each study toward the overall summary results and are especially important when some studies are considered outliers or at high risk of bias. In meta-analyses of test accuracy reviews, such as a bivariate meta-analysis of sensitivity and specificity, the percentage study weights…
Descriptors: Meta Analysis, Research Reports, Statistical Analysis, Sample Size
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Joo, Seang-hwane; Wang, Yan; Ferron, John M. – AERA Online Paper Repository, 2017
Multiple-baseline studies provide meta-analysts the opportunity to compute effect sizes based on either within-series comparisons of treatment phase to baseline phase observations, or time specific between-series comparisons of observations from those that have started treatment to observations of those that are still in baseline. The advantage of…
Descriptors: Meta Analysis, Effect Size, Hierarchical Linear Modeling, Computation
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Tipton, Elizabeth – Society for Research on Educational Effectiveness, 2014
Replication studies allow for making comparisons and generalizations regarding the effectiveness of an intervention across different populations, versions of a treatment, settings and contexts, and outcomes. One method for making these comparisons across many replication studies is through the use of meta-analysis. A recent innovation in…
Descriptors: Replication (Evaluation), Robustness (Statistics), Meta Analysis, Regression (Statistics)
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Lindstromberg, Seth – Language Teaching Research, 2016
This article reviews all (quasi)experimental studies appearing in the first 19 volumes (1997-2015) of "Language Teaching Research" (LTR). Specifically, it provides an overview of how statistical analyses were conducted in these studies and of how the analyses were reported. The overall conclusion is that there has been a tight adherence…
Descriptors: Meta Analysis, Second Language Learning, Second Language Instruction, Guidelines
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Veroniki, Areti Angeliki; Pavlides, Marios; Patsopoulos, Nikolaos A.; Salanti, Georgia – Research Synthesis Methods, 2013
A problem that is frequently encountered during the systematic review process is when studies that meet the inclusion criteria do not provide the appropriate numerical estimates to include in a meta-analysis. For dichotomous outcomes, a method has been suggested by Di Pietrantonj for reconstructing the 2 × 2 table when the Odds Ratio…
Descriptors: Meta Analysis, Tables (Data), Statistical Analysis, Error of Measurement
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Hedges, Larry V. – Journal of Educational and Behavioral Statistics, 2011
Research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Many of these designs involve two levels of clustering or nesting (students within classes and classes within schools). Researchers would like to compute effect size indexes based on the standardized mean difference to…
Descriptors: Effect Size, Research Design, Experiments, Computation
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Warne, Russell T. – Journal of Advanced Academics, 2011
Reliability generalization (RG) is a meta-analysis that combines and synthesizes reliability coefficients from different studies to ascertain the average observed reliability across studies. An RG study was conducted on previously reported data from 16 samples of the Overexcitability Questionnaire--Two (OEQII) with a combined "N" of 5,275.…
Descriptors: Measures (Individuals), Error of Measurement, Psychometrics, Generalization
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Marin-Martinez, Fulgencio; Sanchez-Meca, Julio – Educational and Psychological Measurement, 2010
Most of the statistical procedures in meta-analysis are based on the estimation of average effect sizes from a set of primary studies. The optimal weight for averaging a set of independent effect sizes is the inverse variance of each effect size, but in practice these weights have to be estimated, being affected by sampling error. When assuming a…
Descriptors: Meta Analysis, Sample Size, Effect Size, Monte Carlo Methods
Neel, John H. – 1988
Methods to aid the statistical researchers in making arguments as to what constitutes minimal effect size (MES) are outlined. By selecting MES and determining power for that effect, the researcher communicates to the reader what the researcher considers to be important and what the researcher's chances are for finding that effect or a larger one.…
Descriptors: Effect Size, Error of Measurement, Meta Analysis, Power (Statistics)
Du, Yunfei – 2002
This paper discusses the impact of sampling error on the construction of confidence intervals around effect sizes. Sampling error affects the location and precision of confidence intervals. Meta-analytic resampling demonstrates that confidence intervals can haphazardly bounce around the true population parameter. Special software with graphical…
Descriptors: Computer Software, Effect Size, Error of Measurement, Meta Analysis
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Bosch, Holger; Steinkamp, Fiona; Boller, Emil – Psychological Bulletin, 2006
Seance-room and other large-scale psychokinetic phenomena have fascinated humankind for decades. Experimental research has reduced these phenomena to attempts to influence (a) the fall of dice and, later, (b) the output of random number generators (RNGs). The meta-analysis combined 380 studies that assessed whether RNG output correlated with human…
Descriptors: Nonverbal Communication, Intention, Interaction, Meta Analysis
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