Sentence examples for multiple regression that from inspiring English sources

Exponential models of multiple regression that use a 1-m LiDAR DEM (digital elevation model) explained 70 93% of spatial variability in Mtotal.

Backward stepwise multiple regression that included Apgar scores and gestational age showed a significant correlation of absolute nucleated red blood cell count with the presence of asthma and its severity (P <.001).

A multiple regression that used individual participants' path coefficients to predict participants' mMJI scores was performed in SPSS 17.0 (SPSS , Inc.

In the multiple regression that is the definitive test of whether martial arts influences change in classroom behavior, the time two behavior is the dependent variable.

It is typical of the bivariate multiple regression that a common set of p variables s 1,s 2,...,s p is used to explain h and d.

Its validity to academic performance depends on the specific scale, e.g. Cano (2006) found, using multiple regression, that two scales (namely Affective Strategies and Goal Strategies) contributed to academic performance, whereas one (Comprehension Monitoring Strategies) did not.

In Table 5, we present one linear and two multiple regressions that introduce GDP to the analysis.

We compare the proposed methods with commonly used statistical approaches such as fitting separate regression models for each potential window and fitting simultaneously adjusted multiple regressions that include all exposure measures (time windows) in one model.

It is not restriction in the number of variables, the rule for multiple regressions that the number of variables must be smaller than the number of objects does not apply in PCA case.

The affective category's score was correlated linearly in individual form with the greatest number of variables and it was adjusted to a model of multiple regressions that almost explained the variance in 100% with a contribution of the sensorial and autonomic variables of a 70%and30%0%, respectively.

For both noise and plasticity, our results are robust to a multiple regression analysis that controls for protein abundance and that controls noise for plasticity and vice versa.