Sentence examples for linear regression procedure from inspiring English sources

The SAS SAS Institutee, NC) multiple linear regression procedure, PROC REG, was used to regress the SF-36 outcomes data on treatment assignment, adult height, body mass index, and spontaneous menarche to compute regression coefficients and their 95% CI.

The GWAS was performed using the linear regression procedure implemented in PLINK [ 22], where the DYD for SCS were regressed on the number of copies of a particular allele at the SNP using the PLINK linear option, including population stratification as covariates.

A multiple linear regression procedure was used to design the relationships between molecular descriptor and the activity of imidazole derivatives.

The resulting data were analyzed using a modified forward selection linear regression procedure, thus revealing potential pharmacophoric relationships of the assessed targets within this chemical class.

Applied statistical time series analysis of daily soil temperature used certain proportion of previous observations, gave higher coefficient of determination as well as being able to incorporate measurement and model errors, making it better than the corresponding classical linear regression procedure.

Regression analysis is a technique of multivariate statistical analysis which aims at identifying the relationship between a variable (dependent var iable) and the ensemble of explanatory variables (independent variables) through a correlation model obtained by a linear regression procedure.

Application of linear regression procedures for method comparison studies in clinical chemistry, Part III.

Data were analyzed using multiple linear regression procedures.

Furthermore, the competitive effect of a neighbour species on a target species was quantified through linear regression procedures.

Therefore, a first element of model specification in WGR is whether genetic values are approximated by using linear regression procedures or using semiparametric methods.

Multiple linear regression procedures were applied to analyze data while adjusting for age, which was categorized into 60 69, and 70 84 years, and education.