| dc.description.abstract | In medical research, the receiver operating characteristic curve (ROC curve) is often used to evaluate the predictive ability of biological indicators for diseases. Among them, the time-dependent ROC curve proposed by Heagerty. & Zheng.(2005) is the most common. By analyzing and improving the prediction efficiency, it can identify the predictive ability of each biological indicator, and then find a suitable model. In the past, the literature used proportional hazards model (referred to as PH or Cox model), or used AFT model (Accelerated failure time model), PO model (Proportional odds model) to construct time-dependent ROC curves, and obtained the area under the ROC curves(AUC), through the weighted average of AUC at each time, the consistency index (Concordance) can be obtained, and it can be derived as a function of risk regression. When using different models, just substitute the corresponding hazard function, this consistency metric has previously been shown to be consistent with forecast accuracy. This study proposes a revision to the calculation method of AUC. Through the original definition, the area calculation method is adjusted to obtain results that are closer to the true value. Subsequently, each model proposed in the past literature will be used, applied to the same simulation data, the differences and pros and cons will be compared, and the accuracy of the consistency indicators will be observed. Finally, the actual AIDS data will be analyzed to show the results under different models. | en_US |