Statistics and Probability Commons^™

Statistical Analysis Based On Adaptive Progressive Hybrid Censored Data From Lomax Distribution, Amal Helu, Hani Samawi

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

In this article, we consider statistical inferences about the unknown parameters of the Lomax distribution basedon the Adaptive Type-II Progressive Hybrid censoring scheme, this scheme can save both the total test time and the cost induced by the failure of the units and increases the efficiency of statistical analysis. The estimation of the parameters is derived using the maximum likelihood (MLE) and the Bayesian procedures. The Bayesian estimators are obtained based on the symmetric and asymmetric loss functions. There are no explicit forms for the Bayesian estimators, therefore, we propose Lindley’s approximation method to compute the Bayesian estimators. A comparison …

Performance Of A Validated Spontaneous Preterm Delivery Predictor In South Asian And Sub-Saharan African Women: A Nested Case Control Study, Rasheda Khanam, Tracy C. Fleischer, Nansi Boghossian, Imran Nisar, Usha Dhingra, Sayedur Rahman, Angela C. Fox, Muhammad Iiyas, Arup Dutta, Nurun Naher, Ashoka D. Polpitiya, Usma Mehmood, Saikat Deb, Aziz Ahmed Choudhury, Md Bahadur Badsha, Karim Muhammad, Said Mohammed Ali, Salahuddin Ahmed, Durlin E. Hickok, Najeeha Iqbal, Et. Al.

Faculty Publications

Objectives

To address the disproportionate burden of preterm birth (PTB) in low- and middle-income countries, this study aimed to (1) verify the performance of the United States-validated spontaneous PTB (sPTB) predictor, comprised of the IBP4/SHBG protein ratio, in subjects from Bangladesh, Pakistan and Tanzania enrolled in the Alliance for Maternal and Newborn Health Improvement (AMANHI) biorepository study, and (2) discover biomarkers that improve performance of IBP4/SHBG in the AMANHI cohort.

Study design

The performance of the IBP4/SHBG biomarker was first evaluated in a nested case control validation study, then utilized in a follow-on discovery study performed on the same samples. …

Aggregating Twitter Text Through Generalized Linear Regression Models For Tweet Popularity Prediction And Automatic Topic Classification, Chen Mo, Jingjing Yin, Isaac Chun-Hai Fung, Zion Tse

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

Social media platforms have become accessible resources for health data analysis. However, the advanced computational techniques involved in big data text mining and analysis are challenging for public health data analysts to apply. This study proposes and explores the feasibility of a novel yet straightforward method by regressing the outcome of interest on the aggregated influence scores for association and/or classification analyses based on generalized linear models. The method reduces the document term matrix by transforming text data into a continuous summary score, thereby reducing the data dimension substantially and easing the data sparsity issue of the term matrix. To …

Characterizing Long Covid: Deep Phenotype Of A Complex Condition, Rachel R. Deer, Madeline A. Rock, Nicole Vasilevsky, Leigh Carmody, Halie Rando, Alfred J. Anzalone, Marc D. Basson, Tellen D. Bennett, Timothy Bergquist, Eilis A. Boudreau, Carolyn T. Bramante, James Brian Byrd, Tiffany J. Callahan, Lauren E. Chan, Haitao Chu, Christopher G. Chute, Ben D. Coleman, Hannah E. Davis, Joel Gagnier, Casey S. Greene, Ramakanth Kavuluru

Institute for Biomedical Informatics Faculty Publications

BACKGROUND: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or "long COVID"), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies.

METHODS: The Human Phenotype Ontology …

Causal Effects On Low Apgar At 5-Min And Stillbirth In A Malaria Maternal–Fetal Health Outcome Investigation: A Large Perinatal Surveillance Study In The Brazilian Amazon, Julio Abel Seijas-Chávez, Melissa Nolan Ph.D., Mph, Mary K. Lynn, Maria José Francalino Da Rocha, Muana Da Costa Araújo, Fernando Luiz Affonso Fonseca, Gabriel Zorello Laporta

Faculty Publications

Background

Malaria elimination in Brazil poses several challenges, including the control of Plasmodium falciparum foci and the hidden burden of Plasmodium vivax in pregnancy. Maternal malaria and fetal health outcomes were investigated with a perinatal surveillance study in the municipality of Cruzeiro do Sul, Acre state, Brazilian Amazon. The research questions are: what are the causal effects of low birth weight on low Apgar at 5-min and of perinatal anaemia on stillbirth?

Methods

From November 2018 to October 2019, pregnant women of ≥ 22 weeks or puerperal mothers, who delivered at the referral maternity hospital (Juruá Women and Children’s Hospital), …

The Dietary Inflammatory Index Is Not Associated With Gut Permeability Or Biomarkers Of Systemic Inflammation In Hiv Immunologic Non-Responders, Fat Malazogu, Rodney K. Rousseau, Nitin Shivappa Mbbs, Mph, Ph.D., Sanja Huibner, Sharon L. Walmsley, Colin M. Kovacs, Erika Benko, Robert J. Reinhard, Ron Rosenes, James R. Hébert, Rupert Kaul

Faculty Publications

Immunologic non-responders (INRs) are a subset of individuals living with HIV who have suboptimal blood CD4+ T cell recovery despite effective antiretroviral therapy (ART). They are at an increased risk of serious non-AIDS co-morbidities and death, and demonstrate enhanced systemic immune activation. In other populations diet has been correlated with markers of systemic inflammation through the Diet Inflammatory Index (DII), but this association has not been studied in persons living with HIV (PLWH). Blood was collected from 28 INR PLWH with a blood CD4+ T cell count <350/μL despite ≥2 years of effective ART. Participants completed a Canadian Diet History Questionnaire, and their responses were used to calculate the DII. Plasma inflammatory markers (IFNγ, TNF, IL-6, sVCAM, D-dimer, sCD14 and CRP) were assayed by ELISA, cellular immune activation (HLA-DR and CD38 on CD4+ and CD8+ T cells) was quantified using flow cytometry, and small bowel permeability assessed by calculation of the urine LacMan ratio after drinking a mix of lactulose and mannitol. Participants were a median age of 57 years, had been on effective ART for 15 years, and the median DII was −1.91 (range of −3.78 to +2.23). No correlation was observed between DII and plasma markers of inflammation, levels of T cell activation, gut permeability, or the biomarker of bacterial translocation sCD14. Self-reported alcohol intake, a potential confounder of the relationship between diet and inflammatory biomarkers, was also not associated with systemic inflammation or gut permeability. Our findings suggest that other mechanisms, rather than diet, are likely to be the major driver of systemic inflammation in INR individuals.

Association Between Diet Quality Indices And Incidence Of Type 2 Diabetes In The Melbourne Collaborative Cohort Study, Allison M. Hodge, Md Nazmul Karim, James Hébert Scd, Nitin Shivappa Mbbs, Mph, Ph.D., Barbora De Courten

Faculty Publications

Type 2 diabetes mellitus is a common condition whose incidence is increasing worldwide, and for which obesity and diet are important risk factors. The aim of this study was to assess the association of three diet quality scores with diabetes risk and how much of the association was mediated through body size. The Melbourne Collaborative Cohort Study recruited 41,513 men and women aged 40–69 years during 1990–1994. At baseline, data were collected on lifestyle and diet, anthropometric measures were performed. Incident diabetes was assessed by self-report at follow-up surveys in 1994–1998 and 2003–2007. The associations between the dietary inflammatory index …

Classifying Mosquito Presence And Genera Using Median And Interquartile Values From 26-Filter Wingbeat Acoustic Properties, Hernan S. Alar, Proceso L. Fernandez Jr

Department of Information Systems & Computer Science Faculty Publications

Mosquitoes are known to be one of the deadliest creatures in the world. There have been several studies that aim to identify mosquito presence and species using various techniques. The most common ones involve automatic identification of mosquito species from the sounds produced by flapping its wings. The development of these important concepts and technologies can help reduce the spread of mosquito-borne diseases. This paper presents a simple model based on mean and interquartile values that aim to solve the mosquito classification. Despite its simplicity, the proposed model significantly outperforms a Convolutional Neural Network (CNN) model in identifying the mosquito …

Uncertainty Quantification In Deep And Statistical Learning With Applications In Bio-Medical Image Analysis, K. Ruwani M. Fernando

USF Tampa Graduate Theses and Dissertations

Deep Learning (DL) has achieved the state-of-the-art performance across a broad spectrum oftasks. From a statistical standpoint, deep neural networks can be construed as universal function approximators. Although statistical modeling and deep learning methods are well-established as independent areas of research, hybridization of the two paradigms via probabilistic deep networks is an emerging trend. Through development of novel analytical methods under the statistical and deep-learning framework, we address some of the major challenges encountered in the design of intelligent systems which include class imbalance learning, probability calibration, uncertainty quantification and high dimensionality. When modeling rare events, existing methodologies require re-sampling …

Applications And Power Analyzation Of New Multiple Testing Procedures Based On Covering Principle, Yu Zhang

Student Theses and Dissertations

Multiple comparison tests are quite prevalent in clinical trials to increase efficiency and the chance of finding treatment or drug effects. However, making multiple comparisons will lead to the potential inflation of the Type I error rate. How well one test procedure controls the rate of false-positive conclusions becomes the main concern nowadays. A novel method named Covering Principle has been proposed recently. It provides a new approach to designing multiple testing procedures from the angle of rejection regions in the sample space, rather than in the parameter space, which uses in the methods based on the closed testing and …

A 6-Cpg Validated Methylation Risk Score Model For Metabolic Syndrome: The Hypergen And Goldn Studies, Bertha A. Hidalgo, Bre Minniefield, Amit Patki, Rikki Tanner, Minoo Bagheri, Hemant K. Tiwari, Donna K. Arnett, Marguerite Ryan Irvin

Epidemiology and Environmental Health Faculty Publications

There has been great interest in genetic risk prediction using risk scores in recent years, however, the utility of scores developed in European populations and later applied to non-European populations has not been successful. The goal of this study was to create a methylation risk score (MRS) for metabolic syndrome (MetS), demonstrating the utility of MRS across race groups using cross-sectional data from the Hypertension Genetic Epidemiology Network (HyperGEN, N = 614 African Americans (AA)) and the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, N = 995 European Americans (EA)). To demonstrate this, we first selected cytosine-guanine dinucleotides …

Interpolating Missing Data And Comparing Performance Of Common Interpolation Techniques From A 30-Year Water Quality Dataset, Wako Bungula, Danelle M. Larson Dr., Killian Davis, Richard Erickson Dr., Amber Lee, Casey Mckean, Frederick Miller, Alaina Stockdill, Enrika Hlavacek

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Estimation Of Parameters Of Epidemiological Models Under A Non-Parametric Approach And Its Application For Covid-19 In Bogotá D.C., Andrés Ríos-Gutiérrez, Viswanathan Arunachalam, Soledad Torres

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Estimation Analysis For The Seir Model With Stochastic Perturbation For The Covid-19 Outbreak In Bogotá, Viswanathan Arunachalam, Andres Rios-Gutierrez

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Reproduction Number For Covid-19 Pandemic On A College Campus, Elizabeth Amona

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Statistical Modeling Of Sars-Cov-2 Mutation In The U.S., Yuru Jing, Angela Antonou

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Species Abundance Distributions And The Canon Of Classical Music, Noelle Atkin

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

R Shiny's Self-Organizing Map, Zury Betzab Marroquin, Joshua Walsh, Trenton Wesley

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Age-Dependent Ventilator-Induced Lung Injury, Quintessa Hay

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Mathematical Modeling And Analysis Of Covid-19 Epidemic With Vaccination, Caitlin Seibel, Tina Huang, Jackson Reisman, Erika Johanna Martinez Salinas, Viswanathan Arunachalam, Moatlhodi Kgosimore, Anuj Mubayi, Padmanabhan Seshaiyer, Allen Bone Sehunelo

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.