Mixed-effects modelStability study is a critical component for the submission and market authorization of a new drug or biological product. Long-term stability studies are required to establish the stability profile and shelf life of the drug product. Accelerated stability studies may provide insight ...
A common approach for dealing with longitudinal categorical responses is to use the Generalized Linear Mixed Model (GLMM). This model induces the potential relation between response variables over time via a vector of random effects, assumed to be shared parameters in the non-ignorable missing ...
Mixed models with set-specific random effects are a flexible tool to model the different sets of items jointly. However, computational problems typically arise as the number of sets increases. This is especially true when the random-effects distribution cannot be integrated out analytically, as with...
Educational Experiences of Children in Foster Care Using a mixed effects model, it was estimated about 31 percent of foster youth qualified for or received... Scherr,G T. - 《School Psychology International》 被引量: 79发表: 2007年 The MM Algorithm Ranola JM, Ahn S, Sehl ME, Smith DJ, ...
We apply a linear mixed-effects model to multivariate failure time data. Computation of the regression parameters involves the Buckley-James method in an iterated Monte Carlo expectation-maximization algorithm, wherein the Monte Carlo E-step is implemented using the Metropolis-Hastings algorithm. From ...
A mixed effects model version of a common swine growth function is introduced. This version, in which the mature BW of each pig is considered random, accou... Craig, B.A.,AP Schinckel - 《Professional Animal Scientist》 被引量: 86发表: 2001年 A multilevel nonlinear mixed-effects approach...
A precise and accessible presentation of linear model theory, illustrated with data examplesStatisticians often use linear models for data analysis and for developing new statistical methods. Most books on the subject have historically discussed univariate, multivariate, and mixed linear models separately,...
This study presents discussion on the effects of correlation among response respect to estimator properties in mixed logit model on multivariate binary response. It is assumed that each respondent was observed for T response. YSUBit/SUB is the tSUPth/SUP response for the iSUPth/SUP individual/...
A mixed effect model is proposed to jointly analyze multivariate longitudinal data with continuous, proportion, count, and binary responses. The association of the variables is modeled through the correlation of random effects. We use a quasi-likelihood type approximation for nonlinear variables and tra...
Bayesian multivariate meta-analysis models: two multivariate analogues of the traditional univariate random effects models which make different assumptions about the relationships between studies and estimates, and a multivariate random effects model which is a Bayesian adaptation of the mixed model approach...