Sentence examples for using the covariance structure from inspiring English sources

As we previously described [33], viral load set-point was estimated using the covariance structure model of the first 2 4 sequential viral load measures across individual participants.

It was generated using the covariance structure of real datasets.

More recently, Xu [ 24] proposed an alternative way to include these interaction effects using the covariance structure given by, with, and Z k is the jth marker locus such that Using this assumption a different version of the common epistasis model is given by: 3 with and.

Even when more complex genetic models are used, the covariance structure among individuals will depend on the particular mix of genotypes, and may not reflect the inherent patterns of canalization.

This model used the covariance structure that maximizes Schwartz's Bayesian Criterion and the Kenward-Roger method for estimating denominator degrees of freedom.

The time profiles were analysed by a multivariate analysis of variance for repeated measurements according to a mixed random effect model, which uses the covariance structure also for estimating the model parameters (SAS PROC MIXED with REPEATED statement and no RANDOM statement).

The kinship matrix (K ) was estimated from the same SSR markers using the allele-similarity method [ 47], which guarantees a positive semi-definite relationship matrix among the 201 genotypes, and was used for the covariance structure of the random genotype effects in the linear mixed model.

All statistical tests considered the dependency within subjects using compound symmetry as the covariance structure and used a criterion of statistical significance of.05.

Exploratory factor analysis was used to examine the covariance structure of symptoms reported by approximately 50,000 cohort members during 2004-2006.

The mixed model was estimated by maximum likelihood and an unstructured covariance type was used to model the covariance structure among repeated measures.

Principal component analysis in this context is used to extract the covariance structure of the PET image volumes and to identify distributed clusters of voxels that covary in their signal intensity according to experimental condition (somatosensory discrimination, rest) and/or group assignment (patients, controls).