Evidence map›Paper›PMID 32896901›Full record

ArticleBiometrics2021

Scalable and robust latent trajectory class analysis using artificial likelihood.

Kari R Hart, Teng Fei, John J Hanfelt

Open access · greenAbstract read
In one paragraph

Article in Biometrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 35% of its field
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

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
  2. 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

3 authors at 2 institutions in 1 country.

Kari R HartThe Peddie School, Hightstown, New Jersey.
Teng FeiDepartment of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia.ORCID 0000-0001-7888-1715
John J HanfeltDepartment of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia.ORCID 0000-0002-8488-6771
Emory University · USPeddie School · US

Funding

NATIONAL ALZHEIMERS COORDINATING CENTER (NACC)U01AG016976 · NIA · UNIVERSITY OF WASHINGTON · PI KUKULL, WALTER ANTHONY · 1999 to 2020
$72.8M
THERAPEUTIC EFFECTS OF INTRA-NASAL INSULIN DETEMIRP50AG005136 · NIA · UNIVERSITY OF WASHINGTON · PI BUCHWALD, DEDRA S · 1985 to 2019
$57.2M
VIRUS-INDUCED BRAIN PATHOLOGYP50AG005131 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI GALASKO, DOUGLAS R · 1985 to 2018
$55.4M
WASHINGTON UNIVERSITY ALZHEIMERS DISEASE RESEARCH CENTERP50AG005681 · NIA · WASHINGTON UNIVERSITY · PI MORRIS, JOHN · 1985 to 2019
$52.1M
SUPPLEMENT TO RUSH ALZHEIMERS DISEASE CENTER COREP30AG010161 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 1991 to 2020
$49.1M
Satellite Diagnostic and Treatment Clinic CoreP50AG008702 · NIA · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI DE JAGER, PHILIP L · 1989 to 2019
$46.3M
National Alzheimer's Coordinating CenterU24AG072122 · NIA · UNIVERSITY OF WASHINGTON · PI STEPHENS, KARI A · 2021 to 2025
$45.8M
TREATMENT OF DEPRESSION IN ALZHEIMER'S DISEASEP50AG005133 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BECKER, JAMES T. · 1985 to 2019
$43.0M
THE ROLE OF ADVANCED CAA IN ALZHEIMER'S DEMENTIAP50AG005134 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI GOMEZ-ISLA, TERESA · 1985 to 2018
$42.1M
VASCULAR RISK AND COGNITIVE STATUS IN A LATINO POPULATIONP50AG005142 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI BRASKIE, MEREDITH NICOLE · 1985 to 2019
$41.0M
VESICULAR LOCALIZATION AND FUNCTION OF PRESENILIN 1 FRAGMENTP50AG005138 · NIA · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI SEWELL, MARGARET · 1985 to 2019
$37.9M
'T V ASSESSMENT - MEMORY DISORDERED PATIENTS'P50AG005146 · NIA · JOHNS HOPKINS UNIVERSITY · PI TRONCOSO, JUAN · 1985 to 2019
$37.6M
NIA NIH HHS P30 AG008017NIA NIH HHS P30 AG008051NIA NIH HHS P30 AG010124NIA NIH HHS P30 AG010129NIA NIH HHS P30 AG010133NIA NIH HHS P30 AG010161NIA NIH HHS P30 AG012300NIA NIH HHS P30 AG013846NIA NIH HHS P30 AG013854NIA NIH HHS P30 AG019610NIA NIH HHS P30 AG028383NIA NIH HHS P30 AG035982NIA NIH HHS P30 AG049638NIA NIH HHS P30 AG053760NIA NIH HHS P30 AG066444NIA NIH HHS P30 AG066511NIA NIH HHS P30 AG066518NIA NIH HHS P30 AG072977NIA NIH HHS P50 AG005131NIA NIH HHS P50 AG005133NIA NIH HHS P50 AG005134NIA NIH HHS P50 AG005136NIA NIH HHS P50 AG005138NIA NIH HHS P50 AG005142NIA NIH HHS P50 AG005146NIA NIH HHS P50 AG005681NIA NIH HHS P50 AG008702NIA NIH HHS P50 AG016573NIA NIH HHS P50 AG016574NIA NIH HHS P50 AG023501NIA NIH HHS P50 AG025688NIA NIH HHS P50 AG033514NIA NIH HHS P50 AG047266NIA NIH HHS P50 AG047270NIA NIH HHS P50 AG047366NIA NIH HHS R01 AG055634NIA NIH HHS U01 AG016976NIA NIH HHS U24 AG072122
6 · The paper itself

Abstract

Latent trajectory class analysis is a powerful technique to elucidate the structure underlying population heterogeneity. The standard approach relies on fully parametric modeling and is computationally impractical when the data include a large collection of non-Gaussian longitudinal features. We introduce a new approach, the first based on artificial likelihood concepts, that avoids undue modeling assumptions and is computationally tractable. We show that this new method provides reliable estimates of the underlying population structure and is from 20 to 200 times faster than conventional methods when the longitudinal features are non-Gaussian. We apply the approach to explore subgroups among research participants in the early stages of neurodegeneration.

Indexed as

Models, StatisticalResearch DesignHumansLatent Class AnalysisLongitudinal StudiesProbabilityfinite mixture modelgeneralized estimating equationlongitudinal dataprojected likelihoodquasi-likelihood

Identifiers

PMID32896901
PMCPMC7937764
OpenAlexW3083952407

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.