Logistic regression when covariates are random effects from a non‐linear mixed model
Copyright policy )Logistic regression when covariates are random effects from a non‐linear mixed model
AbstractIn many studies, the association of longitudinal measurements of a continuous response and a binary outcome are often of interest. A convenient framework for this type of problems is the joint model, which is formulated to investigate the association between a binary outcome and features of longitudinal measurements through a common set of latent random effects. The joint model, which is the focus of this article, is a logistic regression model with covariates defined as the individual‐specific random effects in a non‐linear mixed‐effects model (NLMEM) for the longitudinal measurements. We discuss different estimation procedures, which include two‐stage, best linear unbiased predictors, and various numerical integration techniques. The proposed methods are illustrated using a real data set where the objective is to study the association between longitudinal hormone levels and the pregnancy outcome in a group of young women. The numerical performance of the estimating methods is also evaluated by means of simulation.
Generalized linear models (logistic models), Farmacología, 610, Applications of statistics to biology and medical sciences; meta analysis, Pregnancy, 03 Salud y bienestar, General nonlinear regression, Humans, Chorionic Gonadotropin, beta Subunit, Human, Longitudinal Studies, Laplace approximation, Gaussian quadrature methods, nonlinear mixed-effects models, best linear unbiased predictor (BLUP) and two-stage estimator, Analysis of Variance, Likelihood Functions, Stochastic Processes, Gonadotropinas coriónicas, Computational problems in statistics, Estimation in survival analysis and censored data, logistic regression model, Logistic Models, Nonlinear Dynamics, ROC Curve, Análisis de variancia, Numerical integration, 03 Good Health and Well-being, Female, Medicina y salud
Generalized linear models (logistic models), Farmacología, 610, Applications of statistics to biology and medical sciences; meta analysis, Pregnancy, 03 Salud y bienestar, General nonlinear regression, Humans, Chorionic Gonadotropin, beta Subunit, Human, Longitudinal Studies, Laplace approximation, Gaussian quadrature methods, nonlinear mixed-effects models, best linear unbiased predictor (BLUP) and two-stage estimator, Analysis of Variance, Likelihood Functions, Stochastic Processes, Gonadotropinas coriónicas, Computational problems in statistics, Estimation in survival analysis and censored data, logistic regression model, Logistic Models, Nonlinear Dynamics, ROC Curve, Análisis de variancia, Numerical integration, 03 Good Health and Well-being, Female, Medicina y salud
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).8 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!