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In an inter-rater agreement study, if two raters tend to rate considering different aspects of the subject of interest or have different experience levels, a grey zone occurs among the levels of a square conti...
The spread of severe acute respiratory syndrome coronavirus-2 has suspended many non-COVID-19 related research activities. Where restarting research activities is permitted, investigators need to evaluate the ...
Staquet et al. and Brenner both developed correction methods to estimate the sensitivity and specificity of a binary-response index test when the reference standard is imperfect and its sensitivity and specifi...
Cancer patients’ prognoses are complicated by comorbidities. Prognostic prediction models with inappropriate comorbidity adjustments yield biased survival estimates. However, an appropriate claims-based comorb...
Linear mixed models (LMM) are a common approach to analyzing data from cluster randomized trials (CRTs). Inference on parameters can be performed via Wald tests or likelihood ratio tests (LRT), but both approa...
The best way to calculate statistics from medical data is to use the data of individual patients. In some settings, this data is difficult to obtain due to privacy restrictions. In Germany, for example, it is ...
No standards exist for the handling and reporting of data quality in health research. This work introduces a data quality framework for observational health research data collections with supporting software i...
In case-control studies most algorithms allow the controls to be sampled several times, which is not always optimal. If many controls are available and adjustment for several covariates is necessary, matching ...
Recruitment of general practitioners (GPs) and their patients is reported as one of the most challenging steps when undertaking primary care research. The present paper describes the recruitment process of a c...
The 2018 World Health Organization HIV guidelines were based on the results of a network meta-analysis (NMA) of published trials. This study employed individual patient-level data (IPD) and aggregate data (AgD...
Randomized controlled trials in orthopaedics are powered to mainly find large effect sizes. A possible discrepancy between the estimated and the real mean difference is a challenge for statistical inference ba...
Interrupted time series analysis is increasingly used to evaluate the impact of large-scale health interventions. While segmented regression is a common approach, it is not always adequate, especially in the p...
Published research informs international healthcare, yet only a few studies have assessed the representation of authors, editors, and research from developing countries in biomedical journals.
Estimation that employs instrumental variables (IV) can reduce or eliminate bias due to confounding. In observational studies, instruments result from natural experiments such as the effect of clinician prefer...
Cancer treatment is increasingly dependent on biomarkers for prognostication and treatment selection. Potential biomarkers are frequently evaluated in prospective-retrospective studies in which biomarkers are ...
Recruiting asymptomatic participants with early disease stages into studies is challenging and only little is known about facilitators and barriers to screening and recruitment of study participants. Thus we a...
Beginning in 2019, stepped-wedge designs (SWDs) were being used in the investigation of interventions to reduce opioid-related deaths in communities across the United States. However, these interventions are c...
Royston-Parmar flexible parametric survival models (FPMs) can be fitted on either the cause-specific hazards or cumulative incidence scale in the presence of competing risks. An advantage of modelling within t...
Systematic Reviews (SRs) can build the groundwork for evidence-based health care decision-making. A sound methodological quality of SRs is crucial. AMSTAR (A Measurement Tool to Assess Systematic Reviews) is a...
Outbreaks of infectious diseases generate outbreaks of scientific evidence. In 2016 epidemics of Zika virus emerged, and in 2020, a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a p...
Population segmentation permits the division of a heterogeneous population into relatively homogenous subgroups. This scoping review aims to summarize the clinical applications of data driven and expert driven...
We propose a new measure of treatment effect based on the expected reduction in the number of patients to treat (RNT) which is defined as the difference of the reciprocals of clinical measures of interest betw...
Waist circumference is becoming recognized as a useful predictor of health risks in clinical research. However, clinical datasets tend to lack this measurement and self-reported values tend to be inaccurate. P...
This study investigated the ArmA-TH sub-scale measurement properties based on item response theory using the Rasch model.
The results of clinical trials should be assessed for both statistical significance and importance of observed effects to patients. Minimal important difference (MID) is a threshold denoting a difference that ...
Racial and ethnic minorities are often underrepresented in clinical trials, threatening the generalizability of trial results. Several factors may contribute to underrepresentation of minorities in clinical tr...
The case-crossover design is suited to medication safety studies but is vulnerable to exposure misclassification. Using the example of tricyclic antidepressants and the risk of hip fracture, we present a data ...
The COVID-19 pandemic continues to rage on, and clinical research has been promoted worldwide. We aimed to assess the clinical and methodological characteristics of treatment clinical trials that have been set...
Clinical interpretation of changes measured on a scale is dependent on knowing the minimum clinically important difference (MCID) for that scale: the threshold above which clinicians, patients, and researchers...
To validate e-norms methodology in establishing a reference range for body mass index measures. A new method, the extrapolated norms (e-norms) method of determining normal ranges for biological variables is ea...
Dynamic treatment regimens (DTRs) formalise the multi-stage and dynamic decision problems that clinicians often face when treating chronic or progressive medical conditions. Compared to randomised controlled t...
Data collection is the most critical stage in any population health study and correctly implementing fieldwork enhances the quality of collected information. However, even the most carefully planned large-scal...
Most health surveys have experienced a decline in response rates. A structured approach to evaluate whether a decreasing - and potentially more selective - response over time biased estimated trends in health ...
Time-to-event data that is subject to interval censoring is common in the practice of medical research and versatile statistical methods for estimating associations in such settings have been limited. For righ...
Randomized controlled trials are considered the gold standard to evaluate causal associations, whereas assessing causality in observational studies is challenging.
Ensemble modeling aims to boost the forecasting performance by systematically integrating the predictive accuracy across individual models. Here we introduce a simple-yet-powerful ensemble methodology for fore...
To evaluate the completeness of reporting abstracts of systematic reviews (SRs) before and after the publication of the PRISMA-A checklist in 2013 and to assess if an association exists between abstract charac...
Natural or quasi experiments are appealing for public health research because they enable the evaluation of events or interventions that are difficult or impossible to manipulate experimentally, such as many p...
Scale-up BP was a quasi-experimental implementation study, following a successful randomised controlled trial of the roll-out of telemonitoring in primary care across Lothian, Scotland. Our primary objective w...
In infectious disease transmission dynamics, the high heterogeneity in individual infectiousness indicates that few index cases generate large numbers of secondary cases, which is commonly known as superspread...
Statistical methods for modeling longitudinal and time-to-event data has received much attention in medical research and is becoming increasingly useful. In clinical studies, such as cancer and AIDS, longitudi...
COVID-19 has led to the adoption of unprecedented mitigation measures which could trigger many unintended consequences. These unintended consequences can be far-reaching and just as important as the intended o...
Ethnographic approaches offer a method and a way of thinking about implementation. This manuscript applies a specific case study method to describe the impact of the longitudinal interplay between implementati...
Over 2 billion people suffer from vision impairment or blindness globally, and access to validated visual measurement tools in imperative in accurately describing and managing the burden of eye disease. The pr...
Many respondent-driven sampling (RDS) methodologies have been employed to investigate hard-to-reach populations; however, these methodologies present some limits. We describe a minimally investigated RDS metho...
Early pregnancy weights are needed to quantify gestational weight gain accurately. Different methods have been used in previous studies to impute early-pregnancy weights. However, no studies have systematicall...
The U.S. lacks a stroke surveillance system. This study develops a method to transform an existing registry into a nationally representative database to evaluate acute ischemic stroke care quality.
Trials of novel agents are required to improve the care of patients with rare diseases, but trial feasibility may be uncertain due to concerns over insufficient patient numbers. We aimed to determine the size ...
The use of individual patient data (IPD) in network meta-analyses (NMA) is rapidly growing. This study aimed to determine, through simulations, the impact of select factors on the validity and precision of NMA...
Audit and feedback (A&F) interventions are one of the most common approaches for implementing evidence-based practices. A key barrier to more effective A&F interventions is the lack of a theory-guided approach...
2022 Citation Impact
4.0 - 2-year Impact Factor
7.0 - 5-year Impact Factor
2.055 - SNIP (Source Normalized Impact per Paper)
1.778 - SJR (SCImago Journal Rank)
2023 Speed
40 days submission to first editorial decision for all manuscripts (Median)
210 days submission to accept (Median)
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