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…

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…

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…

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…

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,…

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…

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…

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…

Introduction: The What Works Clearinghouse (WWC) reviews rigorous research on educational interventions with a goal of identifying "what works" and making that information accessible to educators and policymakers. The WWC has historically prioritized internal validity over external validity in rating the quality of research. One critique…

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…

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…

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…

Meta-analytic Structural Equation Modeling (MASEM) is the combination of meta-analysis (MA) and structural equation modeling (SEM). With new MASEM methodologies developed over the past few years, there is an opportunity to compare the past approaches with the new ones. The purpose of this dissertation is two-fold. First, the parameter estimates,…

Over the last four decades, meta-analysis has proven to be a vital analysis strategy in educational research for synthesizing research findings from different studies. When synthesizing studies in a meta-analysis, it is common to assume that the true underlying effect varies from study to study, as studies will differ in design, participants,…

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…