Physical Sciences and Mathematics Commons^™

Assessing Content Validity Through Correlation And Relevance Tools A Bayesian Randomized Equivalence Experiment, Byron Gajewski, Diane Boyle, Marjorie Bott, Larry Price, Jamie Leopold, Nancy Dunton

Diane Kay Boyle PhD, RN, FAAN

Content validity elicits expert opinion regarding items of a psychometric instrument. Expert opinion can be elicited in many forms: for example, how essential an item is or its relevancy to a domain. This study developed an alternative tool that elicits expert opinion regarding correlations between each item and its respective domain. With 109 Registered Nurse (RN) site coordinators from National Database of Nursing Quality Indicators, we implemented a randomized Bayesian equivalence trial with coordinators completing ‘‘relevance’’ or ‘‘correlation’’ content tools regarding the RN Job Enjoyment Scale. We confirmed our hypothesis that the two tools would result in equivalent content information. …

A Comparative Analysis Of Decision Trees Vis-À-Vis Other Computational Data Mining Techniques In Automotive Insurance Fraud Detection, Adrian Gepp, Kuldeep Kumar, J Holton Wilson, Sukanto Bhattacharya

Kuldeep Kumar

No abstract provided.

Nbr2 Errata And Comments, Joseph Hilbe

Joseph M Hilbe

Errata and Comments for Negative Binomial Regression, 2nd edition

A Bayesian Model For Pooling Gene Expression Studies That Incorporates Co-Regulation Information, Erin M. Conlon, Bradley L. L. Postier, Barbara A. Methé, Kelly P. Nevin, Derek R. Lovley

Erin M. Conlon

Current Bayesian microarray models that pool multiple studies assume gene expression is independent of other genes. However, in prokaryotic organisms, genes are arranged in units that are co-regulated (called operons). Here, we introduce a new Bayesian model for pooling gene expression studies that incorporates operon information into the model. Our Bayesian model borrows information from other genes within the same operon to improve estimation of gene expression. The model produces the gene-specific posterior probability of differential expression, which is the basis for inference. We found in simulations and in biological studies that incorporating co-regulation information improves upon the independence model. …

Piscine Myocarditis Virus (Pmcv) In Wild Atlantic Salmon Salmo Salar, Torstein Tengs Dr.

Dr. Torstein Tengs

Cardiomyopathy syndrome (CMS) is a severe cardiac disease of sea-farmed Atlantic salmon Salmo salar L., but CMS-like lesions have also been found in wild Atlantic salmon. In 2010 a double-stranded RNA virus of the Totiviridae family, provisionally named piscine myocarditis virus (PMCV), was described as the causative agent of CMS. In the present paper we report the first detection of PMCV in wild Atlantic salmon. The study is based on screening of 797 wild Atlantic salmon by real-time RT-PCR. The samples were collected from 35 different rivers along the coast of Norway, and all individuals included in the study were …

Multiple Subject Barycentric Discriminant Analysis (Musubada): How To Assign Scans To Categories Without Using Spatial Normalization, Hervé Abdi, Lynne J. Williams, Andrew C. Connolly, M. Ida Gobbini

Dartmouth Scholarship

We present a new discriminant analysis (DA) method called Multiple Subject Barycentric Discriminant Analysis (MUSUBADA) suited for analyzing fMRI data because it handles datasets with multiple participants that each provides different number of variables (i.e., voxels) that are themselves grouped into regions of interest (ROIs). Like DA, MUSUBADA (1) assigns observations to predefined categories, (2) gives factorial maps displaying observations and categories, and (3) optimally assigns observations to categories. MUSUBADA handles cases with more variables than observations and can project portions of the data table (e.g., subtables, which can represent participants or ROIs) on the factorial maps. Therefore MUSUBADA can …

Optimal Spatial Prediction Using Ensemble Machine Learning, Molly M. Davies, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Spatial prediction is an important problem in many scientific disciplines. Super Learner is an ensemble prediction approach related to stacked generalization that uses cross-validation to search for the optimal predictor amongst all convex combinations of a heterogeneous candidate set. It has been applied to non-spatial data, where theoretical results demonstrate it will perform asymptotically at least as well as the best candidate under consideration. We review these optimality properties and discuss the assumptions required in order for them to hold for spatial prediction problems. We present results of a simulation study confirming Super Learner works well in practice under a …

A Modular Mind? A Test Using Individual Data From Seven Primate Species, Federica Amici, Bradley Barney, Valen E. Johnson, Josep Call, Filippo Aureli

Faculty and Research Publications

It has long been debated whether the mind consists of specialized and independently evolving modules, or whether and to what extent a general factor accounts for the variance in performance across different cognitive domains. In this study, we used a hierarchical Bayesian model to re-analyse individual level data collected on seven primate species (chimpanzees, bonobos, orangutans, gorillas, spider monkeys, brown capuchin monkeys and long-tailed macaques) across 17 tasks within four domains (inhibition, memory, transposition and support). Our modelling approach evidenced the existence of both a domain-specific factor and a species factor, each accounting for the same amount (17%) of the …

Relating Nanoparticle Properties To Biological Outcomes In Exposure Escalation Experiments, Trina Patel, Cecile Low-Kam, Zhaoxia Ji, Haiyuan Zhang, Tian Xia, Andre E. Nel, Jeffrey I. Zinc, Donatello Telesca

COBRA Preprint Series

A fundamental goal in nano-toxicology is that of identifying particle physical and chemical properties, which are likely to explain biological hazard. The first line of screening for potentially adverse outcomes often consists of exposure escalation experiments, involving the exposure of micro-organisms or cell lines to a battery of nanomaterials. We discuss a modeling strategy, that relates the outcome of an exposure escalation experiment to nanoparticle properties. Our approach makes use of a hierarchical decision process, where we jointly identify particles that initiate adverse biological outcomes and explain the probability of this event in terms of the particle physico-chemical descriptors. The …

Time Series, Unit Roots, And Cointegration: An Introduction, Lonnie K. Stevans

Lonnie K. Stevans

The econometric literature on unit roots took off after the publication of the paper by Nelson and Plosser (1982) that argued that most macroeconomic series have unit roots and that this is important for the analysis of macroeconomic policy. Yule (1926) suggested that regressions based on trending time series data can be spurious. This problem of spurious correlation was further pursued by Granger and Newbold (1974) and this also led to the development of the concept of cointegration (lack of cointegration implies spurious regression). The pathbreaking paper by Granger (1981), first presented at a conference at the University of Florida …

Evaluation Of The Survival Effect For Various Treatment Modalities Among Stage Ii And Iii Rectal Cancer Patients In California, 1994-2009, Myung Mi Cho

Loma Linda University Electronic Theses, Dissertations & Projects

Background: European trials evaluating the effect of preoperative (PreOP) versus postoperative chemoradiotherapy (PostOP CRT) found no survival benefit. However, the effect of a change from PostOP to PreOP CRT has not been evaluated in a population-based setting. We sought to evaluate multimodal treatment changes and overall survival for perioperative (PeriOP) CRT versus surgery alone and for PreOP versus PostOP CRT from 1994 through 2009 among patients receiving radical surgery for stage II and III rectal cancer (RC).

Patients and Methods: We conducted a nonconcurrent cohort study evaluating demographic predictors of multimodal therapy for stage II and III RC using …

A Regionalized National Universal Kriging Model Using Partial Least Squares Regression For Estimating Annual Pm2.5 Concentrations In Epidemiology, Paul D. Sampson, Mark Richards, Adam A. Szpiro, Silas Bergen, Lianne Sheppard, Timothy V. Larson, Joel Kaufman

UW Biostatistics Working Paper Series

Many cohort studies in environmental epidemiology require accurate modeling and prediction of fine scale spatial variation in ambient air quality across the U.S. This modeling requires the use of small spatial scale geographic or “land use” regression covariates and some degree of spatial smoothing. Furthermore, the details of the prediction of air quality by land use regression and the spatial variation in ambient air quality not explained by this regression should be allowed to vary across the continent due to the large scale heterogeneity in topography, climate, and sources of air pollution. This paper introduces a regionalized national universal kriging …

Generalized Estimating Equations, Second Edition.Pdf, James W. Hardin, Joseph M.. Hilbe

Joseph M Hilbe

Generalized Estimating Equations, Second edition, updates the best-selling previous edition, which has been the standard text on the subject since it was published a decade ago. Combining theory and application, the text provides readers with a comprehensive discussion of GEE and related models. Numerous examples are employed throughout the text, along with the software code used to create, run, and evaluate the models being examined. Stata is used as the primary software for running and displaying modeling output; associated R code is also given to allow R users to replicate Stata examples. Specific examples of SAS usage are provided in …

Sensitivity Analysis For Causal Inference Under Unmeasured Confounding And Measurement Error Problems, Iván Díaz, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

In this paper we present a sensitivity analysis for drawing inferences about parameters that are not estimable from observed data without additional assumptions. We present the methodology using two different examples: a causal parameter that is not identifiable due to violations of the randomization assumption, and a parameter that is not estimable in the nonparametric model due to measurement error. Existing methods for tackling these problems assume a parametric model for the type of violation to the identifiability assumption, and require the development of new estimators and inference for every new model. The method we present can be used in …

Computationally Efficient Confidence Intervals For Cross-Validated Area Under The Roc Curve Estimates, Erin Ledell, Maya L. Petersen, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

In binary classification problems, the area under the ROC curve (AUC), is an effective means of measuring the performance of your model. Most often, cross-validation is also used, in order to assess how the results will generalize to an independent data set. In order to evaluate the quality of an estimate for cross-validated AUC, we must obtain an estimate for its variance. For massive data sets, the process of generating a single performance estimate can be computationally expensive. Additionally, when using a complex prediction method, calculating the cross-validated AUC on even a relatively small data set can still require a …

A National Model Built With Partial Least Squares And Universal Kriging And Bootstrap-Based Measurement Error Correction Techniques: An Application To The Multi-Ethnic Study Of Atherosclerosis, Silas Bergen, Lianne Sheppard, Paul D. Sampson, Sun-Young Kim, Mark Richards, Sverre Vedal, Joel Kaufman, Adam A. Szpiro

UW Biostatistics Working Paper Series

Studies estimating health effects of long-term air pollution exposure often use a two-stage approach, building exposure models to assign individual-level exposures which are then used in regression analyses. This requires accurate exposure modeling and careful treatment of exposure measurement error. To illustrate the importance of carefully accounting for exposure model characteristics in two-stage air pollution studies, we consider a case study based on data from the Multi-Ethnic Study of Atherosclerosis (MESA). We present national spatial exposure models that use partial least squares and universal kriging to estimate annual average concentrations of four PM2.5 components: elemental carbon (EC), organic carbon (OC), …

Analysis Of Alcohol Use Among Pregnant Women In San Luis Obispo County, Samantha Law

Statistics

Drinking alcohol during pregnancy is harmful to the fetus, and can lead to serious alcohol related developmental birth defects. Utilizing prenatal screening, such as the 4P’s Plus© screening tool, during a woman’s first prenatal doctors visit can help educate women and reduce continued alcohol use during pregnancy. Currently the CDC reports that 1 in 13 women in the US drink alcohol while pregnant compared to local reports that 1 in 3 women in San Luis Obispo County continue to drink alcohol during pregnancy. A primary concern for many local county health care experts and organizations is to raise awareness that …

An Analysis Of Risk Reduction Choices In Dcis Breast Cancer Patients, Lauren Soltesz

Statistics

The main focus of this paper was to evaluate possible demographic and clinical characteristics associated with a woman’s choice of breast conserving surgery (BCS), unilateral mastectomy (ULM), or bilateral risk reduction mastectomy (BRRM). The cohort consisted of patients presenting to the City of Hope National Medical Center with ductal carcinoma in situ breast cancer who elected to have cancer directed surgery (N=305). Analyses to examine associations of patient characteristics with type of surgery were conducted using a multinomial logistic regression. Results showed that older women were more likely to choose breast conserving surgery over bilateral risk reduction mastectomy than younger …

Testing The Predictive Performance Of Distribution Models, Volker Bahn, Brian Mcgill

Publications

Distribution models are used to predict the likelihood of occurrence or abundance of a species at locations where census data are not available. An integral part of modelling is the testing of model performance. We compared different schemes and measures for testing model performance using 79 species from the North American Breeding Bird Survey. The four testing schemes we compared featured increasing independence between test and training data: resubstitution, random data hold-out and two spatially segregated data hold-out designs. The different testing measures also addressed different levels of information content in the dependent variable: regression R2 for absolute abundance, squared …

On The Development Of Residential Property Price Indices For Nigeria, Olowofeso E. Olorunsola, Abiodun S. Bada, Mohammed A. Bamanga

CBN Journal of Applied Statistics (JAS)

This work focuses on the development of house price indices for Nigeria, and the estimates of the Nigerian Residential Property Price Indices on housing characteristics are presented. Four main methods of index construction were considered, these are hedonic regression, repeat-sales, stratification and central price tendency methods. It was discovered that econometric methods like hedonic and repeat sales were constraints in constructing residential property price indices for Nigeria by the nature of the data available. Hence, the central price tendency and the sale-based stratification methods which are internationally used measures were applied to the available zonal-level dataset from a survey of …

Analysis Of Crime Data Using Principal Component Analysis: A Case Study Of Katsina State, Shehu U. Gulumbe, Dikko H. .G., Bello Yusuf

CBN Journal of Applied Statistics (JAS)

This paper analyses Katsina State crime data which consists of the averages of eight major crimes reported to the police for the period 2006 – 2008. The crimes consist of robbery, auto theft, house and store breakings, theft/stealing, grievous hurt and wounding, murder, rape, and assault. Correlation analysis and principal component analysis (PCA) were employed to explain the correlation between the crimes and to determine the distribution of the crimes over the local government areas of the state. The result has shown a significant correlation between robbery, theft and vehicle theft. While MSW local government area has the lowest crime …

Inflation And Economic Growth In Nigeria: Detecting The Threshold Level, Sani I. Doguwa

CBN Journal of Applied Statistics (JAS)

This paper re-examines the issue of the existence and the level of inflation threshold in the relationship between inflation and growth in Nigeria, using three different approaches that provide appropriate procedures for estimating the threshold level and inference. While Sarel’s (1996) approach provides a threshold point estimate of 9.9 per cent that was not well identified by the data, the technique of Khan and Senhadji (2001) identifies a 10.5 per cent inflation threshold as statistically significant to explain the inflation-growth nexus in Nigeria. Also, the approach of Drukker et al (2005) suggests a two threshold point model with 11.2 and …

Understanding The Dynamics Of Inflation Volatility In Nigeria: A Garch Perspective, Babatunde S. Omotosho, Sani I. Doguwa

CBN Journal of Applied Statistics (JAS)

The estimation of inflation volatility is important to Central Banks as it guides their policy initiatives for achieving and maintaining price stability. This paper employs three models from the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) family with a view to providing a parsimonious approximation to the dynamics of Nigeria’s inflation volatility between 1996 and 2011. Of the competing models, the asymmetric TGARCH (1,1) provides an appropriate paradigm for explaining the dynamics of headline and core CPI volatilities in Nigeria, while the symmetric GARCH (1,1) was found to be adequate for food CPI. The results are quite revealing. Firstly, model outcomes indicate …

Stress-Lifetime Joint Distribution Model For Performance Degradation Failure, Quan Sun, Yanzhen Tang, Jing Feng, Paul Kvam

Department of Math & Statistics Faculty Publications

The high energy density self-healing metallized film pulse capacitor has been applied to all kinds of laser facilities for their power conditioning systems under several stress levels, such as 23kV, 30kV and 35kV, whose reliability performance and maintenance costs are affected by the reliability of capacitors. Due to the costs and time restriction, how to assess the reliability of highly reliable capacitors under a certain stress level as soon as possible becomes a challenge. Accelerated degradation test provides a way to predict its lifetime and reliability effectively. A model called stress-lifetime joint distribution model and an analysis method based on …

Study Of Reliability With Mixed Standby Components, M. A. El-Damcese, A. N. Helmy

Applications and Applied Mathematics: An International Journal (AAM)

This paper deals with the reliability characteristics of two different series system configurations with mixed standby (include cold and warm standby) components. The failure rates of the primary and warm standby components are assumed to follow the Weibull distribution. The repair time distribution of each server is exponentially distributed. Moreover, we will derive the mean time-to-failure, and the steady-state availability for a special case of a serial system of two primary components, two warm standby components, and one cold standby component, when the failure and repair rate are constant.

Objective Bayesian Inference On The Common Mean Of Normal Distributions, Shiyi Tu

All Theses

One of the oldest problems in statistical area is to make inference on a common mean of several different normal populations with unknown and probably unequal variances. There are several different ways to make inference on the common mean. The most common methods are point estimation, hypothesis testing, and interval estimation. Point estimation uses sample data to calculate a single value serving as a best guess for the unknown population mean. Hypothesis testing assumes all populations have the same mean as the null hypothesis. Interval estimation is an interval of possible values of the unknown mean.
In this paper, we …

The Morbidity & Mortality Of Prevalent Heart Failure, Jennifer Kwon

Loma Linda University Electronic Theses, Dissertations & Projects

The first study population included 292 unselected consecutive patients from the LLUMC heart failure clinic who were enrolled in the study from January to July 2006 and were followed up through the end of December 2010. The treatment policy at the clinic was to uptitrate dosages of beta-adrenergic blockade (β-blockers), angiotensin-converting-enzyme inhibitors (ACEi) and angiotensin II receptor blockers (ARB) to the most tolerable levels in order to reach target dosages, as recommended by the Heart Failure Society of America (HFSA). Patients were classified into systolic heart failure (ejection fraction (EF) < 40%) or diastolic heart failure (EF≥40%). All dosages of β-blockers, ACEi and ARB were extracted through chart reviews and were used as the main predictors of the patients' survival. Results from analyses showed that reaching target dosages of β-blockers and ACEi/ARB may increase survival when compared to not reaching target among the systolic HF population (HR_{β_biockers}= 0.64, 95% CI 0.26-1.56 and HR_ACEi/ARB=0.50, …

An Economic Alternative To The C Chart, Ryan William Black

Graduate Theses and Dissertations

Because the probability of Type I error is not evenly distributed beyond upper and lower three-sigma limits the c chart is theoretically inappropriate for a monitor of Poisson distributed phenomena. Furthermore, the normal approximation to the Poisson is of little use when c is small. These practical and theoretical concerns should motivate the computation of true error rates associated with individuals control assuming the Poisson distribution. An economic alternative to the c chart is described as a statistical model of upward shift from c0 to c1 and the two charts are compared in theory. For a range of c chart …

Visual Data Mining Techniques For Functional Actigraphy Data: An Object-Oriented Approach In R, Abbass Sharif

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Actigraphy, a technology for measuring a subject's overall activity level almost continuously over time, has gained a lot of momentum over the last few years. An actigraph, a watch-like device that can be attached to the wrist or ankle of a subject, uses an accelerometer to measure human movement every minute or even every 15 seconds. Actigraphy data is often treated as functional data. In this dissertation, we discuss what has been done regarding the visualization of actigraphy data, and then we will explain the three main goals we achieved: (i) develop new multivariate visualization techniques for actigraphy data; (ii) …

Limited Sampling Estimates Of Epigallocatechin Gallate Exposures In Cirrhotic And Noncirrhotic Patients With Hepatitis C After Single Oral Doses Of Green Tea Extract., Dina Halegoua-De Marzio, Walter K. Kraft, Constantine Daskalakis, Xie Ying, Roy L Hawke, Victor J. Navarro

Division of Gastroenterology and Hepatology Faculty Papers

BACKGROUND: Epigallocatechin-3-gallate (EGCG) has antiangiogenic, antioxidant, and antifibrotic properties that may have therapeutic potential for the treatment of cirrhosis induced by hepatitis C virus (HCV). However, cirrhosis might affect EGCG disposition and augment its reported dose-dependent hepatotoxic potential.

OBJECTIVE: The safety, tolerability, and disposition of a single oral dose of EGCG in cirrhotic patients with HCV were examined in an exploratory fashion.

METHODS: Eleven patients with hepatitis C and detectable viremia were enrolled. Four had Child-Pugh (CP) class A cirrhosis, 4 had Child-Pugh class B cirrhosis, and 3 were noncirrhotic. After a single oral dose of green tea extract 400 …