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作者：Su, Yu-Ru; Wang, Jane-Ling
作者单位：University of California System; University of California Davis; National Cheng Kung University; University of California System; University of California Davis
摘要：There is a surge in medical follow-up studies that include longitudinal covariates in the modeling of survival data. So far, the focus has been largely on right-censored survival data. We consider survival data that are subject to both left truncation and right censoring. Left truncation is well known to produce biased sample. The sampling bias issue has been resolved in the literature for the case which involves baseline or time-varying covariates that are observable. The problem remains open...
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作者：Antognini, Alessandro Baldi; Zagoraiou, Maroussa
作者单位：University of Bologna
摘要：The present paper deals with the problem of allocating patients to two competing treatments in the presence of covariates or prognostic factors in order to achieve a good trade-off among ethical concerns, inferential precision and randomness in the treatment allocations. In particular we suggest a multipurpose design methodology that combines efficiency and ethical gain when the linear homoscedastic model with both treatment/covariate interactions and interactions among covariates is adopted. ...
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作者：Yang, Min; Stufken, John
作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; University System of Georgia; University of Georgia
摘要：We extend the approach in [Ann. Statist. 38 (2010) 2499-2524] for identifying locally optimal designs for nonlinear models. Conceptually the extension is relatively simple, but the consequences in terms of applications are profound. As we will demonstrate, we can obtain results for locally optimal designs under many optimality criteria and for a larger class of models than has been done hitherto. In many cases the results lead to optimal designs with the minimal number of support points.
