580 research outputs found

    Modeling multilevel sleep transitional data via Poisson log-linear multilevel models

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    This paper proposes Poisson log-linear multilevel models to investigate population variability in sleep state transition rates. We specifically propose a Bayesian Poisson regression model that is more flexible, scalable to larger studies, and easily fit than other attempts in the literature. We further use hierarchical random effects to account for pairings of individuals and repeated measures within those individuals, as comparing diseased to non-diseased subjects while minimizing bias is of epidemiologic importance. We estimate essentially non-parametric piecewise constant hazards and smooth them, and allow for time varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming piecewise constant hazards. This relationship allows us to synthesize two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed

    Modeling Multilevel Sleep Transitional Data Via Poisson Log-Linear Multilevel Models

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    This paper proposes Poisson log-linear multilevel models to investigate population variability in sleep state transition rates. We specifically propose a Bayesian Poisson regression model that is more flexible, scalable to larger studies, and easily fit than other attempts in the literature. We further use hierarchical random effects to account for pairings of individuals and repeated measures within those individuals, as comparing diseased to non-diseased subjects while minimizing bias is of epidemiologic importance. We estimate essentially non-parametric piecewise constant hazards and smooth them, and allow for time varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming piecewise constant hazards. This relationship allows us to synthesize two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed

    A unified approach to modeling multivariate binary data using copulas over partitions

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    Many seemingly disparate approaches for marginal modeling have been developed in recent years. We demonstrate that many current approaches for marginal modeling of correlated binary outcomes produce likelihoods that are equivalent to the proposed copula-based models herein. These general copula models of underlying latent threshold random variables yield likelihood based models for marginal fixed effects estimation and interpretation in the analysis of correlated binary data. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalized models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate concepts

    RESTRICTED LIKELIHOOD RATIO TESTS FOR FUNCTIONAL EFFECTS IN THE FUNCTIONAL LINEAR MODEL

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    The goal of our article is to provide a transparent, robust, and computationally feasible statistical approach for testing in the context of scalar-on-function linear regression models. In particular, we are interested in testing for the necessity of functional effects against standard linear models. Our methods are motivated by and applied to a large longitudinal study involving diffusion tensor imaging of intracranial white matter tracts in a susceptible cohort. In the context of this study, we conduct hypothesis tests that are motivated by anatomical knowledge and which support recent findings regarding the relationship between cognitive impairment and white matter demyelination. R-code and data are provided to reproduce the application

    MODELING SLEEP FRAGMENTATION IN POPULATIONS OF SLEEP HYPNOGRAMS

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    We introduce methods for the analysis of large populations of sleep architectures (hypnograms) that respect the 5-state 20-transition-type structure defined by the American Academy of Sleep Medicine. By applying these methods to the hypnograms of 5598 subjects from the Sleep Heart Health Study we: 1) provide the firrst analysis of sleep hypnogram data of such size and complexity in a community cohort with a 4-level comorbidity; 2) compare 5-state 20-transition-type sleep to 3-state 6-transition-type sleep for a check of feasibility and information-loss; 3) extend current approaches to multivariate survival data analysis to populations of time-to-transition processes; and 4) provide scalable solutions for data analyses required by the case study. This allows us to provide detailed new insights into the association between sleep apnea and sleep architecture. Supporting R as well as SAS code and data are included in the online supplementary materials

    Relating Body Size to the Rate of Home Range Use in Mammals

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    The area occupied or traversed by an animal is a function of the time period considered, but few empirical estimates of the temporal component of home range use are available. We used a statistic called the "time to independence" to make an ecologically meaningful estimate of the amount of time required for an individual to traverse its home range. Data from 23 species of terrestrial mammals indicated the existence of a sizedependent time scale governing the rate of home range use. Foraging mode influenced the rate of home range use; central place foragers traversed their home ranges approximately five times as rapidly as comparably sized noncentral place foragers. Numerous physiological measures of time are related to body mass raised to the V* power. Our results suggest that the time scale governing the rate of space use by mammals is related similarly to body mass. This relationship permits a more critical examination of factors thought to influence home range size, including habitat productivity and social organization

    2FGL J0846.0+2820: A new neutron star binary with a giant secondary and variable γ\gamma-ray emission

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    We present optical photometric and spectroscopic observations of the likely stellar counterpart to the unassociated \emph{Fermi}-Large Area Telescope (LAT) γ\gamma-ray source 2FGL J0846.0+2820, selected for study based on positional coincidences of optical variables with unassociated LAT sources. Using optical spectroscopy from the SOAR telescope, we have identified a late-G giant in an eccentric (ee = 0.06) 8.133 day orbit with an invisible primary. Modeling the spectroscopy and photometry together lead us to infer a heavy neutron star primary of ∼2M⊙\sim 2 M_{\odot} and a partially stripped giant secondary of ∼0.8M⊙\sim 0.8 M_{\odot}. Hα\alpha emission is observed in some of the spectra, perhaps consistent with the presence of a faint accretion disk. We find the γ\gamma-ray flux of 2FGL J0846.0+2820 dropped substantially in mid-2009, accompanied by an increased variation in the optical brightness, and since then it has not been detected by \emph{Fermi}. The long period and giant secondary are reminiscent of the γ\gamma-ray bright binary 1FGL J1417.7--4407, which hosts a millisecond pulsar apparently in the final stages of the pulsar recycling process. The discovery of 2FGL J0846.0+2820 suggests the identification of a new subclass of millisecond pulsar binaries that are the likely progenitors of typical field millisecond pulsars.Comment: 12 pages, 8 figures, 3 tables. Accepted for publication in Ap
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