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Gamon Savatsomboon; Phamornpun Yurayat; Ong-art Chanprasitchai; Warawut Narkbunnum; Jibon Kumar Sharma; Surapol Svetsomboon – Journal of Practical Studies in Education, 2024
The paper has three major objectives. The first objective of the paper is to synthesize and define common categories of meta-analysis. The second objective is to propose a way to comprehend these common categories of meta-analysis through learning from their respective generic conceptual frameworks. The third objective is to point out which R…
Descriptors: Classification, Meta Analysis, Computer Software, Educational Research
James E. Pustejovsky; Man Chen – Journal of Educational and Behavioral Statistics, 2024
Meta-analyses of educational research findings frequently involve statistically dependent effect size estimates. Meta-analysts have often addressed dependence issues using ad hoc approaches that involve modifying the data to conform to the assumptions of models for independent effect size estimates, such as by aggregating estimates to obtain one…
Descriptors: Meta Analysis, Multivariate Analysis, Effect Size, Evaluation Methods
Gamon Savatsomboon; Prasert Ruannakarn; Phamornpun Yurayat; Ong-art Chanprasitchai; Jibon Kumar Sharma Leihaothabam – European Journal of Psychology and Educational Research, 2024
Using R to conduct univariate meta-analyses is becoming common for publication. However, R can also conduct multivariate meta-analysis (MMA). However, newcomers to both R and MMA may find using R to conduct MMA daunting. Given that, R may not be easy for those unfamiliar with coding. Likewise, MMA is a topic of advanced statistics. Thus, it may be…
Descriptors: Educational Psychology, Multivariate Analysis, Evaluation Methods, Data Processing
Reza Norouzian; Zhouhan Jin; Stuart Webb – Modern Language Journal, 2025
Meta-analytic studies of second language (L2) learning typically employ a classic approach to meta-analysis. Although the classic approach can clarify findings, a multivariate, multilevel meta-analysis (3M) approach increases transparency by accounting for (a) dependencies in the evidence presented by primary studies, (b) methodological…
Descriptors: Meta Analysis, Multivariate Analysis, Notetaking, Second Language Learning
Seo, Michael; Furukawa, Toshi A.; Karyotaki, Eirini; Efthimiou, Orestis – Research Synthesis Methods, 2023
Clinical prediction models are widely used in modern clinical practice. Such models are often developed using individual patient data (IPD) from a single study, but often there are IPD available from multiple studies. This allows using meta-analytical methods for developing prediction models, increasing power and precision. Different studies,…
Descriptors: Prediction, Models, Patients, Data Analysis
Miriam Hattle; Joie Ensor; Katie Scandrett; Marienke van Middelkoop; Danielle A. van der Windt; Melanie A. Holden; Richard D. Riley – Research Synthesis Methods, 2024
Individual participant data (IPD) meta-analysis projects obtain, harmonise, and synthesise original data from multiple studies. Many IPD meta-analyses of randomised trials are initiated to identify treatment effect modifiers at the individual level, thus requiring statistical modelling of interactions between treatment effect and participant-level…
Descriptors: Meta Analysis, Randomized Controlled Trials, Outcomes of Treatment, Evaluation Methods
Belias, Michail; Rovers, Maroeska M.; Hoogland, Jeroen; Reitsma, Johannes B.; Debray, Thomas P. A.; IntHout, Joanna – Research Synthesis Methods, 2022
One of the main goals of an individual participant data meta-analysis (IPD-MA) of intervention studies is to investigate whether treatment effect differences are present, and how they are associated with patient characteristics. Examining treatment heterogeneity due to a continuous covariable (e.g., BMI or age) may be challenging, since there is…
Descriptors: Meta Analysis, Outcomes of Treatment, Prediction, Multivariate Analysis
Shih, Ming-Chieh; Tu, Yu-Kang – Research Synthesis Methods, 2021
Network meta-analysis (NMA) compares the efficacy and harm between several treatments by combining direct and indirect evidence. The validity of NMA requires that all available evidence form a coherent network. Failure to meet such requirement is known as inconsistency. The most popular approach to inconsistency detection is to compare the direct…
Descriptors: Networks, Meta Analysis, Evidence, Evaluation Methods
Cerullo, Enzo; Jones, Hayley E.; Carter, Olivia; Quinn, Terry J.; Cooper, Nicola J.; Sutton, Alex J. – Research Synthesis Methods, 2022
Standard methods for the meta-analysis of medical tests, without assuming a gold standard, are limited to dichotomous data. Multivariate probit models are used to analyse correlated dichotomous data, and can be extended to model ordinal data. Within the context of an imperfect gold standard, they have previously been used for the analysis of…
Descriptors: Meta Analysis, Test Format, Medicine, Standards
Godolphin, Peter J.; White, Ian R.; Tierney, Jayne F.; Fisher, David J. – Research Synthesis Methods, 2023
Estimation of within-trial interactions in meta-analysis is crucial for reliable assessment of how treatment effects vary across participant subgroups. However, current methods have various limitations. Patients, clinicians and policy-makers need reliable estimates of treatment effects within specific covariate subgroups, on relative and absolute…
Descriptors: Meta Analysis, Outcomes of Treatment, Medical Research, Comparative Analysis
Jamshidi, Laleh; Declercq, Lies; Fernández-Castilla, Belén; Ferron, John M.; Moeyaert, Mariola; Beretvas, S. Natasha; Van den Noortgate, Wim – Journal of Experimental Education, 2021
Previous research found bias in the estimate of the overall fixed effects and variance components using multilevel meta-analyses of standardized single-case data. Therefore, we evaluate two adjustments in an attempt to reduce the bias and improve the statistical properties of the parameter estimates. The results confirm the existence of bias when…
Descriptors: Statistical Bias, Multivariate Analysis, Meta Analysis, Research Design
Hong, Chuan; Riley, Richard D.; Chen, Yong – Research Synthesis Methods, 2018
Multivariate meta-analysis, which jointly analyzes multiple and possibly correlated outcomes in a single analysis, is becoming increasingly popular in recent years. An attractive feature of the multivariate meta-analysis is its ability to account for the dependence between multiple estimates from the same study. However, standard inference…
Descriptors: Meta Analysis, Correlation, Multivariate Analysis, Research Methodology
Cope, Shannon; Chan, Keith; Jansen, Jeroen P. – Research Synthesis Methods, 2020
Background: Network meta-analysis (NMA) of survival data with a multidimensional treatment effect has been introduced as an alternative to NMA based on the proportional hazards assumption. However, these flexible models have some limitations, such as the use of an approximate likelihood based on discrete hazards, rather than a likelihood for…
Descriptors: Multivariate Analysis, Meta Analysis, Network Analysis, Models
Lin, Lifeng; Chu, Haitao – Research Synthesis Methods, 2018
In medical sciences, a disease condition is typically associated with multiple risk and protective factors. Although many studies report results of multiple factors, nearly all meta-analyses separately synthesize the association between each factor and the disease condition of interest. The collected studies usually report different subsets of…
Descriptors: Bayesian Statistics, Multivariate Analysis, Meta Analysis, Correlation
Onwuegbuzie, Anthony J.; Corrigan, Julie A. – Research in the Schools, 2018
Conducting mixed methods research studies has the potential to help researchers who represent special education to address relatively complex questions compared to monomethod research studies. Therefore, it is important to determine the prevalence of mixed methods research studies in special education, especially because the prevalence rate…
Descriptors: Mixed Methods Research, Special Education, Educational Research, Incidence

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