07.05.2013 | John D. Kalbfleisch, Douglas E. Schaubel, Yining Ye, Qi Gong, Biometrics, 2013

Abstract Summary In clinical and observational studies, the event of interest can often recur on the same subject. In a more complicated situation, there exists a terminal event (e.g., death) which stops the recurrent event process. In many such instances, the terminal event is ...

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02.05.2013 | Qi Gong, Douglas E. Schaubel, Biometrics, 2013

Abstract Summary We propose semiparametric methods for estimating the effect of a time‐dependent covariate on treatment‐free survival. The data structure of interest consists of a longitudinal sequence of measurements and a potentially censored survival time. The factor of interest ...

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23.04.2013 | Samuel D. Lendle, Meenakshi S. Subbaraman, Mark J. van der Laan, Biometrics, 2013

Abstract Summary The natural direct effect (NDE), or the effect of an exposure on an outcome if an intermediate variable was set to the level it would have been in the absence of the exposure, is often of interest to investigators. In general, the statistical parameter associated ...

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22.04.2013 | Anindya Bhadra, Bani K. Mallick, Biometrics, 2013

Abstract Summary We describe a Bayesian technique to (a) perform a sparse joint selection of significant predictor variables and significant inverse covariance matrix elements of the response variables in a high‐dimensional linear Gaussian sparse seemingly unrelated regression (SSUR) ...

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22.04.2013 | Michelle Ross, Jon Wakefield, Biometrics, 2013

Abstract Summary In this article, we consider two‐phase sampling in the situation in which all covariates are categorical. Two‐phase designs are appealing from an efficiency perspective since they allow sampling to be concentrated in informative cells. A number of likelihood‐based ...

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05.04.2013 | Hongtu Zhu, Biometrics, 2013

EDITOR: GUILHERME J. M. ROSA Statistics of Medical Imaging (T. Lei) Hongtu Zhu Bayesian Smoothing and Regression for Longitudinal, Spatial and Event History Data (L. Fahrmeir and T. Kneib) Renato Assunção Targeted Learning (M. van der Laan and S. Rose) Andrea ...

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05.04.2013 | Davide Altomare, Guido Consonni, Luca La Rocca, Biometrics, 2013

Abstract Summary Directed acyclic graphical (DAG) models are increasingly employed in the study of physical and biological systems to model direct influences between variables. Identifying the graph from data is a challenging endeavor, which can be more reasonably tackled if the ...

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04.04.2013 | Abbas Khalili, Shili Lin, Biometrics, 2013

Abstract Summary Feature (variable) selection has become a fundamentally important problem in recent statistical literature. Sometimes, in applications, many variables are introduced to reduce possible modeling biases, but the number of variables a model can accommodate is often limited ...

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15.03.2013 | Angela Schörgendorfer, Adam J. Branscum, Timothy E. Hanson, Biometrics, 2013

Summary Logistic regression is a popular tool for risk analysis in medical and population health science. With continuous response data, it is common to create a dichotomous outcome for logistic regression analysis by specifying a threshold for positivity. Fitting a linear regression to the ...

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14.03.2013 | Colin O. Wu, Gang Zheng, Minjung Kwak, Biometrics, 2013

Summary Genetic association studies in practice often involve multiple traits resulting from a common disease mechanism, and samples for such studies are often stratified based on some trait outcomes. In such situations, statistical methods using only one of these traits may be inadequate ...

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