Sentence examples for mixed models framework from inspiring English sources

37 39 Recently, it has been shown that, through the introduction of the generalised linear mixed models framework, new estimation methods and model specifications can be used to tackle the identification problem.

Owing to the hierarchical structure of the data and the planned missingness design, analyses will be performed within the linear mixed models framework, such as to model the variability and dependency at the different levels.

Two major recent developments in handling categorical data include Muthen's extension of SEM to the 'latent variable modeling' approach [ 17] and an extension of generalized linear models to latent and mixed variables under GLLAMM (Generalized Linear Latent And Mixed Models) framework [ 18].

Methods to derive tests and confidence intervals, fit statistics and (best-linear unbiased) predictions have been previously developed within the linear mixed models framework for the application in this setting, together with a description of the software implementation in the R package mvmeta[ 12].

GBLUP has been shown to be equivalent to ridge regression BLUP (Goddard 2009; Stranden and Garrick 2009), and one of the advantages of GBLUP is that the model can use the well-known mixed models framework similar to the traditional pedigree-based BLUP models.

The modelling approach in MET analysis is recently based on mixed model framework (Piepho 1998; Balzarini 2002).

In these studies, item position effects were estimated as either fixed or random effects using multilevel item response theory (IRT) models within the generalized linear mixed modeling framework.

To examine position effects in large-scale assessments, previous studies often used multilevel item response models within the generalized linear mixed modeling framework.

Then we tested if a random effect model can improve precision in the estimate of move length in a generalised linear mixed model framework.

These genotype group assignments are then treated as cluster indicators in the usual mixed modeling framework.

This paper presents a review of FA models and examines their implementation in the standard, linear mixed model framework.