ArticleStatistics in medicine2025
A Bayesian Multi-Factorial Design and Analysis for Estimating Combined Effects of Multiple Interventions in a Pragmatic Clinical Trial to Improve Dementia Care.
Article in Statistics in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Bridging the Gap Between the ED and Home: The Community Paramedic-Led Transitions Intervention for Persons Living With Dementia.Journal of the American Geriatrics Society · 2026Article
- Emergency Departments Leading the Transformation of Alzheimer's and Dementia Care.Journal of the American Geriatrics Society · 2026Article
- Nurse-Led Telephonic Care Following Emergency Department Visits for Persons Living With Dementia and Their Care Partners: A Program Description.Journal of the American Geriatrics Society · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Factorial study designs can be important for understanding the effectiveness of interventions when multiple interventions are under investigation. In this design setting, a unit of randomization can be assigned to any combination of interventions. The rationale for taking this kind of approach can vary depending on the specific questions targeted by the research. These questions, in turn, have implications for the way in which the analyses will be conducted. The goal in this paper is to describe how we developed a factorial design along with a Bayesian analytic plan for a large cluster-randomized trial-the Emergency Departments LEading the transformation of Alzheimer's and Dementia care (ED-LEAD) study-focused on improving care for persons living with dementia.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.