Evidence map›Paper›PMID 23123680›Full record

ArticleNeuroImage2013

Statistical analysis of longitudinal neuroimage data with Linear Mixed Effects models.

Jorge L Bernal-Rusiel, Douglas N Greve, Martin Reuter, Bruce Fischl, Mert R Sabuncu, Alzheimer's Disease Neuroimaging Initiative

Erratum issuedOpen access · greenAbstract read
In one paragraph

Article in NeuroImage, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 211 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
211citing papers in PubMed, 2 pooled it
7.4field-weighted citation impact, top 2% 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

211 citing papers in PubMed, 2 syntheses or guidelines pooled it, 375 citations in OpenAlex.

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151 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

6 authors at 4 institutions in 1 country.

Jorge L Bernal-RusielAthinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School/Massachusetts General Hospital, Charlestown, MA, USA.
Douglas N GreveAthinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School/Massachusetts General Hospital, Charlestown, MA, USA.
Martin ReuterAthinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School/Massachusetts General Hospital, Charlestown, MA, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Bruce FischlAthinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School/Massachusetts General Hospital, Charlestown, MA, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
Mert R SabuncuAthinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School/Massachusetts General Hospital, Charlestown, MA, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA. Electronic address: msabuncu@nmr.mgh.harvard.edu.
Alzheimer's Disease Neuroimaging Initiative
Harvard University · USAthinoula A. Martinos Center for Biomedical Imaging · USMassachusetts General Hospital · USMassachusetts Institute of Technology · US

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
The VETSA Longitudinal MRI Twin Study of AgingR01AG022381 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KREMEN, WILLIAM S. · 2003 to 2019
$22.3M
ULTRAHIGH FIELD TECHNOLOGY FOR FUNCTIONAL IMAGINGP41RR014075 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 1999 to 2011
$16.4M
EPIDEMIOLOGY OF DEMENTIA IN THE FRAMINGHAM STUDYR01AG008122 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI AU, RHODA, SESHADRI, SUDHA · 1989 to 2015
$14.4M
MRI, Genetics &Cognitive Precursors of AD &DementiaR01AG016495 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI AU, RHODA · 1999 to 2016
$12.5M
The Human Connectome Project (HCP)U01MH093765 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI ROSEN, BRUCE R · 2010 to 2014
$12.1M
Neuroimaging Biomarkers for disease-modyfying therapies in Hintington's diseaseP01NS058793 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI HERSCH, STEVEN M · 2008 to 2012
$6.6M
Prospective Neuroimaging in Huntington's DiseaseR01NS042861 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI ROSAS, HERMINIA DIANA · 2003 to 2013
$5.6M
Harvard Clinical and Translational Science Center (KL2)KL2RR025757 · NCRR · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2008 to 2011
$4.1M
Tools for Analyzing Cortical Structure and ConnectivityR01NS052585 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 2006 to 2010
$2.5M
Longitudinal Neuroimaging and Cognitive Study of HIV-Infected ChildrenR01HD071664 · NICHD · MASSACHUSETTS GENERAL HOSPITAL · PI LAUGHTON, BARBARA, MEINTJES, ERNESTA MARIA · 2011 to 2015
$2.4M
Software Tools for Automated Modeling of White Matter Fascicles from Diffusion MRR01NS070963 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 2011 to 2015
$2.3M
NCCIH NIH HHS RC1 AT005728NCCIH NIH HHS RC1 AT005728-01NCRR NIH HHS 1KL2RR025757-01NCRR NIH HHS 1S10RR019307NCRR NIH HHS 1S10RR023043NCRR NIH HHS 1S10RR023401NCRR NIH HHS KL2 RR025757NCRR NIH HHS P41 RR014075NCRR NIH HHS P41-RR14075NCRR NIH HHS S10 RR019307NCRR NIH HHS S10 RR023043NCRR NIH HHS S10 RR023401NIA NIH HHS 5R01AG008122-22NIA NIH HHS AG022381NIA NIH HHS R01 AG008122NIA NIH HHS R01 AG016495NIA NIH HHS R01 AG022381NIA NIH HHS U01 AG024904NIBIB NIH HHS 1K25EB013649-01NIBIB NIH HHS K25 EB013649NIBIB NIH HHS R01 EB006758NIBIB NIH HHS R01EB006758NICHD NIH HHS R01 HD071664NICHD NIH HHS R01-HD071664NIMH NIH HHS 5U01-MH093765NIMH NIH HHS U01 MH093765NINDS NIH HHS 1R01NS070963NINDS NIH HHS 1R21NS072652-01NINDS NIH HHS 2R01NS042861-06A1NINDS NIH HHS 5P01NS058793-03NINDS NIH HHS P01 NS058793NINDS NIH HHS R01 NS042861NINDS NIH HHS R01 NS052585NINDS NIH HHS R01 NS052585-01NINDS NIH HHS R01 NS070963NINDS NIH HHS R21 NS072652
6 · The paper itself

Abstract

Longitudinal neuroimaging (LNI) studies are rapidly becoming more prevalent and growing in size. Today, no standardized computational tools exist for the analysis of LNI data and widely used methods are sub-optimal for the types of data encountered in real-life studies. Linear Mixed Effects (LME) modeling, a mature approach well known in the statistics community, offers a powerful and versatile framework for analyzing real-life LNI data. This article presents the theory behind LME models, contrasts it with other popular approaches in the context of LNI, and is accompanied with an array of computational tools that will be made freely available through FreeSurfer - a popular Magnetic Resonance Image (MRI) analysis software package. Our core contribution is to provide a quantitative empirical evaluation of the performance of LME and competing alternatives popularly used in prior longitudinal structural MRI studies, namely repeated measures ANOVA and the analysis of annualized longitudinal change measures (e.g. atrophy rate). In our experiments, we analyzed MRI-derived longitudinal hippocampal volume and entorhinal cortex thickness measurements from a public dataset consisting of Alzheimer's patients, subjects with mild cognitive impairment and healthy controls. Our results suggest that the LME approach offers superior statistical power in detecting longitudinal group differences.

Indexed as

Linear ModelsAgedAged, 80 and overAlgorithmsAlzheimer DiseaseBrainCognitive DysfunctionFemaleHumansImage Processing, Computer-AssistedLongitudinal StudiesMagnetic Resonance ImagingMaleMiddle AgedLinear Mixed Effects modelsLongitudinal studiesStatistical analysis

Identifiers

PMID23123680
PMCPMC3586747
OpenAlexW2142864721

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.