Statistics and Probability Commons^™

Adverse Events Reporting Of Clinical Trials In Exercise Oncology Research (Advance): Protocol For A Scoping Review, Hao Luo, Oliver Schumacher, Daniel A. Galvão, Robert U. Newton, Dennis R. Taaffe

Research outputs 2022 to 2026

Introduction: Adequate, transparent, and consistent reporting of adverse events (AEs) in exercise oncology trials is critical to assess the safety of exercise interventions for people following a cancer diagnosis. However, there is little understanding of how AEs are reported in exercise oncology trials. Thus, we propose to conduct a scoping review to summarise and evaluate current practice of reporting of AEs in published exercise oncology trials with further exploration of factors associated with inadequate reporting of AEs. The study findings will serve to inform the need for future research on standardisation of the definition, collection, and reporting of AEs for …

Diet Quality And Dietary Inflammatory Index Score Among Women’S Cancer Survivors, Sibylle Kranz, Faten Hasan, Erin Kennedy, Jamie Zoellner, Kristin A. Guertin, Nitin Shivappa Mbbs, Mph, Ph.D., James R. Hébert, Roger Anderson, Wendy Cohn

Faculty Publications

The purpose of this study was to investigate Healthy Eating Index 2015 (HEI-2015) and Energy-Adjusted Dietary Inflammatory Index (E-DIITM) scores in women's cancer survivors and to examine socio-economic (SES) characteristics associated with these two diet indices. In this cross-sectional study, survivors of women's cancers completed a demographic questionnaire and up to three 24-h dietary recalls. HEI-2015 and E-DII scores were calculated from average intakes. One-way ANOVA was used to examine the association of various demographic factors on HEI-2015 and E-DII scores. Pearson Correlation was used to calculate the correlation between the two scores. The average HEI-2015 score was 55.0 +/- …

Session 13: On Statistical Estimates Of The Inverted Kumaraswamy Distribution Under Adaptive Type-I Progressive Hybrid Censoring, Qingqing Li, Yuhlong Lio

SDSU Data Science Symposium

The probability distribution modeling is investigated via maximum likelihood estimation method based on adaptive type-I progressively hybrid censored samples from the inverted Kumaraswamy distribution. The point estimates of model parameters, reliability, hazard rate and quantile are obtained and confidence intervals are also developed by using asymptotic distribution as well as bootstrap method. Monte Carlo simulation has been performed to evaluate the accuracy of estimations. Finally, a real data set is given for the application illustration.

An Alpha-Based Prescreening Methodology For A Common But Unknown Source Likelihood Ratio With Different Subpopulation Structures, Dylan Borchert, Semhar Michael, Christopher Saunders, Andrew Simpson

SDSU Data Science Symposium

Prescreening is a commonly used methodology in which the forensic examiner includes sources from the background population that meet a certain degree of similarity to the given piece of evidence. The goal of prescreening is to find the sources closest to the given piece of evidence in an alternative source population for further analysis. This paper discusses the behavior of an $\alpha-$based prescreening methodology in the form of a Hotelling $T^2$ test on the background population for a common but unknown source likelihood ratio. An extensive simulation study with synthetic and real data were conducted. We find that prescreening helps …

Identifying Subpopulations Of A Hierarchical Structured Data Using A Semi-Supervised Mixture Modeling Approach, Andrew Simpson, Semhar Michael, Christopher Saunders, Dylan Borchert

SDSU Data Science Symposium

The field of forensic statistics offers a unique hierarchical data structure in which a population is composed of several subpopulations of sources and a sample is collected from each source. This subpopulation structure creates a hierarchical layer. We propose using a semi-supervised mixture modeling approach to model the subpopulation structure which leverages the fact that we know the collection of samples came from the same, yet unknown, source. A simulation study based on a famous glass data was conducted and shows this method performs better than other unsupervised approaches which have been previously used in practice.

Session 5: Equipment Finance Credit Risk Modeling - A Case Study In Creative Model Development & Nimble Data Engineering, Edward Krueger, Landon Thompson, Josh Moore

SDSU Data Science Symposium

This presentation will focus first on providing an overview of Channel and the Risk Analytics team that performed this case study. Given that context, we’ll then dive into our approach for building the modeling development data set, techniques and tools used to develop and implement the model into a production environment, and some of the challenges faced upon launch. Then, the presentation will pivot to the data engineering pipeline. During this portion, we will explore the application process and what happens to the data we collect. This will include how we extract & store the data along with how it …

Angiotensin Blockade Therapy And Survival In Pancreatic Cancer: A Population Study, Scott W Keith, Vittorio Maio, Hwyda A Arafat, Matthew Alcusky, Thomas Karagiannis, Carol Rabinowitz, Harish Lavu, Daniel Z. Louis

College of Population Health Faculty Papers

Background: Pancreatic cancer (PC) is one of the most aggressive and challenging cancer types to effectively treat, ranking as the fourth-leading cause of cancer death in the United States. We investigated if exposures to angiotensin II receptor blockers (ARBs) or angiotensin I converting enzyme (ACE) inhibitors after PC diagnosis are associated with survival.

Methods: PC patients were identified by ICD-9 diagnosis and procedure codes among the 3.7 million adults living in the Emilia-Romagna Region from their administrative health care database containing patient data on demographics, hospital discharges, all-cause mortality, and outpatient pharmacy prescriptions. Cox modeling estimated covariate-adjusted mortality hazard ratios …

Transmodel: An R Package For Linear Transformation Model With Censored Data, Jie Zhou, Jiajia Zhang Ph.D.

Faculty Publications

Linear transformation models, including the proportional hazards model and proportional odds model, under right censoring were discussed by Chen, Jin, and Ying (2002). The asymptotic variance of the estimator they proposed has a closed form and can be obtained easily by plug-in rules, which improves the computational efficiency. We develop an R package TransModel based on Chen's approach. The detailed usage of the package is discussed, and the function is applied to the Veterans' Administration lung cancer data.

Comparison Of Human Urinary Exosomes Isolated Via Ultracentrifugation Alone Versus Ultracentrifugation Followed By Sec Column-Purification, Kun Huang, Sudha Garimella, Alyssa Clay-Gilmour, Lucia Vojtech, Bridget Armstrong, Madison Bessonny, Alexis Stamatikos

Faculty Publications

Chronic kidney disease is a progressive, incurable condition that involves a gradual loss of kidney function. While there are no non-invasive biomarkers available to determine whether individuals are susceptible to developing chronic kidney disease, small RNAs within urinary exosomes have recently emerged as a potential candidate to use for assessing renal function. Ultracentrifugation is the gold standard for urinary exosome isolation. However, extravesicular small RNA contamination can occur when isolating exosomes from biological fluids using ultracentrifugation, which may lead to misidentifying the presence of certain small RNA species in human urinary exosomes. Therefore, we characterized human urinary exosomal preparations isolated …

Periodicity On Isolated Time Scales, Martin Bohner, Jaqueline Mesquita, Sabrina Streipert

Mathematics and Statistics Faculty Research & Creative Works

In this work, we formulate the definition of periodicity for functions defined on isolated time scales. The introduced definition is consistent with the known formulations in the discrete and quantum calculus settings. Using the definition of periodicity, we discuss the existence and uniqueness of periodic solutions to a family of linear dynamic equations on isolated time scales. Examples in quantum calculus and for mixed isolated time scales are presented.

On Inclusions With Monotone-Type Mappings In Nonreflexive Banach Spaces, Vy Khoi Le

Mathematics and Statistics Faculty Research & Creative Works

We are concerned in this article with the existence of solutions to inclusions containing generalized pseudomonotone perturbations of maximal monotone mappings in general Banach spaces. Our approach is based on a truncation–regularization technique and an extension of the Moreau–Yosida–Brezis–Crandall–Pazy regularization for maximal monotone mappings in general Banach spaces. We also consider some applications to multivalued variational inequalities containing elliptic operators with rapidly growing coefficients in Orlicz–Sobolev spaces.

Marginal Proportional Hazards Models For Clustered Interval-Censored Data With Time-Dependent Covariates, Kaitlyn Cook, Wenbin Lu, Rui Wang

Harvard University Biostatistics Working Paper Series

The Botswana Combination Prevention Project was a cluster-randomized HIV prevention trial whose follow-up period coincided with Botswana’s national adoption of a universal test-and-treat strategy for HIV management. Of interest is whether, and to what extent, this change in policy (i) modified the observed preventative effects of the study intervention and (ii) was associated with a reduction in the population-level incidence of HIV in Botswana. To address these questions, we propose a stratified proportional hazards model for clustered interval-censored data with time-dependent covariates and develop a composite expectation maximization algorithm that facilitates estimation of model parameters without placing parametric assumptions on …

A Multigrid Multilevel Monte Carlo Method For Stokes–Darcy Model With Random Hydraulic Conductivity And Beavers–Joseph Condition, Zhipeng Yang, Ju Ming, Changxin Qiu, Maojun Li, Xiaoming He

Mathematics and Statistics Faculty Research & Creative Works

A multigrid multilevel Monte Carlo (MGMLMC) method is developed for the stochastic Stokes–Darcy interface model with random hydraulic conductivity both in the porous media domain and on the interface. Three interface conditions with randomness are considered on the interface between Stokes and Darcy equations, especially the Beavers–Joesph interface condition with random hydraulic conductivity. Because the randomness through the interface affects the flow in the Stokes domain, we investigate the coupled stochastic Stokes–Darcy model to improve the fidelity. Under suitable assumptions on the random coefficient, we prove the existence and uniqueness of the weak solution of the variational form. To construct …

Probability Models With Discrete And Continuous Parts, James E. Marengo, David L. Farnsworth

Articles

In mathematical statistics courses, students learn that the quadratic function E ((X – x )-squared) is minimized when x is the mean of the random variable X, and that the graphs of this function for any two distributions of X are simply translates of each other. We focus on the problem of minimizing the function defined by y ( x) = E ( IX – xI-squared ) in the context of mixtures of probability distributions of the discrete, absolutely continuous, and singular continuous types. This problem is important, for example, in Bayesian statistics, when one attempts to compute the decision …

Towards Statistical Best Practices For Gender And Sex Data, Suzanne Thornton, D. Roy, S. Parry, D. Lalonde, W. Martinez, R. Ellis, D. Corliss

Mathematics & Statistics Faculty Works

Suzanne Thornton, Dooti Roy, Stephen Parry, Donna LaLonde, Wendy Martinez, Renee Ellis and David Corliss call for a more inclusive – and informative – approach to collecting data on human gender and sex.

Mental Health In The Uk Biobank: A Roadmap To Self-Report Measures And Neuroimaging Correlates, Rosie K. Dutt, Kayla Hannon, Ty O. Easley, Joseph C. Griffis, Wei Zhang, Janine D. Bijsterbosch

Statistical and Data Sciences: Faculty Publications

The UK Biobank (UKB) is a highly promising dataset for brain biomarker research into population mental health due to its unprecedented sample size and extensive phenotypic, imaging, and biological measurements. In this study, we aimed to provide a shared foundation for UKB neuroimaging research into mental health with a focus on anxiety and depression. We compared UKB self-report measures and revealed important timing effects between scan acquisition and separate online acquisition of some mental health measures. To overcome these timing effects, we introduced and validated the Recent Depressive Symptoms (RDS-4) score which we recommend for state-dependent and longitudinal research in …

Slices Of The Big Apple: A Visual Explanation And Analysis Of The New York City Budget, Joanne Ramadani

Dissertations, Theses, and Capstone Projects

As a component of government, budgets are fundamental not only to improving the quality of a shared society, but also to understanding what our government officials consider to be their priorities. However, most budgets can be difficult to understand, using terms that are not familiar to people who have not studied finance or economics. To that end, Slices of the Big Apple is an interactive, centralized narrative website that uses visualizations at its core in order to: 1) facilitate a holistic understanding of the New York City government budget for NYC residents; and 2) conduct a five-year analysis of Community …

The Data Analytics And The Science Revolution, Leila Halawi, Amal Clarke, Kelly George

Publications

This text highlights the difference between analytics and data science, using predictive analytic techniques to analyze different historical data, including aviation data and concrete data, interpreting the predictive models, and highlighting the steps to deploy the models and the steps ahead. The book combines the conceptual perspective and a hands-on approach to predictive analytics using SAS VIYA, an analytic and data management platform. The authors use SAS VIYA to focus on analytics to solve problems, highlight how analytics is applied in the airline and business environment, and compare several different modeling techniques. They decipher complex algorithms to demonstrate how they …

Liquidity Commonality With Factor Models, Ernesto Garcia Iii

Dissertations, Theses, and Capstone Projects

Market microstructure research has recently devoted attention to a phenomenon called commonality in liquidity. In this dissertation, I will analyze commonality in liquidity using a novel factor model approach and a generalized definition of commonality in liquidity. This analysis will show that commonality in liquidity is rarely a marketwide phenomenon and is mostly restricted to stocks with a large market capitalization. Additionally, commonality in liquidity is a very recent phenomenon whose appearance coincides with a rise in passive investing after the Dotcom Bubble burst and, more so, after the 2008 Financial Crisis. I will present evidence that suggests commonality in …

Ecu-Ioft: A Dataset For Analysing Cyber-Attacks On Internet Of Flying Things, Mohiuddin Ahmed, David Cox, Benjamin Simpson, Aseel Aloufi

Research outputs 2022 to 2026

There has been a significant increase in the adoption of unmanned aerial vehicles (UAV) within science, technology, engineering, and mathematics project-based learning. However, the risks that education providers place their student and staff under is often unknown or undocumented. Low-end consumer drones used within the education sector are vulnerable to state-of-the-art cyberattacks. Therefore, datasets are required to conduct further research to establish cyber defenses for UAVs used within the education sector. This paper showcases the development of the ECU-IoFT dataset, documenting three known cyber-attacks targeting Wi-Fi communications and the lack of security in an affordable off-the-shelf drone. At present, there …

So Long My Friend, Bryan Mcnair

Journal of Humanistic Mathematics

No abstract provided.

Teiresias, Proportions, And Sexual Pleasure, Spyros Missiakoulis

Journal of Humanistic Mathematics

In this short article, I claim that Teiresias, the blind prophet of Apollo, in order to answer the question of whether “in sexual intercourse the woman had a larger share of pleasure than the man did”, measured the abstract concept of sexual pleasure and acted as a present-day scholar. With the help of numerical, not geometrical, proportions, he ended up with the conclusion “a man enjoyed one-tenth of the pleasure and a woman nine-tenths”.

Transition Metal Phosphides For High Performance Electrochemical Energy Storage Devices, Amina Saleh

Theses and Dissertations

Electrochemical energy storage technologies are nowadays playing a leading role in the global effort to address the energy challenges. A lot of attention has been devoted to designing hybrid devices known as supercapatteries which combine the merits of supercapacitors (high power density) and rechargeable batteries (high energy density). Transition metal phosphides (TMP) are a rising star for supercapattery anode materials thanks to their high conductivity, metalloid characteristics, and kinetic favorability for fast electron transport. Herein, new TMP-based materials were synthesized for use as supercapattery positive electrodes, via a multifaceted approach to yield devices enjoying concurrently high power and energy densities. …

The Power Of First-Order Smooth Optimization For Black-Box Non-Smooth Problems, Alexander V. Gasnikov., Anton Novitskii, Vasilii Novitskii, Farshed Abdukhakimov, Dmitry Kamzolov, Aleksandr Beznosikov, Martin Takáč, Pavel Dvurechensky, Bin Gu

Machine Learning Faculty Publications

Gradient-free/zeroth-order methods for black-box convex optimization have been extensively studied in the last decade with the main focus on oracle calls complexity. In this paper, besides the oracle complexity, we focus also on iteration complexity, and propose a generic approach that, based on optimal first-order methods, allows to obtain in a black-box fashion new zeroth-order algorithms for non-smooth convex optimization problems. Our approach not only leads to optimal oracle complexity, but also allows to obtain iteration complexity similar to first-order methods, which, in turn, allows to exploit parallel computations to accelerate the convergence of our algorithms. We also elaborate on …

Blood Flow Restriction Training After Patellar Instability (Brains Trial), Benjamin D. Brightwell, Austin V. Stone, Xiaojuan Li, Peter A. Hardy, Katherine L. Thompson, Brian W. Noehren, Cale A. Jacobs

Orthopaedic Surgery and Sports Medicine Faculty Publications

Background

Patellar instability is a common and understudied condition that disproportionally affects athletes and military personnel. The rate of post-traumatic osteoarthritis that develops following a patellar dislocation can be up to 50% of individuals 5–15 years after injury. Conservative treatment is the standard of care for patellar instability however, there are no evidence-informed rehabilitation guidelines in the scientific literature. The purpose of this study is to assess the effectiveness of blood-flow restriction training (BFRT) for patellar instability. Our hypotheses are that this strategy will improve patient-reported outcomes and accelerate restoration of symmetric strength and knee biomechanics necessary to safely return …

On Assessing Survival Benefit Of Immunotherapy Using Long-Term Restricted Mean Survival Time, Miki Horiguchi, Lu Tian, Hajime Uno

Harvard University Biostatistics Working Paper Series

The pattern of the difference between two survival curves we often observe in randomized clinical trials for evaluating immunotherapy is not proportional hazards; the treatment effect typically appears several months after the initiation of the treatment (i.e., delayed difference pattern). The commonly used logrank test and hazard ratio estimation approach will be suboptimal concerning testing and estimation for those trials. The long-term restricted mean survival time (LT-RMST) approach is a promising alternative for detecting the treatment effect that potentially appears later in the study. A challenge in employing the LT-RMST approach is that it must specify a lower end of …

Scanner: A Web Platform For Annotation, Visualization And Sharing Of Single Cell Rna-Seq Data, Guoshuai Cai, Xuanxuan Yu, Choonhan Youn, Jun Zhou, Feifei Xiao

Faculty Publications

In recent years, efficient scRNA-seq methods have been developed, enabling the transcriptome profiling of single cells massively in parallel. Meanwhile, its high dimensionality and complexity bring challenges to the data analysis and require extensive collaborations between biologists and bioinformaticians and/or biostatisticians. The communication between these two units demands a platform for easy data sharing and exploration. Here we developed Single-Cell Transcriptomics Annotated Viewer (SCANNER), as a public web resource for the scientific community, for sharing and analyzing scRNA-seq data in a collaborative manner. It is easy-to-use without requiring special software or extensive coding skills. Moreover, it equipped a real-time database …

Author’S Reflections On Making Sense Of Numbers: Quantitative Reasoning For Social Research, Jane E. Miller

Numeracy

Miller, Jane E. 2021. Making Sense of Numbers: Quantitative Reasoning for Social Research. (Los Angeles: SAGE Publications) 608 pp. ISBN 978-1544355597.

This article introduces and provides an excerpt from Making Sense of Numbers: Quantitative Reasoning for Social Research, published by Sage. The book explains and illustrates how making sense of numbers involves integrating concepts and skills from mathematics, statistics, study design, and communications, along with information about the specific topic and context under study. It teaches how to avoid making common errors of logic, calculation, and interpretation by introducing a systematic approach and a healthy dose of skepticism …

Parametric And Reliability Estimation Of The Kumaraswamy Generalized Distribution Based On Record Values, Mohd. Arshad, Qazi J. Azhad

Journal of Modern Applied Statistical Methods

A general family of distributions, namely Kumaraswamy generalized family of (Kw-G) distribution, is considered for estimation of the unknown parameters and reliability function based on record data from Kw-G distribution. The maximum likelihood estimators (MLEs) are derived for unknown parameters and reliability function, along with its confidence intervals. A Bayesian study is carried out under symmetric and asymmetric loss functions in order to find the Bayes estimators for unknown parameters and reliability function. Future record values are predicted using Bayesian approach and non Bayesian approach, based on numerical examples and a monte carlo simulation.

A Keyword-Enhanced Approach To Handle Class Imbalance In Clinical Text Classification, Andrew E. Blanchard, Shang Gao, Hong Jun Yoon, J. Blair Christian, Eric B. Durbin, Xiao Cheng Wu, Antoinette Stroup, Jennifer Doherty, Stephen M. Schwartz, Charles Wiggins, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi

School of Public Health Faculty Publications

Recent applications ofdeep learning have shown promising results for classifying unstructured text in the healthcare domain. However, the reliability of models in production settings has been hindered by imbalanced data sets in which a small subset of the classes dominate. In the absence of adequate training data, rare classes necessitate additional model constraints for robust performance. Here, we present a strategy for incorporating short sequences of text (i.e. keywords) into training to boost model accuracy on rare classes. In our approach, we assemble a set of keywords, including short phrases, associated with each class. The keywords are then used as …