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Showing 1 to 15 of 145 results Save | Export
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T. D. Stanley; Hristos Doucouliagos; Tomas Havranek – Research Synthesis Methods, 2024
We demonstrate that all meta-analyses of partial correlations are biased, and yet hundreds of meta-analyses of partial correlation coefficients (PCCs) are conducted each year widely across economics, business, education, psychology, and medical research. To address these biases, we offer a new weighted average, UWLS[subscript +3]. UWLS[subscript…
Descriptors: Meta Analysis, Correlation, Bias, Sample Size
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Rrita Zejnullahi; Larry V. Hedges – Research Synthesis Methods, 2024
Conventional random-effects models in meta-analysis rely on large sample approximations instead of exact small sample results. While random-effects methods produce efficient estimates and confidence intervals for the summary effect have correct coverage when the number of studies is sufficiently large, we demonstrate that conventional methods…
Descriptors: Robustness (Statistics), Meta Analysis, Sample Size, Computation
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Jiang, Ziren; Cao, Wenhao; Chu, Haitao; Bazerbachi, Fateh; Siegel, Lianne – Research Synthesis Methods, 2023
A reference interval, or an interval in which a prespecified proportion of measurements from a healthy population are expected to fall, is used to determine whether a person's measurement is typical of a healthy individual. For a specific biomarker, multiple published studies may provide data collected from healthy participants. A reference…
Descriptors: Intervals, Computation, Meta Analysis, Measurement
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Jansen, Katrin; Holling, Heinz – Research Synthesis Methods, 2023
In meta-analyses of rare events, it can be challenging to obtain a reliable estimate of the pooled effect, in particular when the meta-analysis is based on a small number of studies. Recent simulation studies have shown that the beta-binomial model is a promising candidate in this situation, but have thus far only investigated its performance in a…
Descriptors: Bayesian Statistics, Meta Analysis, Probability, Simulation
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Schwarzer, Guido; Efthimiou, Orestis; Rücker, Gerta – Research Synthesis Methods, 2021
The Peto odds ratio is a well-known effect measure in meta-analysis of binary outcomes. For pairwise comparisons, the Peto odds ratio estimator can be severely biased in the situation of unbalanced sample sizes in the two treatment groups or large treatment effects. In this publication, we evaluate Peto odds ratio estimators in the setting of…
Descriptors: Meta Analysis, Sample Size, Computation, Probability
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Chuanjian Zhang; Na Sun; Yueshuai Jiang; Huacong Liu; Qinhui Huang – Asia-Pacific Education Researcher, 2025
Peer tutoring has become a widely used practice in higher education institutions to support students' academic success, although its effects remain controversial. This article synthesizes 27 independent experimental and quasi-experimental studies to examine the relationship between peer tutoring programs and college students' academic performance,…
Descriptors: Peer Teaching, Tutoring, Academic Achievement, Higher Education
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Nurbanu Kansizoglu; Nazan Bekiroglu – Journal of Pedagogical Research, 2025
This study aims to assess the overall impact of vocabulary development interventions on cognitive vocabulary outcomes. To achieve this, 43 theses on vocabulary teaching, each involving a specific intervention, were analyzed using meta-analysis. The findings from the meta-analysis, based on the random effects model, indicated that the average…
Descriptors: Vocabulary Development, Intervention, Outcomes of Education, Meta Analysis
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Winton, Bradley G.; Sabol, Misty A. – International Journal of Social Research Methodology, 2022
Convenience sampling dominates social science research. But there is a paucity of studies comparing the impact of sample source type based on composite-based theoretical model relationships. This study empirically tests four different sample sources (e.g. student, crowdsourced, professional panel, and respondent driven social network) to assess…
Descriptors: Sampling, Sample Size, Social Science Research, Measurement
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Jackson, Dan; Rhodes, Kirsty; Ouwens, Mario – Research Synthesis Methods, 2021
Methods for indirect comparisons and network meta-analysis use aggregate level data from multiple studies. A very common, and closely related, scenario is where a company has individual patient data (IPD) from its own trial, but only has published aggregate data from a competitor's trial, and an indirect comparison of the treatments evaluated in…
Descriptors: Comparative Analysis, Meta Analysis, Sample Size, Statistical Analysis
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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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Riley, Richard D.; Collins, Gary S.; Hattle, Miriam; Whittle, Rebecca; Ensor, Joie – Research Synthesis Methods, 2023
Before embarking on an individual participant data meta-analysis (IPDMA) project, researchers should consider the power of their planned IPDMA conditional on the studies promising their IPD and their characteristics. Such power estimates help inform whether the IPDMA project is worth the time and funding investment, before IPD are collected. Here,…
Descriptors: Computation, Meta Analysis, Participant Characteristics, Data
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Qi, Hongchao; Rizopoulos, Dimitris; Rosmalen, Joost – Research Synthesis Methods, 2023
The meta-analytic-predictive (MAP) approach is a Bayesian method to incorporate historical controls in new trials that aims to increase the statistical power and reduce the required sample size. Here we investigate how to calculate the sample size of the new trial when historical data is available, and the MAP approach is used in the analysis. In…
Descriptors: Sample Size, Computation, Meta Analysis, Bayesian Statistics
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Rrita Zejnullahi – Society for Research on Educational Effectiveness, 2021
Background: Meta-analysis is considered to be the gold standard for evidence synthesis. It involves combining data from multiple independent sources to produce a summary estimate with improved precision. Traditionally, meta-analysis methods have been applied to a large collection of studies, and past research efforts have indicated its numerous…
Descriptors: Meta Analysis, Randomized Controlled Trials, Sample Size, Best Practices
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Shi, Jiandong; Luo, Dehui; Weng, Hong; Zeng, Xian-Tao; Lin, Lu; Chu, Haitao; Tong, Tiejun – Research Synthesis Methods, 2020
When reporting the results of clinical studies, some researchers may choose the five-number summary (including the sample median, the first and third quartiles, and the minimum and maximum values) rather than the sample mean and standard deviation (SD), particularly for skewed data. For these studies, when included in a meta-analysis, it is often…
Descriptors: Statistics, Computation, Sample Size, Mathematical Formulas
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Wenhao Yu; Jiaqi He; Julan Luo; Xiaoyan Shu – Journal of Computer Assisted Learning, 2024
Background: Although gender inequality in education is gaining increasing attention, female underrepresentation remains pervasive in STEM fields. Many studies have applied various interventions to narrow the gender gap in STEM education. Objectives: In this study, we conducted a systematic meta-analysis to examine the effectiveness of various…
Descriptors: Intervention, Sex Fairness, STEM Education, Females
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