Anonymization has the potential to foster the sharing of medical data. State-of-the-art methods use mathematical models to modify data to reduce privacy risks. However, the degree of protection must b...
The COVID-19 pandemic has revealed significant challenges in disease forecasting and in developing a public health response, emphasizing the need to manage missing data from various sources in making ...
We aimed to show how handling missing data can affect estimates of the COVID-19 incidence rate (CIR) in different pandemic situations....
This study used data from the COVID-19/SARS-CoV-2 surveillance system at the National Institute of Hygiene and Epidemiology, Vietnam. We separated the available data set into 3 distinct periods: zero ...
Our study examined missing data imputation performance across 3 study time periods: zero COVID-19 (n=3149), transition (n=1290), and new normal (n=9288). Imputation analyses showed that K-nearest neig...
Our study emphasizes the importance of understanding that the specific imputation method used by investigators should be tailored to the specific epidemiological context and data collection environmen...
Valid inference can be drawn from a random-effects model for repeated measures that are incomplete if whether the data are missing or not, known as missingness, is independent of the missing data. Dat...
Biological entities are inherently dynamic. As such, various ecological disciplines use mathematical models to describe temporal evolution. Typically, growth curves are modelled as sigmoids, with the ...
Missing data is a pervasive problem in longitudinal data analysis. Several single-imputation (SI) and multiple-imputation (MI) approaches have been proposed to address this issue. In this study, for t...
Using different simulation scenarios derived from a real data set, we compared the performance of cross, trajectory mean, interpolation, copy-mean, and MI methods (27 approaches) to impute missing lon...
The longitudinal regression tree algorithm outperformed based on the criteria such as MSE, RMSE, and MAD than the linear mixed-effects model (LMM) for analyzing the TCGS and simulated data using the m...
Both SI and MI approaches performed better using the longitudinal regression tree algorithm compared with the parametric longitudinal models. Based on the results from both the real and simulated data...
In randomised controlled trials with efficacy-related primary outcomes, adverse events are collected to monitor potential intervention harms. The analysis of adverse event data is challenging, due to ...
We conducted a methodological scoping review of the literature to identify all existing methods using structures within the data to detect signals for adverse reactions in a trial. Embase, MEDLINE, Sc...
We identified 18 different methods from 14 sources. These were categorised as either Bayesian approaches (n=11), which flagged events based on posterior estimates of treatment effects, or error contro...
We found a large number of analysis methods that use the group structures of adverse events. Continuous methodological developments in this area highlight the growing awareness that better practices a...
The FICUS trial is a cluster-randomized superiority trial to determine the effectiveness of a nurse-led, interprofessional family support intervention (FSI) on the quality of care, family management a...
Ultrasound-guided supraclavicular block (UGSCB) is an emerging technique gaining interest amongst emergency physicians that provides regional anaesthesia to the upper limb to tolerate painful procedur...
SUPERB (SUPraclavicular block for Emergency Reduction versus Bier block) is a prospective open-label non-inferiority randomised controlled trial comparing the effectiveness of UGSCB versus BB for clos...
Primary outcome analysis will be performed using both the intention-to-treat and per-protocol populations. The between-group difference in maximum pain intensity will be assessed using linear regressi...
SUPERB is the first randomised controlled trial to investigate the effectiveness and safety of UGSCB in the ED. The trial has the potential to demonstrate that UGSCB is an alternative safe and effecti...
Globally, violence against children poses substantial health and economic challenges, with estimated costs nearing USD 7 trillion. This prompts the urgent call for effective evidence-based interventio...
This study is a pragmatic, two-arm, cluster-randomised trial in Mwanza, Tanzania's urban and peri-urban areas. Assessments are set for baseline, 1 month post-intervention, and 12 months post-intervent...
Preparations for the trial began in December 2022, including community mobilisation and sensitisation. Rolling recruitment, baseline data collection, and implementation onboarding took place between A...
The trial was registered on the Open Science Framework on 14 March 2023: https://doi.org/10.17605/OSF.IO/T9FXZ . The trial protocol was published in Trials 25, 119 (2024): Baerecke, L., Ornellas, A., ...
Neonatal mortality in India has fallen steadily and was estimated to be 24 per 1000 live births in the year 2017. However, neonatal mortality remains high in rural parts of the country. The Community ...
The CHAMPION2 trial forms one part of a cluster-randomised controlled trial with villages (clusters) randomised to receive either a health (CHAMPION2) or education (STRIPES2) intervention. Villages re...
This update to the published trial protocol gives a detailed plan for the statistical analysis of the CHAMPION2 trial....
Registry of India: CTRI/2019/05/019296. Registered on 23 May 2019. https://ctri.nic.in/Clinicaltrials/pmaindet2.php?EncHid=MzExOTg=&Enc=&userName=champion2....
