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The backward selection procedure was applied to each of the 1,000 replicates to verify the stability of the chosen predictors in the final models.
Reports of physical abuse, suicide attempt and symptoms of dissociation were thus all significant predictors in the final models of both automatic and social functions.
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For prediction of self-reported abstinence at the end of the trial, predictors in the final model included: days of cocaine use, UDS results, CSSA score, and the ASI composite family social score.
Inspection of the variance inflation factor did not suggest multicollinearity among predictors in the final model.
Predictors in the final model were age, sex, race and CD4 count.
Medicaid and Medicare, AA race, longer LOS, and lower HbA1c were also significant independent predictors in the final model.
To select minimal soil chemical models, we used stepAIC on a model with all soil chemical vectors and included only statistically significant predictors in the final model.
Odds ratios for transport were estimated for predictors in the final model, and confidence intervals were computed using a normal approximation.
The β weights of each of these predictors in the final model, as well as the standard error of each regression model, were used to calculate predicted scores on each test.
It is important to note that this model is different from the one constructed in the original study where the predictors in the final model are age, baseline WBC, splenomegaly and mediastinal mass.
The predictors in the final model were: background NO2-concentration, traffic volume at the nearest road, distance to the nearest main road and residential land use in a 5 km circular buffer.
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