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A related problem stems from modeling strategies when a large number of predictors are present.
Our approaches can also be applied to other settings where a large number of strongly correlated predictors are present.
These results also demonstrate that most of the signatures evaluated in this study can provide similar outcome predictions, although significant differences across predictors are present.
It makes more sense to start with a preventive intervention when 'short-term predictors' are present in elderly people compared to a situation in which it will take another 6 years (or longer) before disability will develop.
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The results for odds of child mortality with multiple predictors are presented in the same table.
Correlations between these predictors are presented in Table 2.
Unadjusted (crude) odds ratio (OR) and statistical significance for each predictors are presented in Table 7.
The predictors are presented with odds ratios (ORs) and 95% confidence intervals (CI) in Table 2.
Odds ratios (OR) and 95%% confidence intervals (CI) for significant predictors are presented.
The results from the full model that included all predictors, as well as results from the reduced model that included only significant predictors are presented.
The final hierarchical logistic regression models for each outcome variable, after trimming of nonsignificant predictors, are presented in Table 5. Lifetime Wheezing or Whistling in the Chest.
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