Using a sample of 70,399 published p-values from 192 meta-analyses, we empirically estimate the counterfactual distribution of p-values in the absence of any biases. Comparing observed p-values with counterfactually expected p-values allows us to estimate how many p-values are published as being statistically significant when they should have been…

The Cochrane Rapid Review Methods Group (RRMG) first released interim guidance in March 2020 to support authors in conducting rapid reviews (RRs). The objective of this mixed-methods study was to assess the adherence and investigate authors' understanding of the RRMG guidance. We identified all documents citing the Interim Cochrane RRMG guidance…

Collecting data for an individual participant data meta-analysis (IPDMA) project can be time consuming and resource intensive and could still have insufficient power to answer the question of interest. Therefore, researchers should consider the power of their planned IPDMA before collecting IPD. Here we propose a method to estimate the power of a…

Sample size and statistical power are important factors to consider when planning a research synthesis. Power analysis methods have been developed for fixed effect or random effects models, but until recently these methods were limited to simple data structures with a single, independent effect per study. Recent work has provided power…

In fields (such as population health) where randomised trials are often lacking, systematic reviews (SRs) can harness diversity in study design, settings and populations to assess the evidence for a putative causal relationship. SRs may incorporate causal assessment approaches (CAAs), sometimes called 'causal reviews', but there is currently no…

Mendelian randomization (MR) uses genetic variants as instrumental variables to infer whether a risk factor causally affects a health outcome. Meta-analysis has been used historically in MR to combine results from separate epidemiological studies, with each study using a small but select group of genetic variants. In recent years, it has been used…

Meta-analyses are often used to estimate the relative average values of a quantitative outcome in two groups (eg, control and experimental groups). However, they may also examine the relative variability (variance) of those groups. For such comparisons, two relatively new effect size statistics, the log-transformed "variability ratio"…

Descriptive analyses of socially important or theoretically interesting phenomena and trends are a vital component of research in the behavioral, social, economic, and health sciences. Such analyses yield reliable results when using representative individual participant data (IPD) from studies with complex survey designs, including educational…

The purpose of this study is to show how Monte Carlo analysis of meta-analytic estimators can be used to select estimators for specific research situations. Our analysis conducts 1620 individual experiments, where each experiment is defined by a unique combination of sample size, effect size, effect size heterogeneity, publication selection…

Systematic reviews often encounter primary studies that report multiple effect sizes based on data from the same participants. These have the potential to introduce statistical dependency into the meta-analytic data set. In this paper, we provide a tutorial on dealing with effect size multiplicity within studies in the context of meta-analyses of…

Clinical trials have different designs: In late stage drug development, the parallel trial design is the most frequent one; however, the crossover design is not rare; different techniques are used to analyse their results. Although both designs measure the same treatment effect, combining parallel and crossover trials in a meta-analysis is not…

Network meta-analysis compares multiple treatments in terms of their efficacy and harm by including evidence from randomized controlled trials. Most clinical trials use parallel design, where patients are randomly allocated to different treatments and receive only 1 treatment. However, some trials use within person designs such as split-body,…

Studies combined in a meta-analysis often have differences in their design and conduct that can lead to heterogeneous results. A random-effects model accounts for these differences in the underlying study effects, which includes a heterogeneity variance parameter. The DerSimonian-Laird method is often used to estimate the heterogeneity variance,…

Objective: Search strategies are essential for the adequate retrieval of studies in a systematic review (SR). Our objective was to identify problems in the design and reporting of search strategies in a sample of new Cochrane SRs first published in The Cochrane Library in 2015. Study design and setting: We took a random sample of 70 new Cochrane…

When the Medical Library Association identified questions critical for the future of the profession, it assigned groups to use systematic reviews to find the answers to these questions. Group 6, whose question was on emerging technologies, recognized early on that the systematic review process would not work well for this question, which looks…