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crude.ROCt |
| This function allows the estimation of a crude time-dependent ROC curve, |
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\( \mbox{ } \) |
| respecting the definition proposed by Heagerty et al. (2000). |
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net.ROCt |
| This function allows the estimation of net time-dependent ROC curve, i.e. |
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\( \mbox{ } \) |
| when the only cause of death is due to the disease. |
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EUt |
| The expected utility theory allows the estimation of optimal |
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| cut-of for medical decision making. |
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AUC |
| This function computes the area under ROC curve using the trapezoidal rule |
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\( \mbox{ } \) |
| based on two vectors of sensitivities and specificities. |
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adjusted.ROC |
| This function allows for the estimation of ROC curve by taking into account possible |
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\( \mbox{ } \) |
| confounding factors (IPW or placement values estimators). |
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adjusted.ROCt |
| This function allows for the estimation of time-dependent ROC curve by taking |
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\( \mbox{ } \) |
| into account possible confounding factors (IPW estimator). |