Qualitative comparative analysis (QCA) is a hybrid method designed to bridge the gap between qualitative and quantitative research in a case-sensitive approach that considers each case holistically as a complex configuration of conditions and outcomes. QCA allows for multiple conjunctural causation, implying that it is often a combination of…

Methods for indirect comparisons and network meta-analysis use aggregate level data from multiple studies. A very common, and closely related, scenario is where a company has individual patient data (IPD) from its own trial, but only has published aggregate data from a competitor's trial, and an indirect comparison of the treatments evaluated in…

Population-adjusted indirect comparisons estimate treatment effects when access to individual patient data is limited and there are cross-trial differences in effect modifiers. Popular methods include matching-adjusted indirect comparison (MAIC) and simulated treatment comparison (STC). There is limited formal evaluation of these methods and…

Network meta-analysis is a popular method to synthesize the information obtained in a systematic review of studies (e.g., randomized clinical trials) involving subsets of multiple treatments of interest. The dominant method of analysis employs within-study information on treatment contrasts and integrates this over a network of studies. One…

Meta-analysis of individual participant data (IPD) is considered the "gold-standard" for synthesizing clinical study evidence. However, gaining access to IPD can be a laborious task (if possible at all) and in practice only summary (aggregate) data are commonly available. In this work we focus on meta-analytic approaches of comparative…

Meta-analyses often include only a small number of studies ([less than or equal to]5). Estimating between-study heterogeneity is difficult in this situation. An inaccurate estimation of heterogeneity can result in biased effect estimates and too narrow confidence intervals. The beta-binominal model has shown good statistical properties for…

Background: This study describes an approach for the use of a specific type of qualitative evidence synthesis in the matrix approach, a mixed studies reviewing method. The matrix approach compares quantitative and qualitative data on the review level by juxtaposing concrete recommendations from the qualitative evidence synthesis against…

Indirect treatment comparisons are useful to estimate relative treatment effects when head-to-head studies are not conducted. Statisticians at the National Centre for Pharmacoeconomics Ireland (NCPE) and Scottish Medicines Consortium (SMC) assess the clinical and cost-effectiveness of new medicines as part of multidisciplinary teams. We describe…

Objective: Various statistical methods have been developed to estimate hazard ratios (HRs) from published Kaplan-Meier (KM) curves for the purpose of performing meta-analyses. The objective of this study was to determine the reliability, accuracy, and precision of four commonly used methods by Guyot, Williamson, Parmar, and Hoyle and Henley.…

Meta-analytic structural equation modeling (MASEM) combines the techniques of meta-analysis and structural equation modeling for the purpose of synthesizing correlation or covariance matrices and fitting structural equation models on the pooled correlation or covariance matrix. Both fixed-effects and random-effects models can be defined in MASEM.…

Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable…

In meta-analysis, the random-effects model is often used to account for heterogeneity. The model assumes that heterogeneity has an additive effect on the variance of effect sizes. An alternative model, which assumes multiplicative heterogeneity, has been little used in the medical statistics community, but is widely used by particle physicists. In…

Meta-analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between-study variability, which is typically modelled using a between-study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between-study variance,…

Aim: To examine how effectively forwards citation searching with Web of Science (WOS) or Google Scholar (GS) identified evidence to support public health guidance published by the National Institute for Health and Care Excellence. Method: Forwards citation searching was performed using GS on a base set of 46 publications and replicated using WOS.…

Statistical methods for sequential meta-analysis have applications also for the design of new trials. Existing methods are based on group sequential methods developed for single trials and start with the calculation of a required information size. This works satisfactorily within the framework of fixed effects meta-analysis, but conceptual…