53 research outputs found
Bayesian Synthesis: Combining subjective analyses, with an application to ozone data
Bayesian model averaging enables one to combine the disparate predictions of
a number of models in a coherent fashion, leading to superior predictive
performance. The improvement in performance arises from averaging models that
make different predictions. In this work, we tap into perhaps the biggest
driver of different predictions---different analysts---in order to gain the
full benefits of model averaging. In a standard implementation of our method,
several data analysts work independently on portions of a data set, eliciting
separate models which are eventually updated and combined through a specific
weighting method. We call this modeling procedure Bayesian Synthesis. The
methodology helps to alleviate concerns about the sizable gap between the
foundational underpinnings of the Bayesian paradigm and the practice of
Bayesian statistics. In experimental work we show that human modeling has
predictive performance superior to that of many automatic modeling techniques,
including AIC, BIC, Smoothing Splines, CART, Bagged CART, Bayes CART, BMA and
LARS, and only slightly inferior to that of BART. We also show that Bayesian
Synthesis further improves predictive performance. Additionally, we examine the
predictive performance of a simple average across analysts, which we dub Convex
Synthesis, and find that it also produces an improvement.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS444 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Bayesian models to adjust for response bias in survey data for estimating rape and domestic violence rates from the NCVS
It is difficult to accurately estimate the rates of rape and domestic
violence due to the sensitive nature of these crimes. There is evidence that
bias in estimating the crime rates from survey data may arise because some
women respondents are "gagged" in reporting some types of crimes by the use of
a telephone rather than a personal interview, and by the presence of a spouse
during the interview. On the other hand, as data on these crimes are collected
every year, it would be more efficient in data analysis if we could identify
and make use of information from previous data. In this paper we propose a
model to adjust the estimates of the rates of rape and domestic violence to
account for the response bias due to the "gag" factors. To estimate parameters
in the model, we identify the information that is not sensitive to time and
incorporate this into prior distributions. The strength of Bayesian estimators
is their ability to combine information from long observational records in a
sensible way. Within a Bayesian framework, we develop an
Expectation-Maximization-Bayesian (EMB) algorithm for computation in analyzing
contingency table and we apply the jackknife to estimate the accuracy of the
estimates. Our approach is illustrated using the yearly crime data from the
National Crime Victimization Survey. The illustration shows that compared with
the classical method, our model leads to more efficient estimation but does not
require more complicated computation.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS160 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Yielding and hardening of flexible fiber packings during triaxial compression
This paper examines the mechanical response of flexible fiber packings
subject to triaxial compression. Short fibers yield in a manner similar to
typical granular materials in which the deviatoric stress remains nearly
constant with increasing strain after reaching a peak value. Interestingly,
long fibers exhibit a hardening behavior, where the stress increases rapidly
with increasing strain at large strains and the packing density continuously
increases. Phase diagrams for classifying the bulk mechanical response as
yielding, hardening, or a transition regime are generated as a function of the
fiber aspect ratio, fiber-fiber friction coefficient, and confining pressure.
Large fiber aspect ratio, large fiber-fiber friction coefficient, and large
confining pressure promote hardening behavior. The hardening packings can
support much larger loads than the yielding packings contributing to the
stability and consolidation of the granular structure, but larger internal
axial forces occur within fibers.Comment: 14 pages, 4 figure
One-year implant survival following lateral window sinus augmentation using plasma rich in growth factors (PRGF) : a retrospective study
The aim of this study was to assess one-year implant survival after lateral window sinus augmentation using PRGF combined with various bone grafting materials. This was a retrospective chart review and radiographic analysis of patients that had undergone lateral window sinus augmentation with PRGF and had dental implants placed at least 6 months post augmentation. All implants included were followed up for at least one year after placement. Demographic, sinus and implant related characteristics (residual ridge height, sinus membrane perforation, type of graft material, implant length and width and ISQ at placement) were analyzed. A total of 31 patients with 39 sinus augmentations and 48 implants were included. The mean follow up was 22.8 ± 9.9 months. Implant survival was 95.8%, with 2 implants overall failing. Among all the variables assessed, the only one found to be associated with an increased risk for implant failure was the use of xenograft as bone grafting material in the sinus. Within the limitations of this study, dental implants placed in maxillary sinuses grafted with PRGF in combination with bone grafting materials, exhibit high implant survival rates after at least one year follow up
Discrete Element Method Model of Elastic Fiber Uniaxial Compression
A flexible fiber model based on the discrete element method (DEM) is
presented and validated for the simulation of uniaxial compression of flexible
fibers in a cylindrical container. It is found that the contact force models in
the DEM simulations have a significant impact on compressive forces exerted on
the fiber bed. Only when the geometry-dependent normal contact force model and
the static friction model are employed, the simulation results are in good
agreement with experimental results. Systematic simulation studies show that
the compressive force initially increases and eventually saturates with an
increase in the fiber-fiber friction coefficient, and the fiber-fiber contact
forces follow a similar trend. The compressive force and lateral
shear-to-normal stress ratio increase linearly with increasing fiber-wall
friction coefficient. In uniaxial compression of frictional fibers, more static
friction contacts occur than dynamic friction contacts with static friction
becoming more predominant as the fiber-fiber friction coefficient increases.Comment: 30 pages, 14 figures, submitted for publicatio
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Exploring racial disparity in obesity: A mediation analysis considering geo-coded environmental factors.
Research shows aconsistent racial disparity in obesity between white and black adults in the United States. Accounting for the disparity is a challenge given the variety of the contributing factors, the nature of the association, and the multilevel relationships among the factors. We used the multivariable mediation analysis (MMA) method to explore the racial disparity in obesity considering not only the individual behavior but also geospatially derived environmental risk factors. Results from generalized linear models (GLM) were compared with those from multiple additive regression trees (MART) which allow for hierarchical data structure, and fitting of nonlinear and complex interactive relationships. As results, both individual and geographically defined factors contributed to the racial disparity in obesity. MART performed better than GLM models in that MART explained a larger proportion of the racial disparity in obesity. However, there remained disparities that cannot be explained by factors collected in this study
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