latent class mixed modelprofiling patientstime-to-event dataWhen modelling the dynamics of biomarkers in biomedical studies, it is essential to identify homogeneous clusters of patients and analyse them from a precision medicine perspective. This need has emerged as crucial and urgent during the COVID...
The Latent Class Choice Model (LCCM) remains the most popular and well-established example of discrete nonparametric mixing distributions and can be described as a mixed logit model with a finite mixing distribution (Train, 2008, Yuan et al., 2015). LCCM is a random-utility model that is ...
Bayesian Spatial and Spatio-temporal Modelling with R-INLA INLA is designed for latent Gaussian mod- els, a very wide and flexible class of models ranging from (generalized) linear mixed to spatial and spatio-temporal models. Combined with the Stochastic Partial Differential Equation approach (......
a generative Large Language Model for generalized linear and nonlinear multivariate latent-variable multilevel/mixed modelling - bbolker/gLLMglnlmvlvMMM
A latent class analysis (LCA) was conducted using the age of onset of alcohol, tobacco, and cannabis use as an indicator. Three distinct classes were identified: C1 (45%), characterized by early alcohol and late cannabis and tobacco use; C2 (49.1%) presenting early alcohol, cannabis and ...
Latent class models for joint analysis of longitudinal biomarker and event process data: application to longitudinal prostate-specific antigen ... H Lin,BW Turnbull,MCH Slate - 《Journal of the American Statistical Association》 被引量: 0发表: 2002年 Joint modelling of longitudinal measurements and ...
Modelling the severity of pedestrian injury in pedestrian-vehicle crashes in North Carolina: A partial proportional odds logit model approach Journal of Transportation Safety & Security, 12 (3) (2019), pp. 358-370 10.1080/19439962.2018.1483989 View in ScopusGoogle Scholar Li et al., 2021 J Li,...
Researchers have previously captured the complex and diverse patterns of polyvictimization and potentially relevant violence factors via mixture modelling (e.g., latent class analysis; growth mixture modelling), as this allows examination of heterogeneous experiences of victimization (Butcher et al., 2016...
(2020) studied the public’s willingness to reduce microplastics and the factors influencing it in Shanghai and used ordered regression modelling, reporting that more than half of the respondents had not heard of microplastics before the survey, but most of the public was willing to take measures...
Latent variable modelling has gradually become an integral part of mainstream statistics and is currently used for a multitude of applications in different subject areas. Examples of `traditional' latent variable models include latent class models, item-response models, common factor models, structural ...