Meta-analyses examining dichotomous outcomes often include single-zero studies, where no events occur in intervention or control groups. These pose challenges, and several methods have been proposed to address them. A fixed continuity correction method has been shown to bias estimates, but it is frequently used because sometimes software (e.g.,…

Single-case comparative studies could help identify efficient instructional procedures for individuals with disabilities. However, previous literature reported inconsistent efficiency results if multiple comparisons were conducted, indicating that within-participant replication was uncommon. In this review, we examined single-case comparative…

We developed "metadta," a flexible, robust, and user-friendly statistical procedure that fuses established and innovative statistical methods for meta-analysis, meta-regression, and network meta-analysis of diagnostic test accuracy studies in Stata. Using data from published meta-analyses, we validate "metadta" by comparing and…

We first review existing literature on cumulative logit models along with various ways to test the parallel lines assumption. Building on the traditional frequentist framework, we introduce a method of Bayesian assessment of null values to provide an alternative way to examine the parallel lines assumption using highest density intervals and…

Causal inference involves determining whether a treatment (e.g., an education program) causes a change in outcomes (e.g., academic achievement). It is well-known that causal effects are more challenging to estimate than associations. Over the past 50 years, the potential outcomes framework has become one of the most widely used approaches for…

When meta-analyzing heterogeneous bodies of literature, meta-regression can be used to account for potentially relevant between-studies differences. A key challenge is that the number of candidate moderators is often high relative to the number of studies. This introduces risks of overfitting, spurious results, and model non-convergence. To…

Partial correlation coefficients are often used as effect sizes in the meta-analysis and systematic review of multiple regression analysis research results. There are two well-known formulas for the variance and thereby for the standard error (SE) of partial correlation coefficients (PCC). One is considered the "correct" variance in the…

Implementation planning is a consultative educator support strategy with preliminary evidence of effectiveness from single-case design research. This meta-analysis investigates the impacts of implementation planning on educator implementation and student outcomes and explores moderators of these relationships. Principles of open science and…

Meta-analysis is a statistical method that combines quantitative findings from previous studies. It has been increasingly used to obtain more credible results in a wide range of scientific fields. Combining the results of relevant studies allows researchers to leverage study similarities while modeling potential sources of between-study…

Purpose: Systematic review and meta-analysis are regarded as standard and valuable tools for providing an objective and reproducible synthesis of research findings in the literature. Their increasing popularity has led to heightened expectations for comprehensiveness and rigor in conducting scientific reviews and analyses. The purpose of this…

The purpose of this study is to determine the effect size of gender on motivation towards science learning by combining the results of studies, which were conducted to determine the effect of gender on motivation towards science learning, via the meta-analysis method. In this context, master's thesis, doctoral dissertations, and articles, which…

Computer-based assessment (CBA) is a top-rated tool for conducting assessments, mapping learning outcomes, and selecting new candidates. Research that examines the development and use of CBA is also increasing from year to year, so without bibliometric analysis, it would be quite challenging to keep up with all of these studies. This study aims to…

Background/Context: Methodological background: Meta-analysis typically depends on the assumption that true effects follow the normal distribution. While assuming normality of effect "estimates" is often supported by a central limit theorem, normality for the distribution of interventions' "true" effects is a computational…

Two meta-analyses assessed whether the relations between reading and mathematics outcomes could be explained through overlapping skills (e.g., systems for word and fact retrieval) or domain-general influences (e.g., top-down attentional control). The first (378 studies, 1,282,796 participants) included weighted random-effects meta-regression…

When studies use different scales to measure continuous outcomes, standardised mean differences (SMD) are required to meta-analyse the data. However, outcomes are often reported as endpoint or change from baseline scores. Combining corresponding SMDs can be problematic and available guidance advises against this practice. We aimed to examine the…