Sentence examples for multiple regressions between from inspiring English sources

VIF = 1/(1 − r2), in which r is the correlation coefficient of multiple regressions between one variable and the others.

The model calibration process is based on the multiple regressions between the predictand (observed rainfall) and NCEP predictors (Table 8).

For each buffer area and species, we conducted multiple regressions between average bird counts and percent area represented by each land use category.

It was developed by multiple regressions between estimated centroid of the atmosphere and surface pressure, surface temperature using radiosonde data of five radiosonde stations spread over the Indian subcontinent.

Finally, the size – shape relationship was assessed by calculating directions of allometry by multiple regressions between size and FCs.

Simple and multiple regressions between contaminants and TSH as well as fT4 were not significant.

A population dynamic model would better account for the interaction between density-dependent processes and weather variables than a simple multiple regression between the latter and guanaco population growth rate.

Finally, as the rate of force development depends on muscle activation and muscle fiber type, it is likely that a multiple regression between CMJ, MRTD, and stiffness indices includes the main factors determining vertical jump performance.

We therefore performed a multiple regression between the mirSVR score, a conventional estimate of mRNA down-regulation calculated for each miRNA-mRNA pair [ 28], and the distance between the same miRNA-mRNA pair in each of the first 50 MDS dimensions.

a: multiple regressions performed between each dimension of burnout and facet of job satisfaction separately (P < 0.10); b: for each burnout dimension, all significant job facets from 1st analysis entered simultaneously in second multiple regression (P < 0.05).

d: multiple regressions performed between each dimension of job search/turnover and facet of job satisfaction separately (P < 0.10); e: for both job search and turnover, all significant job facets from 1st analysis entered simultaneously in second multiple regression (P < 0.05).