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Classification Trees (CT) were used to explore the influence of the specified predictors on the use or refusal of condoms.
Univariable logistic regression of predictors on the use of clustering analysis to account for multiple centers is shown in Table 4.
Univariable logistic regression of predictors on the use of any type of accounting for clustering is shown in Table 3, which compares articles containing these predictors to those that do not.
Other included predictors had small effect estimates and none were found to have a significant association with the outcome variable at alpha = 0.05.> Table 5 shows univariable logistic regression of predictors on the use of clustering analysis to account for multiple therapists.
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One such study, conducted in Boston, found that first CD4 count, viral load, insurance status, and being on combination therapy were predictors of the use of primary care services (Lo et al. 2002).
Another strength of the present study is the broad spectrum of patient-level variables examined as potential predictors and the use of "early on-treatment" variables to assess the predictive value of early changes in patients' status to reflect the medication's early efficacy, tolerability, and safety.
Moreover, we benchmark DISpro with seven other protein disorder predictors on the 95 targets used in CASP7.
To describe the magnitude of the effect of dichotomous predictors on the likelihood of colonoscopy use, we computed average changes in predicted probability using a multi-step process.
A multiple linear regression model was used to estimate independently the effects of the previously described predictors on the amount of HHS used per week.
Moreover, we compare DISpro with seven other automated disorder predictors on the 95 protein targets used in the seventh edition of Critical Assessment of Techniques for Protein Structure Prediction (CASP7).
Experimental results on the BetaSheet916 dataset showed significant improvements of the proposed method in both execution time and the prediction accuracy in comparison with the state-of-the-art β-sheet structure prediction methods Moreover, we investigate the effect of different contact map predictors on the performance of the proposed method using BetaSheet1452 dataset.
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