Sentence examples for multiple regressions the from inspiring English sources
In multiple regressions, the partial regression coefficient (byi) denotes the regression coefficient of each explanatory variable on the dependent variable, while removing the effect of all other explanatory variables as though they were kept constant.
In the case of the leverage plots from the multiple regressions, the considerable variability in the health parameters relates to blood Hg concentrations primarily at the extreme ranges.
Following multiple regressions, the pre- and post-operative day two TUG was significantly associated with LOS and OARS score, while the pre-operative WOMAC function subscale was associated with the OARS score.
After controlling for relevant confounding factors in multiple regressions, the elevation in negative self-esteem among IBS patients remained statistically significant (p = 0.02), as did the lower scores for sense of coherence among IBS cases (p = 0.04).
In multiple regressions, the main influences on the genetic diversity of quantitative traits within populations were the summer warmth in the populations of origin and whether populations were growing on rocks or on screes and walls (Table 5).
In a series of stepwise multiple regressions, the mediational role of general stress and diabetes-related stress in the relation between A1C and adolescents' adjustment was tested in cases that met the criteria for mediation described by Baron and Kenny (15).
Chapter 12: Multiple Regression Regression revisited Introducing a second predictor A detailed example Issues concerning normality Missing data Testing for linearity and homoscedasticity A multiple regression: The first pass Addressing multicollinearity Interactions What can go wrong?
In multiple regression, the highest correlation with stature was achieved in female (r = 0.72).
Finally, we analyze, within a multiple regression, the validity to our video- activity score.
In hierarchic multiple regression, the order in which variables are entered is specified in advance.
As in the interpretation of multiple regression, the R 2 indicates the amount of variance explained by the proposed model.
