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and partly because of the unexplained causal direction concerning the relationship between explanatory and dependent variables.
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The study also assumed a linear additive relationship between the explanatory and dependent variable.
A four-year lag between the explanatory and dependent variables may address this issue.
Steiner's model was criticized by Resnik & Kushner 1987 who questioned the absolute distinction between explanatory and non-explanatory proofs and argued that such a distinction can only be context-dependent.
In applied studies, the relationship between an explanatory and a dependent variable is routinely measured using a statistical model.
The categorical transformation is a more flexible way to explore the unknown shape of the effect between an explanatory and a dependent variable.
The methods developed, based on resampling methods, enable us to consider categorical transformations as more flexible in order to explore the unknown shape of the effect between an explanatory and a dependent variable.
The main difference between PC and PLS is that PC extracts latent factors accounting for most of gene expression variations regardless of outcome variables and is unsupervised while PLS maximizes the covariance between latent explanatory and latent dependent variables and is supervised in nature.
Multiple logistic regression models were performed to detect statistically significant differences between the appropriate explanatory variables and dependent variables that represented utilization of dental services [users vs. non-users] and patterns of dental attendance (regular vs. irregular), using the backward stepwise Wald method (BSTEP).
Both bivariate and multivariate analyses were done to determine the presence of statistically significant associations and strength of associations between explanatory variables and the dependent variable.
Fig. 3 Scatterplot of each pair of explanatory features and dependent variable (importance index) in the final dataset for the period between 1991 and 2011.
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