Evidence map›Paper›PMID 41684276›Full record

ArticleStatistics in medicine2026

A Functional Joint Model for Survival and Multivariate Sparse Functional Data in Multi-Cohort Alzheimer's Disease Study.

Wenyi Wang, Luo Xiao, Ruonan Li, Sheng Luo, Alzheimer's Disease Neuroimaging Initiative

Abstract read
In one paragraph

Article in Statistics in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Wenyi WangDepartment of Statistics, North Carolina State University, Raleigh, North Carolina, USA.ORCID https://orcid.org/0009-0002-1154-636X
Luo XiaoDepartment of Statistics, North Carolina State University, Raleigh, North Carolina, USA.
Ruonan LiDepartment of Statistics, North Carolina State University, Raleigh, North Carolina, USA.ORCID https://orcid.org/0000-0001-7293-9779
Sheng LuoDepartment of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, USA.ORCID https://orcid.org/0000-0003-4214-5809
Alzheimer's Disease Neuroimaging Initiative

Funding

Resource Core 3 - Metabolomics CoreP30AG028716 · NIA · DUKE UNIVERSITY · PI CATHLEEN S COLON-EMERIC, Susan Nicole Hastings · 2006 to 2026
$24.6M
Research Education Component CoreP30AG072958 · NIA · DUKE UNIVERSITY · PI Heather E. Whitson · 2021 to 2026
$24.1M
Integrative modeling and dynamic prediction of Alzheimer's diseaseR01AG064803 · NIA · DUKE UNIVERSITY · PI LUO, SHENG · 2020 to 2024
$2.3M
Comprehensive White-matter Microstructure-informed Analytical Methods to Elucidate Neurobiological Mechanisms of Sports-related Concussion (SRC)R01NS112303 · NINDS · INDIANA UNIVERSITY INDIANAPOLIS · PI HAREZLAK, JAROSLAW, WU, YU-CHIEN · 2020 to 2024
$2.3M
NIA NIH HHS P30 AG028716NIA NIH HHS P30AG028716NIA NIH HHS P30 AG072958NIA NIH HHS P30AG072958NIA NIH HHS R01 AG064803NIA NIH HHS R01AG064803NINDS NIH HHS R01 NS112303NINDS NIH HHS R01NS112303
6 · The paper itself

Abstract

We develop an integrative joint model for multivariate sparse functional and survival data to analyze Alzheimer's disease (AD) across multiple studies. To address missing-by-design outcomes in multi-cohort studies, our approach extends the multivariate functional mixed model (MFMM), which integrates longitudinal outcomes to extract shared disease progression trajectories and links these outcomes to time-to-event data through a parsimonious survival model. This framework balances flexibility and interpretability by modeling shared progression trajectories while accommodating cohort-specific mean functions and survival parameters. For efficient estimation, we incorporate penalized splines into an EM algorithm. Application to three AD cohorts demonstrates the model's ability to capture disease trajectories and account for inter-cohort variability. Simulation studies confirm its robustness and accuracy, highlighting its value in advancing the understanding of AD progression and supporting clinical decision-making in multi-cohort settings.

Indexed as

Alzheimer DiseaseModels, StatisticalAlgorithmsCohort StudiesComputer SimulationDisease ProgressionHumansLongitudinal StudiesMultivariate AnalysisSurvival AnalysisEM algorithmfunctional datamultivariate longitudinal datapenalized splines

Identifiers

PMID41684276
PMCPMC12902813

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.