Statistics and Probability Commons^™

Accounting For Spatial Autocorrelation In Modeling The Distribution Of Water Quality Variables, Lorrayne Miralha

Theses and Dissertations--Geography

Several studies in hydrology have reported differences in outcomes between models in which spatial autocorrelation (SAC) is accounted for and those in which SAC is not. However, the capacity to predict the magnitude of such differences is still ambiguous. In this thesis, I hypothesized that SAC, inherently possessed by a response variable, influences spatial modeling outcomes. I selected ten watersheds in the USA and analyzed them to determine whether water quality variables with higher Moran’s I values undergo greater increases in the coefficient of determination (R²) and greater decreases in residual SAC (rSAC) after spatial modeling. I compared non-spatial ordinary …

Improved Methods And Selecting Classification Types For Time-Dependent Covariates In The Marginal Analysis Of Longitudinal Data, I-Chen Chen

Theses and Dissertations--Epidemiology and Biostatistics

Generalized estimating equations (GEE) are popularly utilized for the marginal analysis of longitudinal data. In order to obtain consistent regression parameter estimates, these estimating equations must be unbiased. However, when certain types of time-dependent covariates are presented, these equations can be biased unless an independence working correlation structure is employed. Moreover, in this case regression parameter estimation can be very inefficient because not all valid moment conditions are incorporated within the corresponding estimating equations. Therefore, approaches using the generalized method of moments or quadratic inference functions have been proposed for utilizing all valid moment conditions. However, we have found that …

Microrna Expression Patterns In Human Anterior Cingulate And Motor Cortex: A Study Of Dementia With Lewy Bodies Cases And Controls, Peter T. Nelson, Wang-Xia Wang, Sarah A. Janse, Katherine L. Thompson

Sanders-Brown Center on Aging Faculty Publications

Overview

MicroRNAs (miRNAs) have been implicated in neurodegenerative diseases including Parkinson’s disease and Alzheimer’s disease (AD). Here, we evaluated the expression of miRNAs in anterior cingulate (AC; Brodmann area [BA] 24) and primary motor (MO; BA 4) cortical tissue from aged human brains in the University of Kentucky AD Center autopsy cohort, with a focus on dementia with Lewy bodies (DLB).

Methods

RNA was isolated from gray matter of brain samples with pathology-defined DLB, AD, AD+DLB, and low-pathology controls, with n=52 cases initially included (n=23 with DLB), all with low (<4hrs) postmortem intervals. RNA was profiled using Exiqon miRNA microarrays. Quantitative PCR for post-hoc replication was performed on separate cases (n=6 controls) and included RNA isolated from gray matter of MO, AC, primary somatosensory (BA 3), and dorsolateral prefrontal (BA 9) cortical regions.

Results

The miRNA expression patterns differed substantially according to …

Automated Tree-Level Forest Quantification Using Airborne Lidar, Hamid Hamraz

Theses and Dissertations--Computer Science

Traditional forest management relies on a small field sample and interpretation of aerial photography that not only are costly to execute but also yield inaccurate estimates of the entire forest in question. Airborne light detection and ranging (LiDAR) is a remote sensing technology that records point clouds representing the 3D structure of a forest canopy and the terrain underneath. We present a method for segmenting individual trees from the LiDAR point clouds without making prior assumptions about tree crown shapes and sizes. We then present a method that vertically stratifies the point cloud to an overstory and multiple understory tree …

Modeling And Mapping Location-Dependent Human Appearance, Zachary Bessinger

Theses and Dissertations--Computer Science

Human appearance is highly variable and depends on individual preferences, such as fashion, facial expression, and makeup. These preferences depend on many factors including a person's sense of style, what they are doing, and the weather. These factors, in turn, are dependent upon geographic location and time. In our work, we build computational models to learn the relationship between human appearance, geographic location, and time. The primary contributions are a framework for collecting and processing geotagged imagery of people, a large dataset collected by our framework, and several generative and discriminative models that use our dataset to learn the relationship …

Occurrence And Attributes Of Two Echinoderm-Bearing Faunas From The Upper Mississippian (Chesterian; Lower Serpukhovian) Ramey Creek Member, Slade Formation, Eastern Kentucky, U.S.A., Ann Well Harris

Theses and Dissertations--Earth and Environmental Sciences

Well-preserved echinoderm faunas are rare in the fossil record, and when uncovered, understanding their occurrence can be useful in interpreting other faunas. In this study, two such faunas of the same age from separate localities in the shallow-marine Ramey Creek Member of the Slade Formation in the Upper Mississippian (Chesterian) rocks of eastern Kentucky are examined. Of the more than 5,000 fossil specimens from both localities, only 9–34 percent were echinoderms from 3–5 classes. Nine non-echinoderm (8 invertebrate and one vertebrate) classes occurred at both localities, but of these, bryozoans, brachiopods and sponges dominated. To understand the attributes of both …

High Dimensional Multivariate Inference Under General Conditions, Xiaoli Kong

Theses and Dissertations--Statistics

In this dissertation, we investigate four distinct and interrelated problems for high-dimensional inference of mean vectors in multi-groups.

The first problem concerned is the profile analysis of high dimensional repeated measures. We introduce new test statistics and derive its asymptotic distribution under normality for equal as well as unequal covariance cases. Our derivations of the asymptotic distributions mimic that of Central Limit Theorem with some important peculiarities addressed with sufficient rigor. We also derive consistent and unbiased estimators of the asymptotic variances for equal and unequal covariance cases respectively.

The second problem considered is the accurate inference for high-dimensional repeated …

Accounting For Matching Uncertainty In Photographic Identification Studies Of Wild Animals, Amanda R. Ellis

Theses and Dissertations--Statistics

I consider statistical modelling of data gathered by photographic identification in mark-recapture studies and propose a new method that incorporates the inherent uncertainty of photographic identification in the estimation of abundance, survival and recruitment. A hierarchical model is proposed which accepts scores assigned to pairs of photographs by pattern recognition algorithms as data and allows for uncertainty in matching photographs based on these scores. The new models incorporate latent capture histories that are treated as unknown random variables informed by the data, contrasting past models having the capture histories being fixed. The methods properly account for uncertainty in the matching …

The Family Of Conditional Penalized Methods With Their Application In Sufficient Variable Selection, Jin Xie

Theses and Dissertations--Statistics

When scientists know in advance that some features (variables) are important in modeling a data, then these important features should be kept in the model. How can we utilize this prior information to effectively find other important features? This dissertation is to provide a solution, using such prior information. We propose the Conditional Adaptive Lasso (CAL) estimates to exploit this knowledge. By choosing a meaningful conditioning set, namely the prior information, CAL shows better performance in both variable selection and model estimation. We also propose Sufficient Conditional Adaptive Lasso Variable Screening (SCAL-VS) and Conditioning Set Sufficient Conditional Adaptive Lasso Variable …

Mixtures-Of-Regressions With Measurement Error, Xiaoqiong Fang

Theses and Dissertations--Statistics

Finite Mixture model has been studied for a long time, however, traditional methods assume that the variables are measured without error. Mixtures-of-regression model with measurement error imposes challenges to the statisticians, since both the mixture structure and the existence of measurement error can lead to inconsistent estimate for the regression coefficients. In order to solve the inconsistency, We propose series of methods to estimate the mixture likelihood of the mixtures-of-regressions model when there is measurement error, both in the responses and predictors. Different estimators of the parameters are derived and compared with respect to their relative efficiencies. The simulation results …

Multifactor Dimensionality Reduction With P Risk Scores Per Person, Ye Li

Theses and Dissertations--Statistics

After reviewing Multifactor Dimensionality Reduction(MDR) and its extensions, an approach to obtain P(larger than 1) risk scores is proposed to predict the continuous outcome for each subject. We study the mean square error(MSE) of dimensionality reduced models fitted with sets of 2 risk scores and investigate the MSE for several special cases of the covariance matrix. A methodology is proposed to select a best set of P risk scores when P is specified a priori. Simulation studies based on true models of different dimensions(larger than 3) demonstrate that the selected set of P(larger than 1) risk scores outperforms the single …

Estimation In Partially Linear Models With Correlated Observations And Change-Point Models, Liangdong Fan

Theses and Dissertations--Statistics

Methods of estimating parametric and nonparametric components, as well as properties of the corresponding estimators, have been examined in partially linear models by Wahba [1987], Green et al. [1985], Engle et al. [1986], Speckman [1988], Hu et al. [2004], Charnigo et al. [2015] among others. These models are appealing due to their flexibility and wide range of practical applications including the electricity usage study by Engle et al. [1986], gum disease study by Speckman [1988], etc., wherea parametric component explains linear trends and a nonparametric part captures nonlinear relationships.

The compound estimator (Charnigo et al. [2015]) has been used to …

Investigating The Role Of Prescription Drug Monitoring Programs In Reducing Rates Of Opioid-Related Poisonings, Nathan James Pauly

Theses and Dissertations--Pharmacy

The United States is in the midst of an opioid epidemic. In addition to other system level interventions, almost all states have responded to the crisis by implementing prescription drug monitoring programs (PDMPs). PDMPs are state-level interventions that track the dispensing of Controlled Substances. Data generated at the time of medication dispensing is uploaded to a central data server that may be used to assist in identifying drug diversion, medication misuse, or potentially aberrant prescribing practices.

Prior studies assessing the impact of PDMPs on trends in opioid-related morbidity have often failed to take into account the wide heterogeneity of program …

Using The Qbest Equation To Evaluate Ellagic Acid Safety Data: Generating A Qnoael With Confidence Levels From Disparate Literature, Cynthia Rose Dickerson

Theses and Dissertations--Pharmacy

QBEST, a novel statistical method, can be applied to the problem of estimating the No Observed Adverse Effect Level (NOAEL or QNOAEL) of a New Molecular Entity (NME) in order to anticipate a safe starting dose for beginning clinical trials. The NOAEL from QBEST (called the QNOAEL) can be calculated using multiple disparate studies in the literature and/or from the lab. The QNOAEL is similar in some ways to the Benchmark Dose Method (BMD) used widely in toxicological research, but is superior to the BMD in some ways. The QNOAEL simulation generates an intuitive curve that is comparable to the …

Bivariate Generalization Of The Time-To-Event Conditional Reassessment Method With A Novel Adaptive Randomization Method, Donglin Yan

Theses and Dissertations--Epidemiology and Biostatistics

Phase I clinical trials in oncology aim to evaluate the toxicity risk of new therapies and identify a safe but also effective dose for future studies. Traditional Phase I trials of chemotherapies focus on estimating the maximum tolerated dose (MTD). The rationale for finding the MTD is that better therapeutic effects are expected at higher dose levels as long as the risk of severe toxicity is acceptable. With the advent of a new generation of cancer treatments such as the molecularly targeted agents (MTAs) and immunotherapies, higher dose levels no longer guarantee increased therapeutic effects, and the focus has shifted …

Improved Standard Error Estimation For Maintaining The Validities Of Inference In Small-Sample Cluster Randomized Trials And Longitudinal Studies, Whitney Ford Tanner

Theses and Dissertations--Epidemiology and Biostatistics

Data arising from Cluster Randomized Trials (CRTs) and longitudinal studies are correlated and generalized estimating equations (GEE) are a popular analysis method for correlated data. Previous research has shown that analyses using GEE could result in liberal inference due to the use of the empirical sandwich covariance matrix estimator, which can yield negatively biased standard error estimates when the number of clusters or subjects is not large. Many techniques have been presented to correct this negative bias; However, use of these corrections can still result in biased standard error estimates and thus test sizes that are not consistently at their …

Using Prescription Drug Monitoring Data To Inform Population Level Analysis Of Opioid Analgesic Utilization, Huong T. T. Luu

Theses and Dissertations--Epidemiology and Biostatistics

Increased opioid analgesic (OA) prescribing has been associated with increased risk of prescription opioid diversion, misuse, and abuse. States established prescription drug monitoring programs (PDMPs) to collect and analyze electronic records for dispensed controlled substances to reduce prescription drug abuse and diversion. PDMP data can be used by prescribers for tracking patient’s history of controlled substance prescribing to inform clinical decisions.

The studies in this dissertation are focused on the less utilized potential of the PDMP data to enhance public health surveillance to monitor OA prescribing and co-prescribing and association with opioid overdose mortality and morbidity. Longitudinal analysis of OA …

Categorizing A Continuous Predictor Subject To Measurement Error, Betsabé G. Blas Achic, Tianying Wang, Ya Su, Victor Kipnis, Kevin Dodd, Raymond J. Carroll

Statistics Faculty Publications

Epidemiologists often categorize a continuous risk predictor, even when the true risk model is not a categorical one. Nonetheless, such categorization is thought to be more robust and interpretable, and thus their goal is to fit the categorical model and interpret the categorical parameters. We address the question: with measurement error and categorization, how can we do what epidemiologists want, namely to estimate the parameters of the categorical model that would have been estimated if the true predictor was observed? We develop a general methodology for such an analysis, and illustrate it in linear and logistic regression. Simulation studies are …

Long-Term Follow-Up Of Cardiac Function And Quality Of Life For Patients In Nsabp Protocol B-31/Nrg Oncology: A Randomized Trial Comparing The Safety And Efficacy Of Doxorubicin And Cyclophosphamide (Ac) Followed By Paclitaxel With Ac Followed By Paclitaxel And Trastuzumab In Patients With Node-Positive Breast Cancer With Tumors Overexpressing Human Epidermal Growth Factor Receptor 2, Patricia A. Ganz, Edward H. Romond, Reena S. Cecchini, Priya Rastogi, Charles E. Geyer Jr., Sandra M. Swain, Jong-Hyeon Jeong, Louis Fehrenbacher, Howard M. Gross, Adam M. Brufsky, Patrick J. Flynn, Tanya A. Wahl, Thomas E. Seay, James L. Wade Iii, David D. Biggs, James N. Atkins, Jonathan Polikoff, John L. Zapas, Eleftherios P. Mamounas, Norman Wolmark

Markey Cancer Center Faculty Publications

Purpose

Early cardiac toxicity is a risk associated with adjuvant chemotherapy plus trastuzumab. However, objective measures of cardiac function and health-related quality of life are lacking in long-term follow-up of patients who remain cancer free after completion of adjuvant treatment.

Patients and Methods

Patients in NSABP Protocol B-31 received anthracycline and taxane chemotherapy with or without trastuzumab for adjuvant treatment of node-positive, human epidermal growth factor receptor 2–positive early-stage breast cancer. A long-term follow-up assessment was undertaken for patients who were alive and disease free, which included measurement of left ventricular ejection fraction by multigated acquisition scan along with patient-reported …

Bayesian Prediction Intervals For Assessing P-Value Variability In Prospective Replication Studies, Olga A. Vsevolozhskaya, Gabriel Ruiz, Dmitri Zaykin

Biostatistics Faculty Publications

Increased availability of data and accessibility of computational tools in recent years have created an unprecedented upsurge of scientific studies driven by statistical analysis. Limitations inherent to statistics impose constraints on the reliability of conclusions drawn from data, so misuse of statistical methods is a growing concern. Hypothesis and significance testing, and the accompanying P-values are being scrutinized as representing the most widely applied and abused practices. One line of critique is that P-values are inherently unfit to fulfill their ostensible role as measures of credibility for scientific hypotheses. It has also been suggested that while P-values …

Some Dimension Reduction Strategies For The Analysis Of Survey Data, Jiaying Weng, Derek S. Young

Statistics Faculty Publications

In the era of big data, researchers interested in developing statistical models are challenged with how to achieve parsimony. Usually, some sort of dimension reduction strategy is employed. Classic strategies are often in the form of traditional inference procedures, such as hypothesis testing; however, the increase in computing capabilities has led to the development of more sophisticated methods. In particular, sufficient dimension reduction has emerged as an area of broad and current interest. While these types of dimension reduction strategies have been employed for numerous data problems, they are scantly discussed in the context of analyzing survey data. This …

Reliability Of An Observational Method Used To Assess Tennis Serve Mechanics In A Group Of Novice Raters, Natalie L. Myers, W. Ben Kibler, Gilson J. Capilouto, Philip M. Westgate, Tony English, Timothy L. Uhl

Physical Therapy Faculty Publications

Background: Previous research has developed an observational tennis serve analysis (OTSA) tool to assess serve mechanics. The OTSA has displayed substantial agreement between the two health care professionals that developed the tool; however, it is currently unknown if the OTSA is reliable when administered by novice users.

Purpose: The purpose of this investigation was to determine if reliability for the OTSA could be established in novice users via an interactive classroom training session.

Methods: Eight observers underwent a classroom instructional training protocol highlighting the OTSA. Following training, observers participated in two different rating sessions approximately a week apart. Each observer …

A Customized Quantitative Pcr Microrna Panel Provides A Technically Robust Context For Studying Neurodegenerative Disease Biomarkers And Indicates A High Correlation Between Cerebrospinal Fluid And Choroid Plexus Microrna Expression, Wang-Xia Wang, David W. Fardo, Gregory A. Jicha, Peter T. Nelson

Sanders-Brown Center on Aging Faculty Publications

MicroRNA (miRNA) expression varies in association with different tissue types and in diseases. Having been found in body fluids including blood and cerebrospinal fluid (CSF), miRNAs constitute potential biomarkers. CSF miRNAs have been proposed as biomarkers for neurodegenerative diseases; however, there is a lack of consensus about the best candidate miRNA biomarkers and there has been variability in results from different research centers, perhaps due to technical factors. Here, we sought to optimize technical parameters for CSF miRNA studies. We examined different RNA isolation methods and performed miRNA expression profiling with TaqMan® miRNA Arrays. More specifically, we developed a customized …

Load Model Verification, Validation And Calibration Framework By Statistical Analysis On Field Data, Xiangqing Jiao, Yuan Liao, Thai Nguyen

Electrical and Computer Engineering Faculty Publications

Accurate load models are critical for power system analysis and operation. A large amount of research work has been done on load modeling. Most of the existing research focuses on developing load models, while little has been done on developing formal load model verification and validation (V&V) methodologies or procedures. Most of the existing load model validation is based on qualitative rather than quantitative analysis. In addition, not all aspects of model V&V problem have been addressed by the existing approaches. To complement the existing methods, this paper proposes a novel load model verification and validation framework that can systematically …

Reducing Symptom Distress In Patients With Advanced Cancer Using An E-Alert System For Caregivers: Pooled Analysis Of Two Randomized Clinical Trials, David H. Gustafson, Lori L. Dubenske, Amy K. Atwood, Ming-Yuan Chih, Roberta A. Johnson, Fiona Mctavish, Andrew Quanbeck, Roger L. Brown, James F. Cleary, Dhavan Shah

Health and Clinical Sciences Faculty Publications

Background: Symptom distress in patients toward the end of life can change rapidly. Family caregivers have the potential to help patients manage those symptoms, as well as their own stress, if they are equipped with the proper resources. Electronic health (eHealth) systems may be able to provide those resources. Very sick patients may not be able to use such systems themselves to report their symptoms but family caregivers could.

Objective: The aim of this paper was to assess the effects on cancer patient symptom distress of an eHealth system that alerts clinicians to significant changes in the patient’s symptoms, as …

Correct Model Selection In Multiple Regression Analyses Of Big Data, Katherine L. Thompson

Commonwealth Computational Summit

Goals:

• Improve statistical modeling in a variety of application areas
• Correctly identify the relationships present in data sets
• Understand the difficulty in choosing the correct statistical model in big data

Systems Biology Approach To Late-Onset Alzheimer's Disease Genome-Wide Association Study Identifies Novel Candidate Genes Validated Using Brain Expression Data And Caenorhabditis Elegans Experiments, Shubhabrata Mukherjee, Joshua C. Russell, Daniel T. Carr, Jeremy D. Burgess, Mariet Allen, Daniel J. Serie, Kevin L. Boehme, John S. K. Kauwe, Adam C. Naj, David W. Fardo, Dennis W. Dickson, Thomas J. Montine, Nilufer Ertekin-Taner, Matt R. Kaeberlein, Paul K. Crane

Biostatistics Faculty Publications

Introduction—We sought to determine whether a systems biology approach may identify novel late-onset Alzheimer's disease (LOAD) loci.

Methods—We performed gene-wide association analyses and integrated results with human protein-protein interaction data using network analyses. We performed functional validation on novel genes using a transgenic Caenorhabditis elegans Aβ proteotoxicity model and evaluated novel genes using brain expression data from people with LOAD and other neurodegenerative conditions.

Results—We identified 13 novel candidate LOAD genes outside chromosome 19. Of those, RNA interference knockdowns of the C. elegans orthologs of UBC, NDUFS3, EGR1, and ATP5H were associated with Aβ …

Increased Birth Weight Is Associated With Altered Gene Expression In Neonatal Foreskin, Leryn J. Reynolds, Rebecca I. Pollack, Richard J. Charnigo, Cetewayo S. Rashid, Arnold J. Stromberg, Shu Shen, John O'Brien, Kevin J. Pearson

Pharmacology and Nutritional Sciences Faculty Publications

Elevated birth weight is linked to glucose intolerance and obesity health-related complications later in life. No studies have examined if infant birth weight is associated with gene expression markers of obesity and inflammation in a tissue that comes directly from the infant following birth. We evaluated the association between birth weight and gene expression on fetal programming of obesity. Foreskin samples were collected following circumcision, and gene expression analyzed comparing the 15% greatest birth weight infants (n = 7) v. the remainder of the cohort (n = 40). Multivariate linear regression models were fit to relate expression levels on differentially …

Judging The Neonatal Abstinence Syndrome Assessment Tools To Guide Future Tool Development: The Use Of Clinimetrics As Opposed To Psychometrics, Philip M. Westgate, Enrique Gomez-Pomar

Biostatistics Faculty Publications

In the face of the current Neonatal Abstinence Syndrome (NAS) epidemic, there is considerable variability in the assessment and management of infants with NAS. In this manuscript, we particularly focus on NAS assessment, with special attention given to the popular Finnegan Neonatal Abstinence Score (FNAS). A major instigator of the problem of variable practices is that multiple modified versions of the FNAS exist and continue to be proposed, including shortened versions. Furthermore, the validity of such assessment tools has been questioned, and as a result, the need for better tools has been suggested. The ultimate purpose of this manuscript, therefore, …

Prevention Of Renal Apob Retention Is Protective Against Diabetic Nephropathy: Role Of Tgf-Β Inhibition, Patricia G. Wilson, Joel C. Thompson, Meghan S. Yoder, Richard Charnigo, Lisa R. Tannock

Internal Medicine Faculty Publications

Animal studies demonstrate that hyperlipidemia and renal lipid accumulation contribute to the pathogenesis of diabetic nephropathy (DN). We previously demonstrated that renal lipoproteins colocalize with biglycan, a renal proteoglycan. The purpose of this study was to determine whether prevention of renal lipid (apoB) accumulation attenuates DN. Biglycan-deficient and biglycan wild-type Ldlr^−/− mice were made diabetic via streptozotocin and fed a high cholesterol diet. As biglycan deficiency is associated with elevated transforming growth factor-β (TGF-β), in some experiments mice were injected with either the TGF-β-neutralizing antibody, 1D11, or with 13C4, an irrelevant control antibody. Biglycan deficiency had no significant effect …