Sentence examples for multivariate general linear from inspiring English sources

Next, variables of interest were included as predictors of the two outcome variables in multivariate general linear models (GLM).

The underlying trends in DC phenotype in relation to conjugate properties were elucidated via multivariate general linear models.

Multivariate general linear models (GLM) including reconstruction algorithms, sphere diameter, SBR, and slice thickness of the reconstructed PET data were used to analyze the association between these factors.

To jointly model many brain voxels' responses to designed stimuli, we present a new low-rank multivariate general linear model (LRMGLM) for stimulus-evoked fMRI data.

A multivariate general linear model with post hoc comparisons was used to compare the outcomes of mechanical testing, mean compressive force and mean area of compression of the three groups (IBM SPSS Statistics Version 21, IBM Corp .. Two-tailed paired t-test was also performed to evaluate the difference between compressive force and area across the osteotomy initially and after 10 min.

To understand the changes in male acoustic signals in response to the broadcast stimulus, I developed a multivariate general linear model (GLM) for five acoustic characters.

A multivariate analysis (general linear model) assessed the effect of the supplementation with different antioxidant and strain on oxidative stress parameters (biomass propagation, fermentation capacity, lipid peroxidation, protein carbonylation, protective metabolites and enzymatic activities).

24 36 37 Multivariate analysis (general linear model) compared the resting state T2 values for the different muscle bellies between both groups, and revealed no influence of the factor 'injury' on the resting state T2 values: p values of 0.881, 0.728, 0.581 and 0.968 for the BF, the ST, the SM and the entire hamstring muscle portion, respectively (cf. table 3).

On the multivariate level, the general linear model procedure was used and the results were controlled for age and educational level.

Multivariate analysis with general linear modelling (analysis of covariance (ANCOVA)) was performed including potential confounding factors of duration of diabetes, other therapies (e.g. for diabetes or lipid lowering), smoking and body mass index (BMI) as covariables as indicated.

Multivariate analyses using general linear mixed modeling indicated a strong correlation between controlled BP and integration for those practices in the highest integration score quartile (r = 0.34, p = 0.07).