Efficient t0-year risk regression using the logistic model
Research output: Contribution to journal › Journal article › Research › peer-review
In some clinical studies patient survival beyond a specific point in time, t(0), say, maybe of special interest as it may for instance indicate patient cure. To analyze the t(0)-year risk for such patients may be accomplished using logistic regression with appropriate weights (IPWCC) that may further be augmented (AIPWCC) to improve efficiency. In this paper, we derive the most efficient estimator for this problem, which is different from the AIPWCC based on the full data efficient influence function. We first give the result for a survival endpoint and then generalize to the competing risk setting. The proposed estimators superior behavior is illustrated using simulations as well as applying it to some real data concerning the survival of blood and marrow transplanted patients.
|Journal||Scandinavian Journal of Statistics|
|Number of pages||14|
|Publication status||E-pub ahead of print - 2023|
- augmentation, censoring, double robustness, efficient estimation, fixed time regression, inverse probability of censoring weighting, t(0)-year risk, PSEUDO-OBSERVATIONS, CURVES