Sentence examples for linear regression designs from inspiring English sources
So the problem of finding isotropic DODs resembles that of finding weakly invariant linear regression designs.
The basic structure of algorithms for numerical computation of optimal approximate linear regression designs is briefly summarized.
We therefore applied two linear regression designs to our data, each of which was optimized for a specific purpose.
It has been argued previously that multiple linear regression designs in combination with random effects group statistics optimally account for appropriate sources of between-subject variance (Lorch & Myers, 1990).
In fact, methods from matrix and group theory which have been successfully applied in linear regression design can also be utilized here to construct various isotropic DODs.
In trial I, groups (6 fish each) were fed diets for 42 weeks (body mass 142 ± 1 to 1463 ± 83 g) (mean ± S.D ., containing graded levels of rapeseed oil substituting for fish oil using a linear regression design.
Multilevel analysis is a modified form of multiple linear regression designed to deal with data with a hierarchical clustering structure and has been extensively used in analysis of personal network data (e.g., Gierveld and Perlman 2006; van Duijn et al. 1999; Wellman and Frank 2001).
Statistical analysis methodologies including factor analysis, linear regression, nested design, and chi-square test are utilized in this study.
With consideration of this, the linear regression was designed such that the model utilised the expression levels of each individual miRNA as a covariate, in order to predict the signature score, taken as the median of the log-transformed expression levels of the signature genes.
1 Topics should include correlation and linear regression; experimental design such as t-tests, analysis of variance and chi-square; suggested departments: psychology, sociology, education, biology, and mathematics.
One linear and one quadratic simulated screening scenarios are studied and compared using linear regression and edge designs analysis.
