Literature DB >> 22523185

The analysis of multivariate longitudinal data: a review.

Geert Verbeke1, Steffen Fieuws, Geert Molenberghs, Marie Davidian.   

Abstract

Longitudinal experiments often involve multiple outcomes measured repeatedly within a set of study participants. While many questions can be answered by modeling the various outcomes separately, some questions can only be answered in a joint analysis of all of them. In this article, we will present a review of the many approaches proposed in the statistical literature. Four main model families will be presented, discussed and compared. Focus will be on presenting advantages and disadvantages of the different models rather than on the mathematical or computational details.

Entities:  

Keywords:  Mixed models; conditional models; latent variables; marginal models; random effects; shared parameters

Mesh:

Year:  2012        PMID: 22523185      PMCID: PMC3404254          DOI: 10.1177/0962280212445834

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  32 in total

1.  Latent variable models for longitudinal data with multiple continuous outcomes.

Authors:  J Roy; X Lin
Journal:  Biometrics       Date:  2000-12       Impact factor: 2.571

2.  Bivariate linear mixed models using SAS proc MIXED.

Authors:  Rodolphe Thiébaut; Hélène Jacqmin-Gadda; Geneviève Chêne; Catherine Leport; Daniel Commenges
Journal:  Comput Methods Programs Biomed       Date:  2002-11       Impact factor: 5.428

3.  Joint modelling of multivariate longitudinal profiles: pitfalls of the random-effects approach.

Authors:  Steffen Fieuws; Geert Verbeke
Journal:  Stat Med       Date:  2004-10-30       Impact factor: 2.373

4.  Predicting renal graft failure using multivariate longitudinal profiles.

Authors:  Steffen Fieuws; Geert Verbeke; Bart Maes; Yves Vanrenterghem
Journal:  Biostatistics       Date:  2007-12-03       Impact factor: 5.899

5.  Random-effects models for multivariate repeated measures.

Authors:  S Fieuws; Geert Verbeke; G Molenberghs
Journal:  Stat Methods Med Res       Date:  2007-07-26       Impact factor: 3.021

Review 6.  A review of multivariate longitudinal data analysis.

Authors:  S Bandyopadhyay; B Ganguli; A Chatterjee
Journal:  Stat Methods Med Res       Date:  2010-03-08       Impact factor: 3.021

7.  Correlated binary regression with covariates specific to each binary observation.

Authors:  R L Prentice
Journal:  Biometrics       Date:  1988-12       Impact factor: 2.571

8.  Random-effects models for longitudinal data.

Authors:  N M Laird; J H Ware
Journal:  Biometrics       Date:  1982-12       Impact factor: 2.571

9.  Gender differences in a longitudinal study of age-associated hearing loss.

Authors:  J D Pearson; C H Morrell; S Gordon-Salant; L J Brant; E J Metter; L L Klein; J L Fozard
Journal:  J Acoust Soc Am       Date:  1995-02       Impact factor: 1.840

10.  Estimating a treatment effect from multidimensional longitudinal data.

Authors:  S M Gray; R Brookmeyer
Journal:  Biometrics       Date:  1998-09       Impact factor: 2.571

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  62 in total

1.  DYNAMIC PREDICTION FOR MULTIPLE REPEATED MEASURES AND EVENT TIME DATA: AN APPLICATION TO PARKINSON'S DISEASE.

Authors:  Jue Wang; Sheng Luo; Liang Li
Journal:  Ann Appl Stat       Date:  2017-10-05       Impact factor: 2.083

2.  Improved Sleep, Diet, and Exercise in Adults with Serious Mental Illness: Results from a Pilot Self-Management Intervention.

Authors:  Timothy Schmutte; Larry Davidson; Maria O'Connell
Journal:  Psychiatr Q       Date:  2018-03

3.  Tackling Longitudinal Round-Robin Data: A Social Relations Growth Model.

Authors:  Steffen Nestler; Katharina Geukes; Roos Hutteman; Mitja D Back
Journal:  Psychometrika       Date:  2016-12-06       Impact factor: 2.500

4.  Multivariate analysis of longitudinal rates of change.

Authors:  Matthew Bryan; Patrick J Heagerty
Journal:  Stat Med       Date:  2016-07-14       Impact factor: 2.373

Review 5.  Measurement error in geometric morphometrics.

Authors:  Carmelo Fruciano
Journal:  Dev Genes Evol       Date:  2016-04-01       Impact factor: 0.900

6.  A joint marginal-conditional model for multivariate longitudinal data.

Authors:  James Proudfoot; Walter Faig; Loki Natarajan; Ronghui Xu
Journal:  Stat Med       Date:  2017-12-04       Impact factor: 2.373

7.  Evolution of association between renal and liver functions while awaiting heart transplant: An application using a bivariate multiphase nonlinear mixed effects model.

Authors:  Jeevanantham Rajeswaran; Eugene H Blackstone; John Barnard
Journal:  Stat Methods Med Res       Date:  2016-11-16       Impact factor: 3.021

8.  A guide to missing data for the pediatric nephrologist.

Authors:  Nicholas G Larkins; Jonathan C Craig; Armando Teixeira-Pinto
Journal:  Pediatr Nephrol       Date:  2018-03-13       Impact factor: 3.714

9.  A joint modeling and estimation method for multivariate longitudinal data with mixed types of responses to analyze physical activity data generated by accelerometers.

Authors:  Haocheng Li; Yukun Zhang; Raymond J Carroll; Sarah Kozey Keadle; Joshua N Sampson; Charles E Matthews
Journal:  Stat Med       Date:  2017-08-07       Impact factor: 2.373

10.  Quantification of biological aging in young adults.

Authors:  Daniel W Belsky; Avshalom Caspi; Renate Houts; Harvey J Cohen; David L Corcoran; Andrea Danese; HonaLee Harrington; Salomon Israel; Morgan E Levine; Jonathan D Schaefer; Karen Sugden; Ben Williams; Anatoli I Yashin; Richie Poulton; Terrie E Moffitt
Journal:  Proc Natl Acad Sci U S A       Date:  2015-07-06       Impact factor: 11.205

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