Evidence map›Paper›PMID 40969378›Full record

ArticleBiostatistics & epidemiology2025

Finite Markov chains with absorbing states and mis-specified random effects: application to cognitive data.

Pei Wang, Changrui Liu, Jiyeon Park, Suzanne L Tyas, Richard J Kryscio

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In one paragraph

Article in Biostatistics & epidemiology, 2025. 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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0citing papers 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

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.

Pei WangDepartment of Applied Statistics and Operations Research, Bowling Green State University, Bowling Green, Ohio, USA.
Changrui LiuDepartment of Mathematics and Statistics, University of Tennessee at Martin, Martin, Tennessee, USA.
Jiyeon ParkDepartment of Statistics, University of Kentucky, Lexington, Kentucky, USA.
Suzanne L TyasSchool of Public Health Sciences, University of Waterloo, Waterloo, Ontario, Canada.
Richard J KryscioDepartment of Statistics, University of Kentucky, Lexington, Kentucky, USA.

Funding

Kentucky Center for Clinical and Translational ScienceUL1TR001998 · NCATS · UNIVERSITY OF KENTUCKY · PI HARTMANN, KATHERINE E, KERN, PHILIP A · 2016 to 2025
$34.2M
University of Kentucky Alzheimer's Disease Research CenterP30AG072946 · NIA · UNIVERSITY OF KENTUCKY · PI LINDA J VAN ELDIK · 2021 to 2026
$23.5M
Role of impaired cognitive states & risk factors in conversion to mixed dementiasR01AG038651 · NIA · UNIVERSITY OF KENTUCKY · PI ABNER, ERIN, KRYSCIO, RICHARD J. · 2011 to 2023
$6.1M
Genomic Architecture of a Key Alzheimer's Disease Mimic: CARTSR56AG057191 · NIA · UNIVERSITY OF KENTUCKY · PI FARDO, DAVID WILLIAM · 2019 to 2020
$1.1M
NCATS NIH HHS UL1 TR001998NIA NIH HHS P30 AG072946NIA NIH HHS R01 AG038651NIA NIH HHS R56 AG057191
6 · The paper itself

Abstract

Finite Markov chains with absorbing states are valuable tools for analyzing longitudinal data with categorical responses. However, defining the one-step transition probabilities in terms of fixed and random effects presents challenges due to the large number of unknown parameters involved. To address this, we employ a marginal model to estimate the fixed effects across various choices of the distribution governing the random effects. Subsequently, we utilize an

Indexed as

absorbing statefinite Markov chainsh-likelihoodmis-specificationrandom effect

Identifiers

PMID40969378
PMCPMC12442839

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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.