Meta-analyses can be compromised by studies' internal biases (e.g., confounding in nonrandomized studies) as well as publication bias. These biases often operate nonadditively: publication bias that favors significant, positive results selects indirectly for studies with more internal bias. We propose sensitivity analyses that address two…

Systematic reviews are a time-consuming yet effective approach to understanding research trends. While researchers have investigated how to speed up the process of screening studies for potential inclusion, few have focused on to what extent we can use algorithms to extract data instead of human coders. In this study, we explore to what extent…

The number of meta-analyses of aggregate data has dramatically increased due to the facility of obtaining data from publications and the development of free, easy-to-use, and specialised statistical software. Even when meta-analyses include the same studies, their results may vary owing to different methodological choices. Assessment of the…

Background: Traditionally, meta-analysis of time-to-event outcomes reports a single pooled hazard ratio assuming proportional hazards (PH). For health technology assessment evaluations, hazard ratios are frequently extrapolated across a lifetime horizon. However, when treatment effects vary over time, an assumption of PH is not always valid. The…

Differences in effect sizes between researcher developed (RD) and independently developed (ID) outcome measures are widely documented but poorly understood in education research. We conduct a meta-analysis using item-level outcome data to test potential mechanisms that explain differences in effects by RD or ID outcome type. Our analysis of 45…

Meta-analysts often encounter missing covariate values when estimating meta-regression models. In practice, ad hoc approaches involving data deletion have been widely used. The current study investigates the performance of different methods for handling missing covariates in meta-regression, including complete-case analysis (CCA), shifting-case…

In sparse data meta-analyses (with few trials or zero events), conventional methods may distort results. Although better-performing one-stage methods have become available in recent years, their implementation remains limited in practice. This study examines the impact of using conventional methods compared to one-stage models by re-analysing…

Researchers may have at their disposal the raw data of the studies they wish to meta-analyze. The goal of this study is to identify, illustrate, and compare a range of possible analysis options for researchers to whom raw data are available, wanting to fit a structural equation model (SEM) to these data. This study illustrates techniques that…

In network meta-analysis (NMA), we synthesize all relevant evidence about health outcomes with competing treatments. The evidence may come from randomized clinical trials (RCT) or non-randomized studies (NRS) as individual participant data (IPD) or as aggregate data (AD). We present a suite of Bayesian NMA and network meta-regression (NMR) models…

It may be possible to teach students in undergraduate research methods courses about replication, while simultaneously providing the discipline a means to solve what some have called a replication "crisis." Over the span of three consecutive fall semesters, students replicated Cialdini and Schroeder's "even a penny will help"…

Longitudinal studies provide developmental science with invaluable information about how variables and the associations between variables change across time, but typically give limited attention to the length of time over which that change occurs. The present study re-analyzed data from previously published meta-analyses of longitudinal data…

Background: Meta-analysis refers to the statistical methods employed to combine results of several empirical studies in a topic of interest (Hedges & Olkin, 1985). Meta-analysis is often included in literature review studies to quantitatively analyze data from a collection of studies (Valentine et al., 2010). The statistical power of a…

Meta-analytic models for dependent effect sizes have grown increasingly sophisticated over the last few decades, which has created challenges for a priori power calculations. We introduce power approximations for tests of average effect sizes based upon several common approaches for handling dependent effect sizes. In a Monte Carlo simulation, we…

Background: Searching the literature and screening studies are two key stages to build a strong foundation for a quality systematic review. Low-quality handsearching and citation chasing processes may lead to missing relevant studies, while low-quality study screening may lead to human errors and a lengthy process (Haddaway et al., 2022; Zhang…

Background: Systematic reviews and meta-analyses of interventions can provide critical evidence for educators and policymakers by providing insights into the effectiveness of related interventions. The quality of included studies builds the foundation for a high-quality review, while bias in the included studies increases the risks of unreliable…