More specifically, we estimated an ordinary least squares (OLS) regression that incorporated several independent explanatory variables to explain the variations in graduation rates between the 569 schools.
The first set of linear models assumed that temperature and capacity factors were independent (explanatory) variables that predicted changes in emission rates.
On a priori grounds, we defined this algorithm as a sample regression function linking drug administration costs (ADMINCOST) and a number of independent explanatory variables (X).
Monitoring profile is based on monitoring the prescribed functional relationship between a dependent (explicative) variable and one or more independent (explanatory) variables.
It is also demonstrated that the use of thermal-time and hydro-time as independent explanatory variables in ANN models yields better prediction than using combined hydrothermal-time indices in classical NLR models.
Those independent (explanatory variables have been grouped as individual characteristics, household characteristics, and community characteristics. For instance, age, sex, and education level best describe individual characteristics. Household's total asset, household's access to various media outlets (TV, radio, and newspaper) describe the household's characteristics.
ANOVA/MANOVA, Hotelling tests, GLMs and/or Multiple regression analysis were applied to test the effects of independent explanatory variables.
When evident (r>0.2), a principle component analysis was conducted on the co-linear metrics and the first principal component was used in subsequent analyses as an independent explanatory variable [34].
In other words, a same variable within the same set of 10 12 variables but entered in different order changed their ranking of relative importance, based in independent explanatory power of the response variable.
Predictors declared as the most important by their independent explanatory power appeared in different ranking of importance in models with different orders of the same set of variables (Table 1).
This result changed little when the change was considered only for the five variables with most independent explanatory power (77.5%±5.86, 90.5%±5.04, 91.0%±3.76 for models with ten, eleven and twelve variables respectively).
