Sentence examples for using a regression procedure from inspiring English sources

For this reason, and as is standard in twin analysis, all measures were also corrected for age and sex effects using a regression procedure [37].

Data were analysed using a regression procedure referred to as 'longitudinal logistic regression' [ 36], 'marginal logistic regression' [ 54] or 'repeated measures logistic regression' [ 55], using Generalized Estimation Equations in PASW Statistics 18 [ 55].

We also examined the relationship between remotely sensed and field data, in order to map α- and β-diversity at the landscape-level in the Yucatan Peninsula, using a regression kriging procedure.

Analyses have been carried out on a total of 302 previously published tests using a nonparametric regression procedure known as multivariate adaptive regression splines (MARS), to assess the capacity energy required to trigger liquefaction in sand and silty sands.

Subject-specific statistical maps for the 18 RSNs were created using a dual regression procedure [ Filippini et al., 2009] that involves spatial and temporal regression.

In G −, genotypic information propagates into the relationships of ungenotyped individuals, using a linear regression procedure that implicitly predicts unobserved genotypes as linear combinations of observed genotypes with regression coefficients derived from pedigree relationships.

The spatial pattern of forest cover was quantified by means of pattern metrics and the relation between false change and spatial pattern was analyzed using a stepwise regression procedure.

The coefficient of determination (R2) values, obtained by using a linear regression procedure, were 0.9797 and 0.9833 for frog and pig, respectively.

Using a logistic regression procedure we calculated the area under ROC curve (AUC) for every scoring system.

In the multivariate analysis, T-stage (P = 0.0056) and PCNA LI (P = 0.0332) were significant factors for local control in the final model using a stepwise regression procedure.

There were up to 11% missing values for at least one variable in the dataset, which we imputed using a chained regression procedure, which is recognised as a suitable approach for imputing incomplete large, national and public datasets [ 55– 55].