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Articles 1 - 6 of 6
Full-Text Articles in Statistical Models
Marginal Regression Of Gaps Between Recurrent Events, Yijian Huang, Ying Qing Chen
Marginal Regression Of Gaps Between Recurrent Events, Yijian Huang, Ying Qing Chen
U.C. Berkeley Division of Biostatistics Working Paper Series
Recurrent event data typically exhibit the phenomenon of intra-individual correlation, owing to not only observed covariates but also random effects. In many applications, the population can be reasonably postulated as a heterogeneous mixture of individual renewal processes, and the inference of interest is the effect of individual-level covariates. In this article, we suggest and investigate a marginal proportional hazards model for gaps between recurrent events. A connection is established between observed gap times and clustered survival data, however, with informative cluster size. We then derive a novel and general inference procedure for the latter, based on a functional formulation of …
Theater-Level Stochastic Air-To-Air Engagement Modeling Via Event Occurrence Networks Using Piecewise Polynomial Approximation, David R. Denhard
Theater-Level Stochastic Air-To-Air Engagement Modeling Via Event Occurrence Networks Using Piecewise Polynomial Approximation, David R. Denhard
Theses and Dissertations
This dissertation investigates a stochastic network formulation termed an event occurrence network (EON). EONs are graphical representations of the superposition of several terminating counting processes. An EON arc represents the occurrence of an event from a group of (sequential) events before the occurrence of events from other event groupings. Events between groups occur independently, but events within a group occur sequentially. A set of arcs leaving a node is a set of competing events, which are probabilistically resolved by order relations. An important EON metric is the probability of being at a particular node or set of nodes at time …
Identification Of Regulatory Elements Using A Feature Selection Method, Sunduz Keles, Mark J. Van Der Laan, Michael B. Eisen
Identification Of Regulatory Elements Using A Feature Selection Method, Sunduz Keles, Mark J. Van Der Laan, Michael B. Eisen
U.C. Berkeley Division of Biostatistics Working Paper Series
Many methods have been described to identify regulatory motifs in the transcription control regions of genes that exhibit similar patterns of gene expression across a variety of experimental conditions. Here we focus on a single experimental condition, and utilize gene expression data to identify sequence motifs associated with genes that are activated under this experimental condition. We use a linear model with two way interactions to model gene expression as a function of sequence features (words) present in presumptive transcription control regions. The most relevant features are selected by a feature selection method called stepwise selection with monte carlo cross …
Hierarchical Modeling For Integrated Environmental Assessments, Raymond O'Connor, Deidre Mageean
Hierarchical Modeling For Integrated Environmental Assessments, Raymond O'Connor, Deidre Mageean
University of Maine Office of Research Administration: Grant Reports
The distribution of biotic resources over large spatial extents is often a function of climate, of land-use, and of the demographics of the human population but these different classes of independent variables have different spatial scales for their action. One approach to the integration of these effects across scales is to use hierarchical models that incorporate contingencies and constraints in effects. This project seeks to develop such a modeling paradigm by use of classification and regression trees (CART). The hexagonal grid of the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program is used as the spatial grid, with about …
Testing For Asymmetry In Economic Time Series Using Bootstrap Methods, Claudio Lupi, Patrizia Ordine
Testing For Asymmetry In Economic Time Series Using Bootstrap Methods, Claudio Lupi, Patrizia Ordine
Claudio Lupi
In this paper we show that phase-scrambling bootstrap offers a natural framework for asymmetry testing in economic time series. A comparison with other bootstrap schemes is also sketched. A Monte Carlo analysis is carried out to evaluate the size and power properties of the phase-scrambling bootstrap-based test.
Mixture Hazards Models With Additive Random Effects Accounting For Treatment Effectiveness Lag Time, Ying Qing Chen, C. A. Rohde, M.-C. Wang
Mixture Hazards Models With Additive Random Effects Accounting For Treatment Effectiveness Lag Time, Ying Qing Chen, C. A. Rohde, M.-C. Wang
U.C. Berkeley Division of Biostatistics Working Paper Series
In many clinical trials to evaluate treatment efficacy, it is believed that there may exist latent treatment effectiveness lag times after which medical treatment procedure or chemical compound would be in full effect. In this article, semiparametric regression models are proposed and studied for estimating the treatment effect accounting for such latent lag times. The new models take advantage of the invariance property of the additive hazards model in marginalising over an additive latent variable; parameters in the models are thus easily estimated and interpreted, while the flexibility of not having to specify the baseline hazard function is preserved. Monte …