James-Stein Estimation And The Benjamini-Hochberg Procedure,
2012
Penn State University
James-Stein Estimation And The Benjamini-Hochberg Procedure, Debashis Ghosh
Debashis Ghosh
For the problem of multiple testing, the Benjamini-Hochberg (B-H) procedure has become a very popular method in applications. Based on a spacings theory representation of the B-H procedure, we are able to motivate the use of shrinkage estimators for modifying the B-H procedure. Several generalizations in the paper are discussed, and the methodology is applied to real and simulated datasets.
Shrinkage In Adaptive Procedures For False Discovery Rate Estimation In Multiple Testing: Structure And Synthesis,
2012
Penn State University
Shrinkage In Adaptive Procedures For False Discovery Rate Estimation In Multiple Testing: Structure And Synthesis, Debashis Ghosh
Debashis Ghosh
There has been much interest in the study of adaptive estimation procedures for controlling the false discovery rate (FDR). In this article, we take the direct approach to estimation of FDR of Storey (2002) and show how it can reexpressed as a particular type of shrinkage estimator. This representation leads to natural conditions on finite-sample FDR control for a general class of shrinkage estimators. In addition, many previous proposals from the literature can be unified under this framework for which finite-sample FDR results can be developed. Some asymptotic results are also provided.
An Epidemiological Model Of Rift Valley Fever With Spatial Dynamics,
2012
Old Dominion University
An Epidemiological Model Of Rift Valley Fever With Spatial Dynamics, Tianchan Niu, Holly D. Gaff, Yiannis E. Papelis, David M. Hartley
Biological Sciences Faculty Publications
As a category A agent in the Center for Disease Control bioterrorism list, Rift Valley fever (RVF) is considered a major threat to the United States (USA). Should the pathogen be intentionally or unintentionally introduced to the continental USA, there is tremendous potential for economic damages due to loss of livestock, trade restrictions, and subsequent food supply chain disruptions. We have incorporated the effects of space into a mathematical model of RVF in order to study the dynamics of the pathogen spread as affected by the movement of humans, livestock, and mosquitoes. The model accounts for the horizontal transmission of …
Introducing Functional Data Analysis To Neuroimaging, And Vice Versa,
2011
New York University
Introducing Functional Data Analysis To Neuroimaging, And Vice Versa, Philip T. Reiss
Philip T. Reiss
No abstract provided.
The Use Of Imputed Values In The Meta-Analysis Of Genome-Wide Association Studies.,
2011
Fred Hutchinson Cancer Research Center
The Use Of Imputed Values In The Meta-Analysis Of Genome-Wide Association Studies., Shuo Jiao, Li Hsu, Carolyn Hutter, Ulrike Peters
Shuo Jiao
In genome-wide association studies (GWAS), it is a common practice to impute the genotypes of untyped single nucleotide polymorphism (SNP) by exploiting the linkage disequilibrium structure among SNPs. The use of imputed genotypes improves genome coverage and makes it possible to perform meta-analysis combining results from studies genotyped on different platforms. A popular way of using imputed data is the "expectation-substitution" method, which treats the imputed dosage as if it were the true genotype. In current practice, the estimates given by the expectation-substitution method are usually combined using inverse variance weighting (IVM) scheme in meta-analysis. However, the IVM is not …
Meta-Analysis Of New Genome-Wide Association Studies Of Colorectal Cancer Risk.,
2011
SelectedWorks
Meta-Analysis Of New Genome-Wide Association Studies Of Colorectal Cancer Risk.
Shuo Jiao
Colorectal cancer is the second leading cause of cancer death in developed countries. Genome-wide association studies (GWAS) have successfully identified novel susceptibility loci for colorectal cancer. To follow up on these findings, and try to identify novel colorectal cancer susceptibility loci, we present results for GWAS of colorectal cancer (2,906 cases, 3,416 controls) that have not previously published main associations. Specifically, we calculated odds ratios and 95% confidence intervals using log-additive models for each study. In order to improve our power to detect novel colorectal cancer susceptibility loci, we performed a meta-analysis combining the results across studies. We selected the …
Massively Parallel Nonparametrics [Hds 2011 Slides],
2011
New York University
Massively Parallel Nonparametrics [Hds 2011 Slides], Philip T. Reiss, Lei Huang
Philip T. Reiss
No abstract provided.
Social Marketing, Stages Of Change, And Public Health Smoking Interventions,
2011
University of Washington
Social Marketing, Stages Of Change, And Public Health Smoking Interventions, Paula Diehr
Paula Diehr
As a "thought experiment," the authors used a modified stages of change model for smoking to define homogeneous segments within various hypothetical populations. The authors then estimated the population effect of public health interventions that targeted the different segments. Under most assumptions, interventions that emphasized primary and secondary prevention, by targeting the Never Smoker, Maintenance, or Action segments, resulted in the highest nonsmoking life expectancy. This result is consistent with both social marketing and public health principles. Although the best thing for an individual smoker is to stop smoking, the greatest public health benefit is achieved by interventions that target …
Flexible Dependence Of Functional Responses On Scalar Predictors,
2011
New York University
Flexible Dependence Of Functional Responses On Scalar Predictors, Philip T. Reiss, Lei Huang
Philip T. Reiss
No abstract provided.
Prevalence Of Piscine Myocarditis Virus (Pmcv) In Marine Fish Species,
2011
Norwegian Veterinary Institute
Prevalence Of Piscine Myocarditis Virus (Pmcv) In Marine Fish Species, Torstein Tengs Dr.
Dr. Torstein Tengs
No abstract.
Compound Treatments, Transportability, And The Structural Causal Model: The Power And Simplicity Of Causal Graphs.,
2011
University of California, Berkeley
Compound Treatments, Transportability, And The Structural Causal Model: The Power And Simplicity Of Causal Graphs., Maya Petersen
Maya Petersen
No abstract provided.
Generalized Benjamini-Hochberg Procedures Using Spacings,
2011
Penn State University
Generalized Benjamini-Hochberg Procedures Using Spacings, Debashis Ghosh
Debashis Ghosh
For the problem of multiple testing, the Benjamini-Hochberg (B-H) procedure has become a very popular method in applications. We show how the B-H procedure can be interpreted as a test based on the spacings corresponding to the p-value distributions. Using this equivalence, we develop a class of generalized B-H procedures that maintain control of the false discovery rate in finite-samples. We also consider the effect of correlation on the procedure; simulation studies are used to illustrate the methodology.
Software For Assumption Weighting For Meta-Analysis Of Genomic Data,
2011
Penn State University
Software For Assumption Weighting For Meta-Analysis Of Genomic Data, Debashis Ghosh, Yihan Li
Debashis Ghosh
This is the software that accompanies Li and Ghosh, "Assumption weighting for incorporating heterogeneity into meta-analysis of genomic data."
A Causal Framework For Surrogate Endpoints With Semi-Competing Risks Data,
2011
Penn State University
A Causal Framework For Surrogate Endpoints With Semi-Competing Risks Data, Debashis Ghosh
Debashis Ghosh
In this note, we address the problem of surrogacy using a causal modelling framework that differs substantially from the potential outcomes model that pervades the biostatistical literature. The framework comes from econometrics and conceptualizes direct effects of the surrogate endpoint on the true endpoint. While this framework can incorporate the so-called semi-competing risks data structure, we also derive a fundamental non-identifiability result. Relationships to existing causal modelling frameworks are also discussed.
Propensity Score Modelling In Observational Studies Using Dimension Reduction Methods,
2011
Penn State University
Propensity Score Modelling In Observational Studies Using Dimension Reduction Methods, Debashis Ghosh
Debashis Ghosh
Conditional independence assumptions are very important in causal inference modelling as well as in dimension reduction methodologies. These are two very strikingly different statistical literatures, and we study links between the two in this article. The concept of covariate sufficiency plays an important role, and we provide theoretical justication when dimension reduction and partial least squares methods will allow for valid causal inference to be performed. The methods are illustrated with application to a medical study and to simulated data.
Computational Analyses Of The Uptake And Distribution Of Carbon Monoxide (Co) In Human Subjects,
2011
University of Kentucky
Computational Analyses Of The Uptake And Distribution Of Carbon Monoxide (Co) In Human Subjects, Kinnera Chada
University of Kentucky Doctoral Dissertations
Carbon monoxide (CO) is an odorless, colorless, tasteless gas that binds to hemoglobin with high affinity. This property underlies the use of low doses of CO to determine hemoglobin mass (MHb) in the fields of clinical and sports medicine. However, hemoglobin bound to CO is unable to transport oxygen and exposure to high CO concentrations is a significant environmental and occupational health concern. These contrasting aspects of CO—clinically useful in low doses but potentially lethal in higher doses—mandates a need for a quantitative understanding of the temporal profiles of the uptake and distribution of CO …
A Computational Framework For Proteome-Wide Pursuit And Prediction Of Metalloproteins Using Icp-Ms And Ms/Ms Data,
2011
Philadelphia College of Osteopathic Medicine
A Computational Framework For Proteome-Wide Pursuit And Prediction Of Metalloproteins Using Icp-Ms And Ms/Ms Data, W. Andrew Lancaster, Jeremy L. Praissman, Farris L. Poole, Aleksandar Cvetkovic, Angeli Lal Menon, Joseph W. Scott, Francis E. Jenney, Michael P. Thorgersen, Ewa Kalisiak, Junefredo V. Apon, Sunia A. Trauger, Gary Siuzdak, John A. Tainer, Michael W. W. Adams
PCOM Scholarly Papers
BACKGROUND: Metal-containing proteins comprise a diverse and sizable category within the proteomes of organisms, ranging from proteins that use metals to catalyze reactions to proteins in which metals play key structural roles. Unfortunately, reliably predicting that a protein will contain a specific metal from its amino acid sequence is not currently possible. We recently developed a generally-applicable experimental technique for finding metalloproteins on a genome-wide scale. Applying this metal-directed protein purification approach (ICP-MS and MS/MS based) to the prototypical microbe Pyrococcus furiosus conclusively demonstrated the extent and diversity of the uncharacterized portion of microbial metalloproteomes since a majority of the …
An Algorithm For Facial Expression Recognition To Assist Handicapped Individuals With Eating Disabilities,
2011
California State University, San Bernardino
An Algorithm For Facial Expression Recognition To Assist Handicapped Individuals With Eating Disabilities, Anthony Rudolph De La Loza
Theses Digitization Project
The purpose of this thesis is to describe an algorithm and implement a software system based upon facial expression recognition that will accurately determine the specific need of a handicapped individual pertaining to the eating process. Then based upon that need, determine the appropriate action that should be executed. This thesis aims to present a solution to allow a special needs individual to eat more efficienty and foster independence, while providing a platform for further research in the area of feature detection to assist individuals with special needs.
The Cardiac Atlas Project--An Imaging Database For Computational Modeling And Statistical Atlases Of The Heart,
2011
Touro College
The Cardiac Atlas Project--An Imaging Database For Computational Modeling And Statistical Atlases Of The Heart, Carissa G. Fonseca, Michael Backhaus, David A. Bluemke, Randall D. Britten, Jae Do Chung, Brett R. Cowan, Alan H. Kadish
Office of the President Publications and Research
MOTIVATION: Integrative mathematical and statistical models of cardiac anatomy and physiology can play a vital role in understanding cardiac disease phenotype and planning therapeutic strategies. However, the accuracy and predictive power of such models is dependent upon the breadth and depth of noninvasive imaging datasets. The Cardiac Atlas Project (CAP) has established a large-scale database of cardiac imaging examinations and associated clinical data in order to develop a shareable, web-accessible, structural and functional atlas of the normal and pathological heart for clinical, research and educational purposes. A goal of CAP is to facilitate collaborative statistical analysis of regional heart shape …
Extracting Information From Functional Connectivity Maps Via Function-On-Scalar Regression,
2010
New York University
Extracting Information From Functional Connectivity Maps Via Function-On-Scalar Regression, Philip T. Reiss, Maarten Mennes, Eva Petkova, Lei Huang, Matthew J. Hoptman, Bharat B. Biswal, Stanley J. Colcombe, Xi-Nian Zuo, Michael P. Milham
Lei Huang
Functional connectivity of an individual human brain is often studied by acquiring a resting state functional magnetic resonance imaging scan, and mapping the correlation of each voxel's BOLD time series with that of a seed region. As large collections of such maps become available, including multisite data sets, there is an increasing need for ways to distill the information in these maps in a readily visualized form. Here we propose a two-step analytic strategy. First, we construct connectivity-distance profiles, which summarize the connectivity of each voxel in the brain as a function of distance from the seed, a functional relationship …
