Evidence map›Paper›PMID 29748991›Full record

ArticleBiometrical journal. Biometrische Zeitschrift2018

Marginalized zero-inflated Poisson models with missing covariates.

Habtamu K Benecha, John S Preisser, Kimon Divaris, Amy H Herring, Kalyan Das

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biometrical journal. Biometrische Zeitschrift, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

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.

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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Habtamu K BenechaNational Agricultural Statistics Service, USDA, Washington, USA.ORCID 0000-0002-2227-3988
John S PreisserDepartment of Biostatistics, University of North Carolina, Chapel Hill, USA.ORCID 0000-0002-7869-2057
Kimon DivarisDepartment of Pediatric Dentistry, University of North Carolina, Chapel Hill, USA.
Amy H HerringDepartment of Statistical Science, Duke University, Durham, USA.
Kalyan DasDepartment of Statistics, University of Calcutta, Kolkata, India.

Funding

Biostatstics for Research in Environmental HealthT32ES007018 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Stephanie Engel, Rebecca Fry · 1985 to 2026
$31.3M
Research Services CoreP2CHD050924 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAREN B GUZZO · 2015 to 2026
$9.6M
NICHD NIH HHS P2C HD050924NIEHS NIH HHS T32 ES007018
6 · The paper itself

Abstract

Unlike zero-inflated Poisson regression, marginalized zero-inflated Poisson (MZIP) models for counts with excess zeros provide estimates with direct interpretations for the overall effects of covariates on the marginal mean. In the presence of missing covariates, MZIP and many other count data models are ordinarily fitted using complete case analysis methods due to lack of appropriate statistical methods and software. This article presents an estimation method for MZIP models with missing covariates. The method, which is applicable to other missing data problems, is illustrated and compared with complete case analysis by using simulations and dental data on the caries preventive effects of a school-based fluoride mouthrinse program.

Indexed as

Models, StatisticalAnalysis of VarianceBiometryChildDental CariesFluoridesHumansMonte Carlo MethodMouthwashesPoisson DistributionSchoolsFluoridesMouthwashesmarginalized modelsmissing at randommissing dataMonte Carlo EMzero-inflation

Identifiers

PMID29748991
PMCPMC6453121

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Registered trials

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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.