Pages that link to "Item:Q4366053"

The following pages link to Maximum Likelihood Algorithms for Generalized Linear Mixed Models (Q4366053):

Displaying 50 items.

• Computation of maximum likelihood estimates for multiresponse generalized linear mixed models with non-nested, correlated random effects (Q82357) (← links)
• Efficient maximum likelihood estimation of multiple membership linear mixed models, with an application to educational value-added assessments (Q82511) (← links)
• Generalized linear mixed models for correlated binary data with \(t\)-link (Q261007) (← links)
• Parsimonious classification via generalized linear mixed models (Q263228) (← links)
• Information based model selection criteria for generalized linear mixed models with unknown variance component parameters (Q391541) (← links)
• Empirical likelihood based goodness-of-fit testing for generalized linear mixed models (Q403438) (← links)
• Bayesian nonlinear regression for large \(p\) small \(n\) problems (Q414543) (← links)
• Efficient direct sampling MCEM algorithm for latent variable models with binary responses (Q425378) (← links)
• Fast fitting of joint models for longitudinal and event time data using a pseudo-adaptive Gaussian quadrature rule (Q425636) (← links)
• Asymptotic normality of posterior distributions for generalized linear mixed models (Q444957) (← links)
• Semiparametric analysis of longitudinal zero-inflated count data (Q608323) (← links)
• Sequential D-optimal designs for generalized linear mixed models (Q622431) (← links)
• Fast computing of some generalized linear mixed pseudo-models with temporal autocorrelation (Q626250) (← links)
• Generalized linear mixed models: a review and some extensions (Q636149) (← links)
• Robust analysis of longitudinal data with nonignorable missing responses (Q715507) (← links)
• An alternate approach to pseudo-likelihood model selection in the generalized linear mixed modeling framework (Q721612) (← links)
• High-dimensional variable selection with the plaid mixture model for clustering (Q722745) (← links)
• Practical considerations when analyzing discrete survival times using the grouped relative risk model (Q725426) (← links)
• Composite likelihood and maximum likelihood methods for joint latent class modeling of disease prevalence and high-dimensional semicontinuous biomarker data (Q736631) (← links)
• Generalized linear mixed models with informative dropouts and missing covariates (Q745314) (← links)
• Multivariate generalized linear mixed models with semi-nonparametric and smooth nonparametric random effects densities (Q746181) (← links)
• Estimation in nonlinear mixed-effects models using heavy-tailed distributions (Q746189) (← links)
• On a hybrid data cloning method and its application in generalized linear mixed models (Q746237) (← links)
• Likelihood-based and Bayesian methods for Tweedie compound Poisson linear mixed models (Q746345) (← links)
• A two-state mixed hidden Markov model for risky teenage driving behavior (Q746674) (← links)
• Application of H-likelihood to factor analysis models with binary response data (Q765830) (← links)
• A mixture model-based approach to the clustering of exponential repeated data (Q842912) (← links)
• A hyperspherical transformation forecasting model for compositional data (Q858461) (← links)
• A data cloning algorithm for computing maximum likelihood estimates in spatial generalized linear mixed models (Q901553) (← links)
• Joint modeling of longitudinal drug using pattern and time to first relapse in cocaine dependence treatment data (Q902936) (← links)
• Generalized linear random effects models with varying coefficients (Q951901) (← links)
• Estimation of a generalized random-effects model: some ECME algorithms and Monte Carlo evidence (Q953682) (← links)
• A pairwise likelihood approach to estimation in multilevel probit models (Q956809) (← links)
• Comparison of hierarchical and marginal likelihood estimators for binary outcomes (Q956865) (← links)
• Generalized semiparametrically structured mixed models (Q956981) (← links)
• On likelihood inference in binary mixed model with an application to COPD data (Q957114) (← links)
• Quasi-Monte Carlo sampling to improve the efficiency of Monte Carlo EM (Q957148) (← links)
• Pairwise likelihood inference in spatial generalized linear mixed models (Q957292) (← links)
• Improving the convergence rate in conditional autoregressive models (Q959216) (← links)
• Hierarchical models for repeated binary data using the IBF sampler (Q959226) (← links)
• A Bayesian analysis for longitudinal semicontinuous data with an application to an acupuncture clinical trial (Q961176) (← links)
• Pairwise likelihood for the longitudinal mixed Rasch model (Q961229) (← links)
• Estimation in the probit normal model for binary outcomes using the SAEM algorithm (Q961280) (← links)
• Nonignorable dropout models for longitudinal binary data with random effects: an application of Monte Carlo approximation through the Gibbs output (Q961962) (← links)
• A self-consistency approach to multinomial logit model with random effects (Q963886) (← links)
• Deletion measures for generalized linear mixed effects models (Q1010452) (← links)
• Maximum likelihood estimation for simplex distribution nonlinear mixed models via the stochastic approximation algorithm (Q1011107) (← links)
• Estimation of the mean squared error of predictors of small area linear parameters under a logistic mixed model (Q1019898) (← links)
• EM algorithms for nonlinear mixed effects models (Q1019960) (← links)
• Computational techniques for spatial logistic regression with large data sets (Q1019998) (← links)