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• Estimation of the causal effect of a time-varying exposure on the marginal mean of a repeated binary outcome - Comment AI翻译
  作者：Rubin, DB; Frangakis, CE
  作者单位：Harvard University; Johns Hopkins University
• Pseudolikelihood modeling of multivariate outcomes in developmental toxicology AI翻译
  作者：Geys, H; Molenberghs, G; Ryan, LM
  作者单位：Hasselt University; Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute
  摘要：The primary goal of this article is to determine benchmark doses based on the ethylene glycol study, which comprises data from a developmental toxicity study in mice. Because the data involve a vector of malformation indicators, a flexible model for multivariate clustered data is required. An exponential family model is considered and pseudolikelihood-based inferential tools are proposed, hence avoiding excessive computational requirements.
• Random sieve likelihood and general regression models AI翻译
  作者：Shen, XT; Shi, J; Wong, WH
  作者单位：University System of Ohio; Ohio State University; Chinese Academy of Sciences; University of California System; University of California Los Angeles
  摘要：Consider a semiparametric regression model Y = f (theta, X, epsilon), where f is a known function, theta is an unknown vector, epsilon consists of a random error and possibly of some unobserved variables, and the distribution F(.) of (epsilon, X) is unspecified. This article introduces, in a general setting, new methodology for estimating theta and F(.). The proposed method constructs a profile likelihood defined on random-level sets (a random sieve). The proposed method is related to empirica...
• Analyzing multiple emotions over time by autoregressive negative multinomial regression models AI翻译
  作者：Böckenholt, U
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign
  摘要：This article presents an autoregressive random coefficient model with overdispersed negative multinomial marginal distributions for the analysis of heterogeneity and serial dependencies in multivariate longitudinal count data. The model structure consists of four components that take into account (a) individual difference effects, (b) random time effects, (c) multiple event categories, and (d) autodependencies. The last component is based on a stochastic integer-valued autoregressive process p...
• Combining data from polymerase chain reaction DNA typing experiments: Applications to sperm typing data AI翻译
  作者：Navidi, W; Arnheim, N
  作者单位：Colorado School of Mines; University of Southern California
  摘要：The polymerase chain reaction (PCR) is a procedure by which the DNA in a single cell can be made to replicate many times in a test tube. By amplifying the DNA from individual sperm cells and typing the results, estimates of male recombination fractions can be made, which are valuable for creating genetic maps and locating regions of unusually intense crossover activity on the human genome. Because PCR typing results are subject to random error, stochastic models must be constructed to obtain a...
• Variable selection and function estimation in additive nonparametric regression using a data-based prior - Comment AI翻译
  作者：MacEachern, SN; Shen, XT
  作者单位：University System of Ohio; Ohio State University
• Bridging different eras in sports - Comment AI翻译
  作者：Albert, J
  作者单位：University System of Ohio; Bowling Green State University
• Testing the fit of a parametric function AI翻译
  作者：Aerts, M; Claeskens, G; Hart, JD
  作者单位：Hasselt University; Texas A&M University System; Texas A&M University College Station
  摘要：General methods for testing the fit of a parametric function are proposed. The idea underlying each method is to accept the prescribed parametric model if and only if it is chosen by a model selection criterion. Several different selection criteria are considered, including one based on a modified version of the Akaike information criterion and others based on various score statistics. The tests have a connection with nonparametric smoothing because they use orthogonal series estimators to det...
• SiZer for exploration of structures in curves AI翻译
  作者：Chaudhuri, P; Marron, JS
  作者单位：Indian Statistical Institute; Indian Statistical Institute Kolkata; University of North Carolina; University of North Carolina Chapel Hill
  摘要：In the use of smoothing methods in data analysis, an important question is which observed features are really there, as opposed to being spurious sampling artifacts. An approach is described based on scale-space ideas originally developed in the computer vision literature. Assessment of SIgnificant ZERo crossings of derivatives results in the SiZer map, a graphical device for display of significance of features with respect to both location and scale. Here scale means level of resolution; that...
• Estimation of the causal effect of a time-varying exposure on the marginal mean of a repeated binary outcome - Comment AI翻译
  作者：Wasserman, L
  作者单位：Carnegie Mellon University