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Understanding dose-response relationships is crucial in optimizing clinical outcomes, particularly in complex interventions such as psychotherapy. While dose-response research is common in pharmaceutical conte...
Supervised machine learning is increasingly being used to estimate clinical predictive models. Several supervised machine learning models involve hyper-parameters, whose values must be judiciously specified to...
Consolidation of treatment effects from randomized controlled trials (RCT) is considered one of the highest forms of evidence in research. Cluster randomized trials (CRT) are increasingly used in the assessmen...
Finite mixture models have been recently applied in time-to-event data to identify subgroups with distinct hazard functions, yet they often assume differing covariate effects on failure times across latent cla...
Indirect treatment comparisons can provide evidence of relative efficacy for novel therapies when implementation of a randomised controlled trial is infeasible. However, such comparisons are vulnerable to unme...
Systematic reviews (SRs) are essential to formulate evidence-based guidelines but require time-consuming and costly literature screening. Large Language Models (LLMs) can be a powerful tool to expedite SRs.
The demand for rehabilitation services is rising due to the aging population and increasing number of chronic conditions. High-quality research is essential to address these challenges, with recent mandates em...
The Cass Review aimed to provide recommendations for the delivery of services for gender diverse children and young people in England. The final product of this project, the Cass report, relied on commissioned...
Staircase designs are incomplete stepped wedge designs that, unlike standard stepped wedge designs, require clusters to contribute data for only a limited number of trial periods. Previous work has provided fo...
Vulnerable subgroups of the population, such as care home residents, often face elevated mortality risks during crises like pandemics or wars. To correctly model and interpret the excess mortality of vulnerabl...
To perform a quantitative and qualitative analysis of spin bias in randomized clinical trials (RCTs) focusing on botulinum toxin (BTX-A) for managing bruxism.
Missing data are common in longitudinal studies. Multiple imputation (MI) is widely used to handle missing data. However, most of the MI methods assume various missing data types as missing at random (MAR) in ...
Restricted mean survival time (RMST) quantifies survival benefits in single-endpoint analysis, while restricted mean time lost (RMTL) measures event-related time loss in competing risks settings. Both provide ...
Diverse populations are more exposed to life course influences on adverse ageing, including brain ageing. Research into dementia in the United Kingdom inadvertently lacks diversity. Therefore, there is a need ...
REFRACT is a randomised trial aimed at rapidly evaluating multiple novel therapies against standard treatment for relapsed or refractory follicular lymphoma (rrFL) using a minimal number of patients. To this e...
The cluster randomised trial (CRT) design is increasingly used to evaluate the impact of school-based interventions for improving social-emotional functioning outcomes in pupils. Good knowledge is required on ...
Choice of survey administration features in surveys mapping population health may influence the participation and the generalizability of the results. This randomized study aimed to investigate whether three d...
There has been extensive debate about the role of social media and smartphone use in youth mental health and self-harm. Research to date lacks sufficient detail to determine the mechanisms underpinning any ass...
Pregnancy and birth cohort studies are essential for studying the social and biological determinants of human health, yet racial and ethnic minority populations are underrepresented due to low recruitment and ...
Large language models (LLMs) like ChatGPT showed great potential in aiding medical research. A heavy workload in filtering records is needed during the research process of evidence-based medicine, especially m...
Self-report methods are widely used to assess energy intake but are prone to measurement errors. We aimed to identify under-reported, over-reported, and plausible self-reported energy intake by dietary recalls...
Rare events data have proven difficult to explain and predict. Standard statistical procedures can sharply underestimate the probability of rare events, such as intravenous immune globulin therapy (IVIg) for b...
The aim of equality, equity, diversity, and inclusion (EDI) is to ensure fair treatment, equal opportunities, equitable outcomes, and representation. The NIHR Research Design Service (RDS) EDI toolkit (
Ecological analysis utilizes group-level aggregate measures to investigate the complex relationships between individuals or groups and their environment. Despite its extensive applications across various disci...
Machine learning models have been employed to predict COVID-19 infections and mortality, but many models were built on training and testing sets from different periods. The purpose of this study is to investig...
When conducting network meta-analysis (NMA), researchers need to make several methodological and analytical decisions, which can influence the results of NMAs. Our objective was to evaluate the impact of diffe...
Parameter estimation using regression methods plays a vital role in medical research. Often a non-linear transformation of a regression parameter is preferred for its more intuitive interpretation. Important e...
Hepatitis C virus (HCV) has become a serious global public health issue. Existing study has confirmed the potential role of internet search data in the prediction of infectious diseases. This study aims to exp...
The degrees to which a factor is necessary or sufficient for an event have been proposed as generalizations of attributable risk based on simple functions of unconditional and conditional event probabilities. ...
Expert panels are often used as a reference standard when no gold standard is available in diagnostic test accuracy research. It is often unclear what study and expert panel characteristics produce the best es...
The original article was published in BMC Medical Research Methodology 2024 24:129
Although randomized controlled trials are the gold standard design for cause-effect analysis, high costs and challenges around practicability, feasibility, and ethics may limit their use. In such situations, c...
A simulation study was performed to visually demonstrate the problems with repeated measures ANOVA (RMA) and t-tests (TT) compared to linear mixed effects (LME), covariance pattern (CP) or generalized estimating ...
The win ratio has been widely used in the analysis of hierarchical composite endpoints, which prioritize critical outcomes such as mortality over nonfatal, secondary events. Although a regression framework exi...
Trial sequential methods have been introduced to address issues related to increased likelihood of incorrectly rejecting the null hypothesis in meta-analyses due to repeated significance testing. Between-study...
Compositional data comprise the parts of a ‘whole’ (or ‘total’), which sum to that ‘whole’. The ‘whole’ may vary between units of analyses, or it may be fixed (constant). For example, total energy intake (a va...
Methods that enable early outbreak detection represent powerful tools in epidemiological surveillance, allowing adequate planning and timely response to disease surges. Syndromic surveillance data collected fr...
Segmented regression, a common model for interrupted time series (ITS) analysis, primarily utilizes two equation parametrizations. Interpretations of coefficients vary between the two segmented regression para...
Multistate survival models (MSMs) are widely used in the medical field of clinical studies. For example, in type 2 diabetes mellitus (T2D), these models can be applied to describe progression in T2D by predefi...
The concurrent multiple-intervention stepped wedge design (M-SWD) is one of the most widely used variants of the SWD. We aimed to conduct power analysis for concurrent balanced (equal number of clusters in int...
Unmeasured confounders pose challenges when observational data are analysed in comparative effectiveness studies. Integrating high-dimensional administrative claims data may help adjust for unmeasured confound...
The Matters Arising to this article has been published in BMC Medical Research Methodology 2025 25:93
The Research article to this article has been published in BMC Medical Research Methodology 2020 20:79
The Matters Arising to this article has been published in BMC Medical Research Methodology 2025 25:94
Clustered data arise when observations are correlated within a group or sampling unit and frequently arise in epidemiology, social sciences, education, linguistics, econometrics, and medicine. Given growing in...
Randomisation controlled trial are the gold standard for causal inference, however the rapidly increasing development of new treatments and the movement towards personalised medicine mean there is a need to me...
Systematic Reviews (SRs) rigorously synthesize findings on a theme, but some articles with this design are redundant due to errors and conflicts. Meta-research aims to rigorously analyze research, assessing SR...
Traditional statistical methods assume normally distributed continuous variables, making them unsuitable for analysis of prevalence proportions. To address this problem, two commonly utilized variance-stabiliz...
Public engagement with science (PES) initiatives in health research that use big data to analyze social inequalities in health requires strategies and methods adapted to the contexts of countries in the Global...
The use of Expert Opinion (EO) in clinical guidelines is highly variable and lacks standardization, leading to ongoing controversy. A clear and universally accepted definition of EO is also lacking. To date, n...
Meta-analysis is a useful method for combining evidence from multiple studies to detect treatment effects that could perhaps not be identified in a single study. While traditionally meta-analysis has assumed t...
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