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作者：Tseng, Y. K.; Su, Y. R.; Mao, M.; Wang, J. L.
作者单位：National Central University; Fred Hutchinson Cancer Center; University of California System; University of California Davis
摘要：In clinical trials and other medical studies, it has become increasingly common to observe simultaneously an event time of interest and longitudinal covariates. In the literature, joint modelling approaches have been employed to analyse both survival and longitudinal processes and to investigate their association. However, these approaches focus mostly on developing adaptive and flexible longitudinal processes based on a prespecified survival model, most commonly the Cox proportional hazards m...
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作者：Xu, Peirong; Zhu, Ji; Zhu, Lixing; Li, Yi
作者单位：Southeast University - China; University of Michigan System; University of Michigan; Hong Kong Baptist University; University of Michigan System; University of Michigan
摘要：Linear discriminant analysis has been widely used to characterize or separate multiple classes via linear combinations of features. However, the high dimensionality of features from modern biological experiments defies traditional discriminant analysis techniques. Possible interfeature correlations present additional challenges and are often underused in modelling. In this paper, by incorporating possible interfeature correlations, we propose a covariance-enhanced discriminant analysis method ...
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作者：Zhao, Y. Q.; Zeng, D.; Laber, E. B.; Song, R.; Yuan, M.; Kosorok, M. R.
作者单位：University of Wisconsin System; University of Wisconsin Madison; University of North Carolina; University of North Carolina Chapel Hill; North Carolina State University; University of Wisconsin System; University of Wisconsin Madison
摘要：Individualized treatment rules recommend treatments based on individual patient characteristics in order to maximize clinical benefit. When the clinical outcome of interest is survival time, estimation is often complicated by censoring. We develop nonparametric methods for estimating an optimal individualized treatment rule in the presence of censored data. To adjust for censoring, we propose a doubly robust estimator which requires correct specification of either the censoring model or surviv...
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作者：Hsu, Jesse Y.; Zubizarreta, Jose R.; Small, Dylan S.; Rosenbaum, Paul R.
作者单位：University of Pennsylvania; Columbia University; University of Pennsylvania
摘要：An effect modifier is a pretreatment covariate that affects the magnitude of the treatment effect or its stability. When there is effect modification, an overall test that ignores an effect modifier may be more sensitive to unmeasured bias than a test that combines results from subgroups defined by the effect modifier. If there is effect modification, one would like to identify specific subgroups for which there is evidence of effect that is insensitive to small or moderate biases. In this pap...
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作者：Mealli, Fabrizia; Rubin, Donald B.
作者单位：University of Florence; Harvard University
摘要：We clarify the key concept of missingness at random in incomplete data analysis. We first distinguish between data being missing at random and the missingness mechanism being a missing-at-random one, which we call missing always at random and which is more restrictive. We further discuss how, in general, neither of these conditions is a statement about conditional independence. We then consider the implication of the more restrictive missing-always-at-random assumption when coupled with full u...
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作者：Atkinson, A. C.
作者单位：University of London; London School Economics & Political Science
摘要：Optimum designs are described for two treatments with different variances when covariates are included in the model. The designs, a generalization of Neyman allocation, are required in personalized medicine to model the effect of covariates on the choice of treatment. The use of the designs in clinical trials is indicated. D-optimality of the designs is established using results from Kiefer's general equivalence theorem. The results are obtained with the use of surprisingly elementary algebra.
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作者：Zeng, D.; Lin, D. Y.
作者单位：University of North Carolina; University of North Carolina Chapel Hill
摘要：Meta-analysis is widely used to compare and combine the results of multiple independent studies. To account for between-study heterogeneity, investigators often employ random-effects models, under which the effect sizes of interest are assumed to follow a normal distribution. It is common to estimate the mean effect size by a weighted linear combination of study-specific estimators, with the weight for each study being inversely proportional to the sum of the variance of the effect-size estima...
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作者：Gervini, Daniel
作者单位：University of Wisconsin System; University of Wisconsin Milwaukee
摘要：A characteristic feature of functional data is the presence of phase variability in addition to amplitude variability. Existing functional regression methods do not handle time variability in an explicit and efficient way. In this paper we introduce a functional regression method that incorporates time warping as an intrinsic part of the model. The method achieves good predictive power in a parsimonious way and allows unified statistical inference about phase and amplitude components. The asym...
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作者：Delaigle, A.; Hall, P.
作者单位：University of Melbourne
摘要：Group testing methods are used widely to assess the presence of a contaminant, based on measurements of the concentration of a biomarker, for example to test the presence of a disease in pooled blood samples. The test would be perfect if it produced a positive result whenever the contaminant was present, and a negative result otherwise. However, in practice the test is always at least somewhat imperfect, for example because it is sensitive to the proportion of contaminated items in the group, ...
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作者：Genton, Marc G.; Padoan, Simone A.; Sang, Huiyan
作者单位：King Abdullah University of Science & Technology; Bocconi University; Texas A&M University System; Texas A&M University College Station
摘要：Max-stable processes allow the spatial dependence of extremes to be modelled and quantified, so they are widely adopted in applications. For a better understanding of extremes, it may be useful to study several variables simultaneously. To this end, we study the maxima of independent replicates of multivariate processes, both in the Gaussian and Student-t cases. We define a Poisson process construction and introduce multivariate versions of the Smith Gaussian extreme-value, the Schlather extre...
