ArticleInternational journal of environmental research and public health2017
Extensions to Multivariate Space Time Mixture Modeling of Small Area Cancer Data.
Article in International journal of environmental research and public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.
What it found
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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.
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Who cites it
6 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A Systematic Review of Joint Spatial and Spatiotemporal Models in Health Research.International journal of environmental research and public health · 2023Pooled it
- A systematic review of Bayesian spatial-temporal models on cancer incidence and mortality.International journal of public health · 2020Pooled it
- Article
- Identifying hotspots of cardiometabolic outcomes based on a Bayesian approach: The example of Chile.PloS one · 2020Article
- Trends in Colorectal Cancer Incidence and Survival in Iowa SEER Data: The Timing of It All.Clinical colorectal cancer · 2019Article
- Smoothed Temporal Atlases of Age-Gender All-Cause Mortality in South Africa.International journal of environmental research and public health · 2017Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Oral cavity and pharynx cancer, even when considered together, is a fairly rare disease. Implementation of multivariate modeling with lung and bronchus cancer, as well as melanoma cancer of the skin, could lead to better inference for oral cavity and pharynx cancer. The multivariate structure of these models is accomplished via the use of shared random effects, as well as other multivariate prior distributions. The results in this paper indicate that care should be taken when executing these types of models, and that multivariate mixture models may not always be the ideal option, depending on the data of interest.
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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.