Journal of the American Statistical Association

最新文章

• Nonparametric estimation with recurrent event data AI翻译
  作者：Peña, EA; Strawderman, RL; Hollander, M
  作者单位：University of South Carolina System; University of South Carolina Columbia; Cornell University; Cornell University; State University System of Florida; Florida State University
  摘要：The problem of nonparametric estimation for the distribution function governing the time to occurrence of a recurrent event in the presence of censoring is considered. We derive Nelson-Aalen and Kaplan-Meier-type estimators for the distribution function, and establish their respective finite-sample and asymptotic properties. We allow for random observation periods for each subject under study and explicitly account for the informative sum-quota nature of the data accrual scheme. These allowanc...
• Regularization of wavelet approximations - Discussion AI翻译
  作者：Solo, V
  作者单位：University of New South Wales Sydney
• Semiparametric and nonparametric regression analysis of longitudinal data - Comment AI翻译
  作者：Lin, XH; Carroll, RJ
  作者单位：University of Michigan System; University of Michigan; Texas A&M University System; Texas A&M University College Station; Texas A&M University System; Texas A&M University College Station
• Inference for a random wavelet packet model of single-channel event-related potentials AI翻译
  作者：Raz, J; Turetsky, BI; Dickerson, LW
  作者单位：University of Pennsylvania; University of Pennsylvania; University of Iowa
  摘要：Event-related potentials (ERPs) are brain electrical potentials associated with sensory and cognitive processing. ERP researchers typically wish to separate a recorded time series into functionally distinct component waveforms, and to estimate the effects of experimental conditions on each component. We present an integrated statistical approach to the decomposition of single-channel ERPs and to inference concerning the component waveforms and the effects of experimental conditions on the ampl...
• Evaluation of traffic injury prevention programs using counting process approaches AI翻译
  作者：Sun, JG; Kim, YJ; Hewett, J; Johnson, JC; Farmer, J; Gibler, M
  作者单位：University of Missouri System; University of Missouri Columbia; University of Missouri System; University of Missouri Columbia
  摘要：Traumatic brain injury (TBI) is among the most devastating of injuries leading to death and disability among young people today. The major cause of TBI is motor vehicle crashes. One way to reduce the rates of such crashes and thus TBI is through prevention programs. This article analyzes a study conducted for assessing a 1-day educational traffic injury prevention program for young traffic offenders with speeding violations. The obtained data include information about traffic convictions for s...
• Likelihood-based methods for missing covariates in the Cox proportional hazards model AI翻译
  作者：Herring, AH; Ibrahim, JG
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute
  摘要：Problems associated with missing covariate data are well known but often ignored. We present a method for estimating the parameters in the Cox proportional hazards model when the missing data are missing at random (MAR) and censoring is noninformative. Due to the computational burden of this method, we introduce an approximation that allows us to use a weighted expectation-maximization (EM) algorithm to estimate the parameters more easily. When the missing covariates are continuous rather than...
• Semiparametric and nonparametric regression analysis of longitudinal data - Comment AI翻译
  作者：Hoover, DR; Wu, CO
  作者单位：Rutgers University System; Rutgers University New Brunswick; Johns Hopkins University
• Cluster identification using projections AI翻译
  作者：Peña, D; Prieto, FJ
  作者单位：Universidad Carlos III de Madrid
  摘要：This article describes a procedure to identify clusters in multivariate data using information obtained from the univariate projections of the sample data onto certain directions. The directions are chosen as those that minimize and maximize the kurtosis coefficient of the projected data. It is shown that, under certain conditions, these directions provide the largest separation for the different clusters. The projected univariate data are used to group the observations according to the values...
• Local likelihood analysis of survival data with censored intermediate events AI翻译
  作者：Bebchuk, JD; Betensky, RA
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; Harvard University; Harvard T.H. Chan School of Public Health
  摘要：AIDS Clinical Trials Group protocol 193A was a randomized trial designed to compare survival and progression-free survival among patients on different treatment regimens. A complicating feature of the analysis of progression-free survival is that different censoring mechanisms operated on progression and survival, which resulted in more complete information on survival. A simple analysis that uses the minimum of the times to progression and survival and the minimum of the corresponding censori...
• Density estimation under random censorship and order restrictions: From asymptotic to small samples AI翻译
  作者：Efromovich, S
  作者单位：University of New Mexico
  摘要：Do a random censorship and/or order restrictions (e.g., nonnegativity, monotonicity, convexity) affect estimation of a smooth density under mean integrated squared error (MISE)? Under mild assumptions, the known asymptotic results, which are concerned only with rates, answer no. This answer, especially for censored data, contradicts practical experience and statistical intuition. So what can be said about constants of MISE convergence? It is shown that asymptotically (a) censorship does affect...