Sentence examples for blocks of variables were from inspiring English sources

Because the level of resources devoted to environmental management can have an influence on sustainable product innovation (Severo et al., 2016) and that kind of innovation is associated with pollution prevention, three blocks of variables were used in each of the hierarchical regression model.

Different blocks of variables were tested to find the best model for adjusting for potential confounding.

It should be noted that in the blockwise structured model, these blocks of variables were added to the model last.

Two blocks of variables were entered separately; block 1: Background variables (age, gender, educational level, number of comorbid diseases); block 2: Illness and treatment perceptions variables.

In each phase of the analysis, blocks of variables were added to build multiple models to examine interactions among variables measuring different livelihood constructs, and to assess the extent to which different sets of livelihood variables distinguish household groups.

Four blocks of variables were entered into the regression models in the following order: (1) ethnic linguistic group, (2) sociodemographic characteristics, (3) health status and (4) the six dimensions of patient experiences in PHC: accessibility, utilisation, relationship continuity of care, interpersonal processes of care, quality and acceptability of care and obtaining care outside Canada.

The blocks of variables are considered according to the INEGI division, and additionally, we compare this division with respect to the National Institute's Global Econometric Model, which considers nine blocks with a total of 67 variables.7.7

Model fit statistics (Likelihood ratio Wald test and pseudo-R2) indicate that all five models have significant predictive power, which increases as additional blocks of variables are included in the model.

Binary logistic regression models for the dependant variables were built in which each consecutive, conceptually grouped, block of variables were entered into a stepwise regression algorithm (SES, health and behaviour, community context, and pollution health effects) following forced entry of a priori variables.

The most important predictor variable within this block of variables is the cardiac risk score, which is particularly significant with respect to the physical component of HRQOL.

§ denotes the significant predictors found as each block of variables was added to the model * p < 0.05, ** p < 0.01, *** p < 0.001 There was no evidence that having a non-science A-level affected performance at any stage on the course, nor that the number of A-levels was influential.