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Where variables were highly correlated (Pearson correlation coefficient >0.9) the most statistically significant or biologically plausible variable was selected.
It is probably best suited to areas where there is considerable background knowledge about plausible variable relationships.
Variables with a correlation above 0.8 were investigated for collinearity and the biologically more plausible variable was retained in the model [ 22].
Where variables were highly correlated the most biologically plausible variable, based on biological knowledge and previous research, was selected for inclusion in the model.
As the approach requires background knowledge, it is probably best suited to areas such as clinical epidemiology where researchers know quite a lot about a priori plausible variable relationships.
Similar(55)
Thus, despite the heterogeneity of the sample, a number of plausible variables related to the variability of the outcomes were also confirmed in cancer patients.
Univariate analysis was done to identify significant biological plausible variables.
Two-way interactions between biologically plausible variables in the multivariate model were investigated.
Only statistically significant associations and plausible variables were considered for the logistic regression model.
All plausible variables were included and a forced entry method initially considered all variables in the model.
All clinically plausible variables were considered for entry into the models before family history status was entered.
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