Evidence map›Paper›PMID 33368533›Full record

ArticleStatistics in medicine2021

A longitudinal Bayesian mixed effects model with hurdle Conway-Maxwell-Poisson distribution.

Tong Kang, Jeremy Gaskins, Steven Levy, Somnath Datta

Abstract read
In one paragraph

Article in Statistics in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Tong KangDepartment of Biostatistics, University of Florida, Gainesville, Florida, USA.
Jeremy GaskinsDepartment of Bioinformatics and Biostatistics, University of Louisville, Louisville, Kentucky, USA.
Steven LevyDepartment of Preventive and Community Dentistry, University of Iowa, Iowa City, Iowa, USA.
Somnath DattaDepartment of Biostatistics, University of Florida, Gainesville, Florida, USA.ORCID 0000-0003-4381-1842

Funding

A Novel Analysis Plan for the Caries and Fluorosis Data from the Iowa Fluoride StudyR03DE026757 · NIDCR · UNIVERSITY OF FLORIDA · PI DATTA, SOMNATH · 2018 to 2019
$332k
NIDCR NIH HHS R03 DE026757
6 · The paper itself

Abstract

Dental caries (i.e., cavities) is one of the most common chronic childhood diseases and may continue to progress throughout a person's lifetime. The Iowa Fluoride Study (IFS) was designed to investigate the effects of various fluoride, dietary and nondietary factors on the progression of dental caries among a cohort of Iowa school children. We develop a mixed effects model to perform a comprehensive analysis of the longitudinal clustered data of IFS at ages 5, 9, 13, and 17. We combine a Bayesian hurdle framework with the Conway-Maxwell-Poisson regression model, which can account for both excessive zeros and various levels of dispersion. A hierarchical shrinkage prior distribution is used to share the temporal information for predictors in the fixed-effects model. The dependence among teeth of each individual child is modeled through a sparse covariance structure of the random effects across time. Moreover, we obtain the parameter estimates and credible intervals from a Gibbs sampler. Simulation studies are conducted to assess the accuracy and effectiveness of our statistical methodology. The results of this article provide novel tools to statistical practitioners and offer fresh insights to dental researchers on effects of various risk and protective factors on caries progression.

Indexed as

Dental CariesAdolescentBayes TheoremChildChild, PreschoolComputer SimulationHumansIowaPoisson DistributionBayesian analysisConway-Maxwell-Poisson distributionHurdle modellongitudinal datamixed effects model

Identifiers

PMID33368533
PMCPMC9167575

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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.