Sentence examples for regression account from inspiring English sources

Thus unlike other methods described above, the parameter estimates in each regression account for those derived from abiotic environmental predictors, biotic predictors, and spatial structure in the species data.

The values of R, R adjusted (≥0.70 and 0.64, respectively, except in case of NPQ800 for which R = 0.52 and R adjusted = 0.44) and RMSEF (≤45% of the average scale) as well as the p-values of the whole-model ANOVA tests (p < 0.0001 in every model) tend to indicate that altogether the effects selected through stepwise regression account for an important part of the response variability.

The best multiple regression accounted for 0.51 of the variation in SDMI within experiment.

Tables 9 and 10 present the coefficient estimates for the earnings regression accounting for selection effects for men and women, respectively.

These symptoms were combined into a single binary (any vs. none) variable and analyzed using logistic regression, accounting for the complex survey design.

The four methods compared are logistic regression accounting neither person nor item clustering effect, hierarchical logistic regression accounting for person clustering effect, the testlet model accounting for the item clustering effect, and the multilevel testlet model accounting for both person and item clustering effects.

Using the validation dataset, the environmental variables used in the PLS regression accounted for 56 and 63% of the respective variance in the 300 Index and Site Index (Table 1).

A breakpoint regression accounts for this, and explained variance increases to 38.0%.

The correlation was significant (p<0.001), but the regression accounted for only a small amount of the variance (r2 = 0.195) and the slope was considerably less than unity (0.18).

Competing-risks regression accounts for the fact that the risks of death and LTFU may not be independent, and allows the baseline hazard to differ between the competing risks [16].

Data were analyzed using multiple linear regression, accounting for covariates and clustering by community.