Estimation of extended mixed models using latent classes and latent processes: the R package lcmm
TLDR
The R package lcmm as mentioned in this paper provides a series of functions to estimate statistical models based on linear mixed model theory, including the estimation of mixed models and latent class mixed models for Gaussian longitudinal outcomes.Abstract:
The R package lcmm provides a series of functions to estimate statistical models based on linear mixed model theory. It includes the estimation of mixed models and latent class mixed models for Gaussian longitudinal outcomes (hlme), curvilinear and ordinal univariate longitudinal outcomes (lcmm) and curvilinear multivariate outcomes (multlcmm), as well as joint latent class mixed models (Jointlcmm) for a (Gaussian or curvilinear) longitudinal outcome and a time-to-event that can be possibly left-truncated right-censored and defined in a competing setting. Maximum likelihood esimators are obtained using a modified Marquardt algorithm with strict convergence criteria based on the parameters and likelihood stability, and on the negativity of the second derivatives. The package also provides various post-fit functions including goodness-of-fit analyses, classification, plots, predicted trajectories, individual dynamic prediction of the event and predictive accuracy assessment. This paper constitutes a companion paper to the package by introducing each family of models, the estimation technique, some implementation details and giving examples through a dataset on cognitive aging.read more
Citations
More filters
Journal ArticleDOI
The GRoLTS-Checklist: Guidelines for Reporting on Latent Trajectory Studies
TL;DR: The purpose of GRoLTS is to present criteria that should be included when reporting the results of latent trajectory analysis across research fields, and goes through a systematic process to identify key components that, according to a panel of experts, are necessary when reporting results for trajectory studies.
Journal ArticleDOI
Effects of Gut Microbiota Manipulation by Antibiotics on Host Metabolism in Obese Humans: A Randomized Double-Blind Placebo-Controlled Trial.
Dorien Reijnders,Gijs H. Goossens,Gerben D. A. Hermes,Evelien P. J. G. Neis,Christina M. van der Beek,Jasper Most,Jens J. Holst,Kaatje Lenaerts,Ruud S. Kootte,Max Nieuwdorp,Albert K. Groen,Steven W.M. Olde Damink,Mark V. Boekschoten,Hauke Smidt,Erwin G. Zoetendal,Cornelis H. C. Dejong,Ellen E. Blaak +16 more
TL;DR: Antibiotics did not affect tissue-specific insulin sensitivity, energy/substrate metabolism, postprandial hormones and metabolites, systemic inflammation, gut permeability, and adipocyte size, indicating that interference with adult microbiota by 7-day antibiotic treatment has no clinically relevant impact on metabolic health in obese humans.
Journal ArticleDOI
Hyperglycemia and Adverse Pregnancy Outcome Follow-up Study (HAPO FUS): Maternal Glycemia and Childhood Glucose Metabolism.
Denise M. Scholtens,Alan Kuang,Lynn P. Lowe,Jill Hamilton,Jean M. Lawrence,Yael Lebenthal,Wendy J. Brickman,Wendy J. Brickman,Peter E. Clayton,Ronald C.W. Ma,David R. McCance,Wing Hung Tam,Patrick M. Catalano,Barbara Linder,Alan R. Dyer,William L. Lowe,Boyd E. Metzger +16 more
TL;DR: Across the maternal glucose spectrum, exposure to higher levels in utero is significantly associated with childhood glucose and insulin resistance independent of maternal and childhood BMI and family history of diabetes.
Journal ArticleDOI
Joint modelling of repeated measurement and time-to-event data: an introductory tutorial
TL;DR: Joint models should be preferred for simultaneous analyses of repeated measurement and survival data, especially when the former is measured with error and the association between the underlying error-free measurement process and the hazard for survival is of scientific interest.
Journal ArticleDOI
Framework to construct and interpret latent class trajectory modelling.
Hannah Lennon,Scott P. Kelly,Matthew Sperrin,Iain Buchan,Amanda J. Cross,Michael F. Leitzmann,Michael B. Cook,Andrew G Renehan +7 more
TL;DR: A framework to construct and select a ‘core’ LCTM is proposed, which will facilitate generalisability of results in future studies and rationalise a systematic framework to derive a “core” favoured model.
References
More filters
Journal Article
R: A language and environment for statistical computing.
TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Journal ArticleDOI
Random-effects models for longitudinal data
Nan M. Laird,James H. Ware +1 more
TL;DR: In this article, a unified approach to fitting two-stage random-effects models, based on a combination of empirical Bayes and maximum likelihood estimation of model parameters and using the EM algorithm, is discussed.
Book
Linear Mixed Models for Longitudinal Data
Geert Verbeke,Geert Molenberghs +1 more
TL;DR: Using data of 955 men, Brant et al showed that the average rates of increase of systolic blood pressure (SBP) are smallest in the younger age groups, and greatest in the older agegroups, and that obese individuals tend to have a higher SBP than non-obese individuals.
Journal ArticleDOI
Mixture densities, maximum likelihood, and the EM algorithm
TL;DR: This work discusses the formulation and theoretical and practical properties of the EM algorithm, a specialization to the mixture density context of a general algorithm used to approximate maximum-likelihood estimates for incomplete data problems.
Related Papers (5)
Estimation of extended mixed models using latent classes and latent processes: The R package lcmm
Two-Step Estimation of Models Between Latent Classes and External Variables
Zsuzsa Bakk,Jouni Kuha +1 more