Sentence examples for mixed models testing from inspiring English sources

* p-value for mixed models testing the effect of time (with covariance structure: compound symmetry) Tables 4 and 5 present the results of the linear regression analyses for changes in family caregivers' quality of life at 1- and 4-months.

Hierarchical regression analyses and mixed models tested the association of neurocognition and symptoms with social/occupational functioning as well as changes in these measures during treatment.Both symptoms and neurocognition were associated with quality of life in bivariate correlation analyses.

Linear mixed models tested these associations on all four categories and time-main effects in addition to a time x dynapenia/obesity-group interaction.

A second set of linear mixed models tested the crude and adjusted effect of incident type 2 diabetes on change in cognitive performance over time, excluding participants with baseline diabetes.

A second linear mixed model tested the same relation while adjusting for demographic characteristics.

The mixed model tested the effects for group, time, and the (group × time) interaction.

A linear mixed models test was used to analyze the friction within each of the four groups and to determine the impact of ligatures and wire size on friction.

Mixed models test was selected because it corrects for the relatedness between the genotyped individuals.

All mixed model testing and breeding value estimation (BLUP analyses) were carried out using ASReml (Gilmour et al., 2009) which utilises an average information-restricted maximum likelihood algorithm (REML).

To measure the influence of the relationship among the genotypes on the predictions, we used the adjusted means obtained in the second stage and the pedigree information of the entries in a mixed model testing genotypes and crosses as random effects, so that the variances of both effects would give us an estimation of how much the variation is attributed to the pedigree, e.g. the crosses.

The tests conducted included two-way fixed-effects test on the medians (med2way and mcp2a from the WRS2 package), three-way fixed-effects analysis of variance on the means, and general linear mixed model tests on the means by residual maximum likelihood (asreml in asreml package) with different assumptions about the crop models and/or GCMs as being random factors or error terms.