Bayesian Pollution Source Apportionment Incorporating Multiple Simultaneous Measurements,
2012
Brigham Young University - Provo
Bayesian Pollution Source Apportionment Incorporating Multiple Simultaneous Measurements, Jonathan Casey Christensen
Theses and Dissertations
We describe a method to estimate pollution profiles and contribution levels for distinct prominent pollution sources in a region based on daily pollutant concentration measurements from multiple measurement stations over a period of time. In an extension of existing work, we will estimate common source profiles but distinct contribution levels based on measurements from each station. In addition, we will explore the possibility of extending existing work to allow adjustments for synoptic regimes—large scale weather patterns which may effect the amount of pollution measured from individual sources as well as for particular pollutants. For both extensions we propose Bayesian methods …
Predicting Maximal Oxygen Consumption (Vo2max) Levels In Adolescents,
2012
Brigham Young University - Provo
Predicting Maximal Oxygen Consumption (Vo2max) Levels In Adolescents, Brent A. Shepherd
Theses and Dissertations
Maximal oxygen consumption (VO2max) is considered by many to be the best overall measure of an individual's cardiovascular health. Collecting the measurement, however, requires subjecting an individual to prolonged periods of intense exercise until their maximal level, the point at which their body uses no additional oxygen from the air despite increased exercise intensity, is reached. Collecting VO2max data also requires expensive equipment and great subject discomfort to get accurate results. Because of this inherent difficulty, it is often avoided despite its usefulness. In this research, we propose a set of Bayesian hierarchical models to predict VO2max levels in adolescents, …
Bootstrap-Based Inference On The Difference In The Means Of Two Correlated Functional Processes,
2012
Bloomberg School of Public Health, Department of Biostatistics, Johns Hopkins
Bootstrap-Based Inference On The Difference In The Means Of Two Correlated Functional Processes, Ciprian M. Crainiceanu, Ana-Maria Staicu, Shubankar Ray, Naresh Punjabi
Johns Hopkins University, Dept. of Biostatistics Working Papers
Nonparametric inference methods on the mean difference between two correlated Functional processes are proposed. We compare methods that: 1) incorporate different levels of smoothing of the mean and covariance; 2) preserve the sampling design; and 3) use parametric and nonparametric estimation of the mean functions. We apply our method to estimating the mean difference between average normalized δ-power of sleep electroencephalograms for 51 subjects with severe sleep apnea and 51 matched controls in the first 4 hours after sleep onset. Data are obtained from the Sleep Heart Health Study (SHHS), the largest community cohort study of sleep. While methods are …
Robustness Of Measures Of Interaction To Unmeasured Confounding,
2012
Harvard University
Robustness Of Measures Of Interaction To Unmeasured Confounding, Eric J. Tchetgen Tchetgen, Tyler J. Vanderweele
COBRA Preprint Series
In this paper, we study the impact of unmeasured confounding on inference about a two-way interaction in a mean regression model with identity, log or logit link function. Necessary and sufficient conditions are established for a two-way interaction to be nonparametrically identified from the observed data, despite unmeasured confounding for the factors defining the interaction. A lung cancer data application illustrates the results.
The Effect Of Smoking On Tuberculosis Incidence In Burdened Countries,
2012
Brigham Young University - Provo
The Effect Of Smoking On Tuberculosis Incidence In Burdened Countries, Natalie Noel Ellison
Theses and Dissertations
It is estimated that one third of the world's population is infected with tuberculosis. Though once thought a "dead" disease, tuberculosis is very much alive. The rise of drug resistant strains of tuberculosis, and TB-HIV coinfection have made tuberculosis an even greater worldwide threat. While HIV, poverty, and public health infrastructure are historically assumed to affect the burden of tuberculosis, recent research has been done to implicate smoking in this list. This analysis involves combining data from multiple sources in order determine if smoking is a statistically significant factor in predicting the number of incident tuberculosis cases in a country. …
Does Secondary Inflammatory Breast Cancer Represent Post-Surgical Metastatic Disease?,
2012
George Washington University
Does Secondary Inflammatory Breast Cancer Represent Post-Surgical Metastatic Disease?, Salman Hashmi, Ladan Zolfaghari, Paul H. Levine
Epidemiology Faculty Publications
The phenomenon of accelerated tumor growth following surgery has been observed repeatedly and merits further study. Inflammatory breast carcinoma (IBC) is widely recognized as an extremely aggressive malignancy characterized by micrometastasis at the time of diagnosis, with one interesting subgroup defined as secondary IBC where pathologically identifiable IBC appears after surgical treatment of a primary non-inflammatory breast cancer. One possible mechanism can be related to the stimulation of dormant micrometastasis through local angiogenesis occurring as part of posttraumatic healing. In this report, we review cases of secondary IBC and others where localized trauma was followed by the appearance of IBC …
A Cautionary Note On Generalized Linear Models For Covariance Of Unbalanced Longitudinal Data,
2012
Texas A & M University
A Cautionary Note On Generalized Linear Models For Covariance Of Unbalanced Longitudinal Data, Jianhua Z. Huang, Min Chen, Mehdi Maadooliat, Mohsen Pourahmadi
Mathematics, Statistics and Computer Science Faculty Research and Publications
Missing data in longitudinal studies can create enormous challenges in data analysis when coupled with the positive-definiteness constraint on a covariance matrix. For complete balanced data, the Cholesky decomposition of a covariance matrix makes it possible to remove the positive-definiteness constraint and use a generalized linear model setup to jointly model the mean and covariance using covariates (Pourahmadi, 2000). However, this approach may not be directly applicable when the longitudinal data are unbalanced, as coherent regression models for the dependence across all times and subjects may not exist. Within the existing generalized linear model framework, we show how to overcome …
Application Of Inter-Die Rank Statistics In Defect Detection,
2012
Portland State University
Application Of Inter-Die Rank Statistics In Defect Detection, Vivek Bakshi
Dissertations and Theses
This thesis presents a statistical method to identify the test escapes. Test often acquires parametric measurements as a function of logical state of a chip. The usual method of classifying chips as pass or fail is to compare each state measurement to a test limit. Subtle manufacturing defects are escaping the test limits due to process variations in deep sub-micron technologies which results in mixing of healthy and faulty parametric test measurements. This thesis identifies the chips with subtle defects by using rank order of the parametric measurements. A hypothesis is developed that a defect is likely to disturb the …
A Common Framework For Restriction Semigroups And Regular *-Semigroups,
2012
Marquette University
A Common Framework For Restriction Semigroups And Regular *-Semigroups, Peter R. Jones
Mathematics, Statistics and Computer Science Faculty Research and Publications
Left restriction semigroups have appeared at the convergence of several flows of research, including the theories of abstract semigroups, of partial mappings, of closure operations and even in logic. For instance, they model unary semigroups of partial mappings on a set, where the unary operation takes a map to the identity map on its domain. This perspective leads naturally to dual and two-sided versions of the restriction property. From a varietal perspective, these classes of semigroups–more generally, the corresponding classes of Ehresmann semigroups–derive from reducts of inverse semigroups, now taking a to a+=aa−1 (or, dually, …
When 10 Trials Are Better Than 1000: An Evidentiary Perspective On Trial Sampling,
2012
Vanderbilt University Law School
When 10 Trials Are Better Than 1000: An Evidentiary Perspective On Trial Sampling, Edward K. Cheng
Vanderbilt Law School Faculty Publications
In many mass tort cases, separately trying all individual claims is impractical, and thus a number of trial courts and commentators have explored the use of statistical sampling as a way of efficiently processing claims. Most discussions on the topic, however, implicitly assume that sampling is a “second best” solution: individual trials are preferred for accuracy, and sampling only justified under extraordinary circumstances. This Essay explores whether this assumption is really true. While intuitively one might think that individual trials would be more accurate at estimating liability than extrapolating from a subset of cases, the Essay offers three ways in …
On A Logistic Mixed Model Formulation Of A Quadratic Exponential Model For Correlated Binary Outcomes,
2012
Harvard University
On A Logistic Mixed Model Formulation Of A Quadratic Exponential Model For Correlated Binary Outcomes, Eric J. Tchetgen Tchetgen
Harvard University Biostatistics Working Paper Series
No abstract provided.
C2bat: A Novel Method For Association Between Ge- Netic Markers And Multiple Phenotypes,
2012
Harvard School of Public Health
C2bat: A Novel Method For Association Between Ge- Netic Markers And Multiple Phenotypes, Melissa Naylor, Christoph Lange
Harvard University Biostatistics Working Paper Series
The purpose of this technical report is to describe a novel method developed to detect association between a genetic marker and multiple phenotypes. In order to obtain a one-degree of freedom test, a generalized principal component approach is suggested that aggregates the information about the genetic effect in the first prin- cipal component, while the remain principal components contain only environment noise. A limited simulation study is done validating the method. For scenarios in which the genetic effect is constant across all measurements and there is no envi- ronmental correlation between the measurements, preliminary results suggest that this method has …
Maximizing Network Lifetime On The Line With Adjustable Sensing Ranges,
2012
The Doctorate-Granting Institution of the City University of New York
Maximizing Network Lifetime On The Line With Adjustable Sensing Ranges, Amotz Bar-Noy, Ben Baumer
Statistical and Data Sciences: Faculty Publications
Given n sensors on a line, each of which is equipped with a unit battery charge and an adjustable sensing radius, what schedule will maximize the lifetime of a network that covers the entire line? Trivially, any reasonable algorithm is at least a 1/2-approximation, but we prove tighter bounds for several natural algorithms. We focus on developing a linear time algorithm that maximizes the expected lifetime under a random uniform model of sensor distribution. We demonstrate one such algorithm that achieves an average-case approximation ratio of almost 0.9. Most of the algorithms that we consider come from a family based …
Avoiding Boundary Estimates In Linear Mixed Models Through Weakly Informative Priors,
2012
University of California, Berkeley
Avoiding Boundary Estimates In Linear Mixed Models Through Weakly Informative Priors, Yeojin Chung, Sophia Rabe-Hesketh, Andrew Gelman, Jingchen Liu, Vincent Dorie
U.C. Berkeley Division of Biostatistics Working Paper Series
Variance parameters in mixed or multilevel models can be difficult to estimate, especially when the number of groups is small. We propose a maximum penalized likelihood approach which is equivalent to estimating variance parameters by their marginal posterior mode, given a weakly informative prior distribution. By choosing the prior from the gamma family with at least 1 degree of freedom, we ensure that the prior density is zero at the boundary and thus the marginal posterior mode of the group-level variance will be positive. The use of a weakly informative prior allows us to stabilize our estimates while remaining faithful …
On A Closed-Form Doubly Robust Estimator Of The Adjusted Odds Ratio For A Binary Exposure,
2012
Harvard University
On A Closed-Form Doubly Robust Estimator Of The Adjusted Odds Ratio For A Binary Exposure, Eric J. Tchetgen Tchetgen
Harvard University Biostatistics Working Paper Series
No abstract provided.
Formulae For Causal Mediation Analysis In An Odds Ratio Context Without A Normality Assumption For The Continuous Mediator,
2012
Harvard School of Public Health
Formulae For Causal Mediation Analysis In An Odds Ratio Context Without A Normality Assumption For The Continuous Mediator, Eric J. Tchetgen Tchetgen
Harvard University Biostatistics Working Paper Series
No abstract provided.
A Cautionary Note On Specification Of The Correlation Structure In Inverse-Probability-Weighted Estimation For Repeated Measures,
2012
Harvard University
A Cautionary Note On Specification Of The Correlation Structure In Inverse-Probability-Weighted Estimation For Repeated Measures, Eric J. Tchetgen Tchetgen, M. Maria Glymour, Jennifer Weuve, James Robins
Harvard University Biostatistics Working Paper Series
No abstract provided.
On Parametrization, Robustness And Sensitivity Analysis In A Marginal Structural Cox Proportional Hazards Model For Point Exposure,
2012
Harvard University
On Parametrization, Robustness And Sensitivity Analysis In A Marginal Structural Cox Proportional Hazards Model For Point Exposure, Eric J. Tchetgen Tchetgen, James M. Robins
Harvard University Biostatistics Working Paper Series
No abstract provided.
Multiple-Robust Estimation Of An Odds Ratio Interaction,
2012
Harvard University
Multiple-Robust Estimation Of An Odds Ratio Interaction, Eric J. Tchetgen Tchetgen
Harvard University Biostatistics Working Paper Series
No abstract provided.
Inverse Odds Ratio-Weighted Estimation For Causal Mediation Analysis,
2012
Harvard University
Inverse Odds Ratio-Weighted Estimation For Causal Mediation Analysis, Eric J. Tchetgen Tchetgen
Harvard University Biostatistics Working Paper Series
No abstract provided.
