Open Access. Powered by Scholars. Published by Universities.®

Statistics and Probability Commons™

Open Access. Powered by Scholars. Published by Universities.®

Old Dominion University

Discipline
Keyword
Publication Year
Publication
Publication Type

Articles 31 - 60 of 228

Full-Text Articles in Statistics and Probability

Check Your Data Before You Wreck Your Model: The Impact Of Careless Responding On Substance Use Data Quality, Abby L. Braitman, Anna M. Petrey, Jennifer L. Shipley, Rachel Ayala Guzman, Emily Renzoni, Alison Looby, Adrian J. Bravo Jan 2025

Check Your Data Before You Wreck Your Model: The Impact Of Careless Responding On Substance Use Data Quality, Abby L. Braitman, Anna M. Petrey, Jennifer L. Shipley, Rachel Ayala Guzman, Emily Renzoni, Alison Looby, Adrian J. Bravo

Psychology Faculty Publications

Background: The accuracy of survey responses is a concern in research data quality, especially in college student samples. However, examination of the impact of removing participants from analyses who respond inaccurately or carelessly is warranted given the potential for loss of information or sample diversity. This study aimed to understand if careless responding varies across a number of demographic indices, substance use behaviors, and the timing of survey completion.

Method: College students (N = 5809; 70.7% female; 75.7% White, non-Hispanic) enrolled in psychology classes from six universities completed an online survey assessing a variety of demographic and substance use-related information, …


Group Antenatal Care Positively Transforms The Care Experience: Results Of An Effectiveness Trial In Malawi, Crystal L. Patil, Kathleen F. Noor, Esnath Kapito, Li C. Liu, Xiaohan Mei, Elizabeth Chodzaza, Genesis Chorwe-Sungani, Ursula Kafuulafula, Elizabeth T. Abrams, Allissa Desloge, Ashley Gresh, Rohan D. Jeremiah, Dhruvi R. Patel, Anne Batchelder, Heidy Wang, Jocelyn Faydenko, Sharon S. Rising, Ellen Chirwa Jan 2025

Group Antenatal Care Positively Transforms The Care Experience: Results Of An Effectiveness Trial In Malawi, Crystal L. Patil, Kathleen F. Noor, Esnath Kapito, Li C. Liu, Xiaohan Mei, Elizabeth Chodzaza, Genesis Chorwe-Sungani, Ursula Kafuulafula, Elizabeth T. Abrams, Allissa Desloge, Ashley Gresh, Rohan D. Jeremiah, Dhruvi R. Patel, Anne Batchelder, Heidy Wang, Jocelyn Faydenko, Sharon S. Rising, Ellen Chirwa

Department of Medicine Faculty Publications

Background

We developed and tested a Centering-based group antenatal (ANC) model in Malawi, integrating health promotion for HIV prevention and mental health. We present effectiveness data and examine congruence with only the Group ANC theory of change model, which identifies key processes as supportive relationships, empowered partners in learning and care, and meaningful services, leading to better ANC experiences and outcomes.

Methods

We conducted a hybrid effectiveness-implementation trial at seven clinics in Blantyre District, Malawi, comparing outcomes for 1887 pregnant women randomly assigned to Group ANC or Individual ANC. Group effects on outcomes were summarized and evaluated using t-tests, Mann-Whitney, …


Contributions To Nonparametric Testing In Clustered Data, Hasika Kalani Wickrama Senevirathne Jul 2024

Contributions To Nonparametric Testing In Clustered Data, Hasika Kalani Wickrama Senevirathne

Mathematics & Statistics Theses & Dissertations

Clustered data refers to a specific kind of correlated data where units within the same cluster are correlated while units from different clusters are independent. The number of units in each cluster, known as the cluster size, can be associated with the cluster’s outcome. This is known as the informative cluster size (ICS) and affects the inference drawn from clustered data. Recently, a hypothesis testing method has been developed to detect the presence of ICS. However, considering ICS alone may not be sufficient when comparing outcomes across multiple groups of units within clustered data. The size of a group within …


Time Series Models For Predicting Application Gpu Utilization And Power Draw Based On Trace Data, Dorothy Xiaoshuang Parry Apr 2024

Time Series Models For Predicting Application Gpu Utilization And Power Draw Based On Trace Data, Dorothy Xiaoshuang Parry

Electrical & Computer Engineering Theses & Dissertations

This work explores collecting performance metrics and leveraging various statistical and machine learning time series predictive models on a memory-intensive application, Inception v3. Trace data collected using nvidia-smi measured GPU utilization and power draw for two runs of Inception3. Experimental results from the statistical and machine learning-based time series predictive algorithms showed that the predictions from statistical-based models were unable to capture the complex changes in the trace data. The Probabilistic TNN model provided the best results for the power draw trace, according to the test evaluation metrics. For the GPU utilization trace, the RNN models produced the most accurate …


Numerical Investigation And Statistical Analysis Of The Flow Patterns Behind Square Cylinders Arranged In A Staggered Configuration Utilizing The Lattice Boltzmann Method, M. Abid, N. Yasin, M. Saqlain, S. Ul-Islam, S. Ahmad Jan 2024

Numerical Investigation And Statistical Analysis Of The Flow Patterns Behind Square Cylinders Arranged In A Staggered Configuration Utilizing The Lattice Boltzmann Method, M. Abid, N. Yasin, M. Saqlain, S. Ul-Islam, S. Ahmad

Mathematics & Statistics Faculty Publications

Flow past bluff bodies like square cylinders is important in engineering applications, but flow patterns behind staggered cylinder arrangements remain poorly understood. Existing studies have focused on tandem or side-by-side configurations, while offset orientations have received less attention. The aim of this paper is to numerically investigate flow dynamics and force characteristics behind two offset square cylinders using the single relaxation time lattice Boltzmann method. The effects of changing both the Reynolds number (Re = 1-150) and gap spacing ratio (g* = 0.5-5) between the cylinders are analyzed. Instantaneous vorticity contours, time histories of drag and lift coefficients, power spectra …


Utility In Time Description In Priority Best-Worst Discrete Choice Models: An Empirical Evaluation Using Flynn's Data, Sasanka Adikari, Norou Diawara Jan 2024

Utility In Time Description In Priority Best-Worst Discrete Choice Models: An Empirical Evaluation Using Flynn's Data, Sasanka Adikari, Norou Diawara

Mathematics & Statistics Faculty Publications

Discrete choice models (DCMs) are applied in many fields and in the statistical modelling of consumer behavior. This paper focuses on a form of choice experiment, best-worst scaling in discrete choice experiments (DCEs), and the transition probability of a choice of a consumer over time. The analysis was conducted by using simulated data (choice pairs) based on data from Flynn's (2007) 'Quality of Life Experiment'. Most of the traditional approaches assume the choice alternatives are mutually exclusive over time, which is a questionable assumption. We introduced a new copula-based model (CO-CUB) for the transition probability, which can handle the dependent …


A Copula Discretization Of Time Series-Type Model For Examining Climate Data, Dimuthu Fernando, Olivia Atutey, Norou Diawara Jan 2024

A Copula Discretization Of Time Series-Type Model For Examining Climate Data, Dimuthu Fernando, Olivia Atutey, Norou Diawara

Mathematics & Statistics Faculty Publications

The study presents a comparative analysis of climate data under two scenarios: a Gaussian copula marginal regression model for count time series data and a copula-based bivariate count time series model. These models, built after comprehensive simulations, offer adaptable autocorrelation structures considering the daily average temperature and humidity data observed at a regional airport in Mobile, AL.


Scalar-On-Function Regression: Estimation And Inference Under Complex Survey Designs, Ekaterina Smirnova, Erjia Cui, Lucia Tabacu, Andrew Leroux Jan 2024

Scalar-On-Function Regression: Estimation And Inference Under Complex Survey Designs, Ekaterina Smirnova, Erjia Cui, Lucia Tabacu, Andrew Leroux

Mathematics & Statistics Faculty Publications

Increasingly, large, nationally representative health and behavioral surveys conducted under a multistage stratified sampling scheme collect high dimensional data with correlation structured along some domain (eg, wearable sensor data measured continuously and correlated over time, imaging data with spatiotemporal correlation) with the goal of associating these data with health outcomes. Analysis of this sort requires novel methodologic work at the intersection of survey statistics and functional data analysis. Here, we address this crucial gap in the literature by proposing an estimation and inferential framework for generalizable scalar-on-function regression models for data collected under a complex survey design. We propose to: …


The Geometry Of Dynamic Time-Dependent Best-Worst Choice Pairs, Sasanka Adikari, Norou Diawara, Haim Bar Jan 2024

The Geometry Of Dynamic Time-Dependent Best-Worst Choice Pairs, Sasanka Adikari, Norou Diawara, Haim Bar

Mathematics & Statistics Faculty Publications

There has been increasing interest in best–worst discrete choice experiments (BWDCEs) in health economics, transportation research, and other fields over the last few years. BWDCEs have distinct advantages compared to other measurement approaches in discrete choice experiments (DCEs). A systematic study of best–worst (BW) choice pairs can be traced back to the 1990s. Recently, new ideas have been introduced to the subject. Calculating utility helps measure the attractiveness of BW choices. The goal of this paper is twofold. First, we extend the idea of the BW choice pair to include dynamic, time-dependent transition probability and capture utility at each time …


Investigation Of The Effect Of Preparation Parameters On The Structural And Mechanical Properties Of Gelatin/Elastin/Sodium Hyaluronate Scaffolds Fabricated By The Combined Foaming And Freeze-Drying Techniques, Mansour Qamash, S. Misagh Imani, Meisam Omidi, Ciara Glancy, Lobat Tayebi Jan 2024

Investigation Of The Effect Of Preparation Parameters On The Structural And Mechanical Properties Of Gelatin/Elastin/Sodium Hyaluronate Scaffolds Fabricated By The Combined Foaming And Freeze-Drying Techniques, Mansour Qamash, S. Misagh Imani, Meisam Omidi, Ciara Glancy, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

This paper aimed to evaluate the effects of different preparation parameters, including agitation speed, agitation time, and chilling temperature, on the structural and mechanical properties of a novel gelatin/elastin/sodium hyaluronate tissue engineering scaffold, recently developed by our research group. Fabricated using a combination of foaming and freeze-drying techniques, the scaffolds were assessed to understand how these parameters influence their morphology, internal microstructure, porosity, mechanical properties, and degradation behavior. The fabrication process used in this study involved preparing a homogeneous aqueous solution containing 8% gelatin, 2% elastin, and 0.5% sodium hyaluronate (w/v), which was then subjected to mechanical agitation at speeds …


Dental Hygiene Students Reported Physiological Symptoms Associated With Wearing An N95 Respirator Mask, Peyton Shea Butler Oct 2023

Dental Hygiene Students Reported Physiological Symptoms Associated With Wearing An N95 Respirator Mask, Peyton Shea Butler

Dental Hygiene Theses & Dissertations

Purpose: Physiological symptoms and comfort levels while wearing an N95 respiratory mask has not been examined with dental hygienists. The purpose of this study was to investigate dental hygiene students reported physiological symptoms and comfort perception while wearing an N95 respirator mask during patient care appointments. Methods: After IRB approval (IRB #1987754-2), a 16-item questionnaire was distributed through email to a convenience sample of 65 dental hygiene students. Questions assessed respiratory, dermatologic, cardiac, mask mouth and general physiological symptoms, as well as comfort levels. Additionally, participants were asked to respond to demographic questions and one open ended question inquiring about …


The Prevalence Of Burnout In Saudi Arabia Dental Hygienists, Nouf Hamad Aldayel Oct 2023

The Prevalence Of Burnout In Saudi Arabia Dental Hygienists, Nouf Hamad Aldayel

Dental Hygiene Theses & Dissertations

Purpose: The purpose of this pilot study was to assess the prevalence of burnout in Saudi Arabian dental hygienists and identify risk factors associated with burnout. Methods: A descriptive survey design using the Copenhagen Burnout Inventory (CBI) assessed burnout among a convenience sample of n=123 Saudi dental hygienists. The survey was disseminated electronically to 1,000 Saudi Arabian dental hygienists. The CBI measures three subscales: personal, work-related, and client/patient-related burnout on a five-point Likert-type scale. The survey also included six demographic questions, two Likert-type, one “yes/no,” and one openended question, related to burnout. Descriptive statistics, one-way between subject’s ANOVA, independent samples …


A New Method To Determine The Posterior Distribution Of Coefficient Alpha, John Mart V. Delosreyes Oct 2023

A New Method To Determine The Posterior Distribution Of Coefficient Alpha, John Mart V. Delosreyes

Psychology Theses & Dissertations

There is a focus within the behavioral/social sciences on non-physical, psychological constructs (i.e., constructs). These constructs are indirectly measured using measurement instruments that consist of questions that capture the manifestations of these constructs. The indirect nature of measuring constructs results in a need of ensuring that measurement instruments are reliable. The most popular statistic used to estimate reliability is coefficient alpha as it is easy to compute and has properties that make it desirable to use. Coefficient alpha’s popularity has resulted in a wide breadth of research into its qualities. Notably, research about coefficient alpha’s distribution has led to developments …


Copula Based Models For Bivariate Zero-Inflated Count Time Series Data, Dimuthu Fernando Aug 2023

Copula Based Models For Bivariate Zero-Inflated Count Time Series Data, Dimuthu Fernando

Mathematics & Statistics Theses & Dissertations

Count time series data have multiple applications. The applications can be found in areas of finance, climate, public health and crime data analyses. In most scenarios, time is an important part of the data. Time series counts then come as multivariate vectors that exhibit not only serial dependence within each time series but also with cross-correlation among the series. When considering these observed counts, and when a value, say zero, occurs more often than usual, analysis presents crucial challenges. There is presence of zeroinflation in the data. The literature on bivariate or multivariate count time series, as well as zero-inflated …


Inference For Multiple Utility In Time-Dependent Choice Pairs Under Copula-Based Models, Sasanka Adikari May 2023

Inference For Multiple Utility In Time-Dependent Choice Pairs Under Copula-Based Models, Sasanka Adikari

Mathematics & Statistics Theses & Dissertations

Models for discrete choice experiments (DCE) are frequently used to analyze consumer choices about products and services. A family of DCE, best-worst scaling experiments, offers more in-depth insights into consumer preferences by eliciting a best and worst choice from a set of options, rather than just a single preference. Traditional approaches often assume that choices are mutually exclusive over time, which may not always be the case. This dissertation proposes a novel model for DCE that takes into account the changing nature of consumer choices over time and the priority constraint of transition probabilities. The model introduces a copula combination …


Gpu Utilization: Predictive Sarimax Time Series Analysis, Dorothy Dorie Parry Apr 2023

Gpu Utilization: Predictive Sarimax Time Series Analysis, Dorothy Dorie Parry

Modeling, Simulation and Visualization Student Capstone Conference

This work explores collecting performance metrics and leveraging the output for prediction on a memory-intensive parallel image classification algorithm - Inception v3 (or "Inception3"). Experimental results were collected by nvidia-smi on a computational node DGX-1, equipped with eight Tesla V100 Graphic Processing Units (GPUs). Time series analysis was performed on the GPU utilization data taken, for multiple runs, of Inception3’s image classification algorithm (see Figure 1). The time series model applied was Seasonal Autoregressive Integrated Moving Average Exogenous (SARIMAX).


The Effectiveness Of Visualization Techniques For Supporting Decision-Making, Cansu Yalim, Holly A. H. Handley Apr 2023

The Effectiveness Of Visualization Techniques For Supporting Decision-Making, Cansu Yalim, Holly A. H. Handley

Modeling, Simulation and Visualization Student Capstone Conference

Although visualization is beneficial for evaluating and communicating data, the efficiency of various visualization approaches for different data types is not always evident. This research aims to address this issue by investigating the usefulness of several visualization techniques for various data kinds, including continuous, categorical, and time-series data. The qualitative appraisal of each technique's strengths, weaknesses, and interpretation of the dataset is investigated. The research questions include: which visualization approaches perform best for different data types, and what factors impact their usefulness? The absence of clear directions for both researchers and practitioners on how to identify the most effective visualization …


Statistical Approach To Quantifying Interceptability Of Interaction Scenarios For Testing Autonomous Surface Vessels, Benjamin E. Hargis, Yiannis E. Papelis Apr 2023

Statistical Approach To Quantifying Interceptability Of Interaction Scenarios For Testing Autonomous Surface Vessels, Benjamin E. Hargis, Yiannis E. Papelis

Modeling, Simulation and Visualization Student Capstone Conference

This paper presents a probabilistic approach to quantifying interceptability of an interaction scenario designed to test collision avoidance of autonomous navigation algorithms. Interceptability is one of many measures to determine the complexity or difficulty of an interaction scenario. This approach uses a combined probability model of capability and intent to create a predicted position probability map for the system under test. Then, intercept-ability is quantified by determining the overlap between the system under test probability map and the intruder’s capability model. The approach is general; however, a demonstration is provided using kinematic capability models and an odometry-based intent model.


A Bootstrap Test For Informative Intra-Cluster Group Sizes In Clustered Data, Hasika K. Wickrama Senevirathne, Sandipan Dutta Jan 2023

A Bootstrap Test For Informative Intra-Cluster Group Sizes In Clustered Data, Hasika K. Wickrama Senevirathne, Sandipan Dutta

College of Sciences Posters

Clustered data are frequently observed in various domains of scientific and social studies. In a typical clustered data, units within a cluster are correlated while units between different clusters are independent. An example of such clustered data can be found in dental studies where individuals are treated as clusters and the teeth in an individual are the units within a cluster. While analyzing such clustered data, it has been observed that the number of units present in a cluster can be informative in terms of being associated with the outcome from that cluster. Specifically, when the aim is to compare …


Copula-Based Models For Bivariate And Multivariate Zero-Inflated Count Time Series Data, Dimuthu Fernando, Norou Diawara Jan 2023

Copula-Based Models For Bivariate And Multivariate Zero-Inflated Count Time Series Data, Dimuthu Fernando, Norou Diawara

College of Sciences Posters

Count time series data have multiple applications. The applications can be found in areas of finance, climate, public health and crime data analyses. In some scenarios, count time series come as multivariate vectors that exhibit not only serial dependence within each time series but also with cross correlation among the series. When considering these observed counts, analysis presents crucial challenges when a value, say zero, occurs more often than usual. There is presence of zero-inflation in the data.

In this presentation, we mainly focus on modeling bivariate zero-inflated count time series model based on a joint distribution of the two …


An Adaptive Algorithm For `The Secretary Problem': Alternate Proof Of The Divergence Of A Maximizer Sequence, Andrew Benfante, Xiang Xu Jan 2023

An Adaptive Algorithm For `The Secretary Problem': Alternate Proof Of The Divergence Of A Maximizer Sequence, Andrew Benfante, Xiang Xu

OUR Journal: ODU Undergraduate Research Journal

This paper presents an alternate proof of the divergence of the unique maximizer sequence {𝑥∗ 𝑛} of a function sequence {𝐹𝑛(𝑥)} that is derived from an adaptive algorithm based on the now classic optimal stopping problem, known by many names but here ‘the secretary problem’. The alternate proof uses a result established by Nguyen, Xu, and Zhao (n.d.) regarding the uniqueness of maximizer points of a generalized function sequence {𝑆𝜇,𝜎 𝑛 } and relies on the strict monotonicity of 𝐹𝑛(𝑥) as 𝑛 increases in order to show divergence of {𝑥∗ 𝑛}. Towards this, limits of the exponentiated Gaussian CDF are …


Fitting Time Series Models To Fisheries Data To Ascertain Age, Kathleen S. Kirch, Norou Diawara, Cynthia M. Jones Jan 2023

Fitting Time Series Models To Fisheries Data To Ascertain Age, Kathleen S. Kirch, Norou Diawara, Cynthia M. Jones

OES Faculty Publications

The ability of government agencies to assign accurate ages of fish is important to fisheries management. Accurate ageing allows for most reliable age-based models to be used to support sustainability and maximize economic benefit. Assigning age relies on validating putative annual marks by evaluating accretional material laid down in patterns in fish ear bones, typically by marginal increment analysis. These patterns often take the shape of a sawtooth wave with an abrupt drop in accretion yearly to form an annual band and are typically validated qualitatively. Researchers have shown key interest in modeling marginal increments to verify the marks do, …


Assessing Spurious Correlations In Big Search Data, Jesse T. Richman, Ryan J. Roberts Jan 2023

Assessing Spurious Correlations In Big Search Data, Jesse T. Richman, Ryan J. Roberts

Political Science & Geography Faculty Publications

Big search data offers the opportunity to identify new and potentially real-time measures and predictors of important political, geographic, social, cultural, economic, and epidemiological phenomena, measures that might serve an important role as leading indicators in forecasts and nowcasts. However, it also presents vast new risks that scientists or the public will identify meaningless and totally spurious ‘relationships’ between variables. This study is the first to quantify that risk in the context of search data. We find that spurious correlations arise at exceptionally high frequencies among probability distributions examined for random variables based upon gamma (1, 1) and Gaussian random …


Identifying Potential Consequences Of Use Of A Measure Through Stakeholder Interviews, Melissa G. Kuhn, Joanna K. Garner, Shanan L. Chappell, Linda Bol Jan 2023

Identifying Potential Consequences Of Use Of A Measure Through Stakeholder Interviews, Melissa G. Kuhn, Joanna K. Garner, Shanan L. Chappell, Linda Bol

STEMPS Faculty Publications

The advent of Messick’s Contemporary Validity Theory (1994) led researchers in survey and measure design to develop and standardize qualitative and quantitative methods of collecting evidence for the validity of psychological instruments. However, one aspect of this theory, consequential validity, has few agreed-upon evidence-gathering methods (Furr & Bachrach, 2014). This study added a blueprint-driven interview method of collecting forecasted consequences of use of an instrument into the overall process of developing a measure of outreach impact on undergraduate engineering students (Authors, in press). The method, which included a purposeful sampling of end-users, is illustrated with thematically presented results. Potential implications …


Poisson Regression Model With Application To Wastewater Surveillance Under A Threshold Linear Mixed Model For Covid-19 Sensitivity Rates, Norou Diawara, Hueiwang Anna Jeng, Kyle Curtis, Raul Gonzalez, Nancy Welch, Cynthia Jackson, Rekha Singh, David Jurgens, Sasanka Adikari, Omotomilola Jegede Jan 2023

Poisson Regression Model With Application To Wastewater Surveillance Under A Threshold Linear Mixed Model For Covid-19 Sensitivity Rates, Norou Diawara, Hueiwang Anna Jeng, Kyle Curtis, Raul Gonzalez, Nancy Welch, Cynthia Jackson, Rekha Singh, David Jurgens, Sasanka Adikari, Omotomilola Jegede

Mathematics & Statistics Faculty Publications

A Threshold Linear Mixed Model (TLMM) has been developed to identify specific thresholds based on wastewater SARS-CoV-2 viral concentrations, which reflect COVID-19 cases. The thresholds can guide decisions regarding public health responses and prevention measures. To assess the practical application of TLMM, a simple simulation was conducted using a sample size of 100 and 500 replications. The simulation allowed for comparing parameter estimators by assessing bias and standard deviation and the root of the mean square error. The model and estimation procedures were applied to reported wastewater and clinic data to test its application for real-world scenarios. Our results demonstrated …


Cheiloscopy Patterns In Individuals With And Without Parafunctional Oral Habits: A Cross-Sectional Observation Pilot Study, Emily Regan, Brenda Bradshaw, Ann Bruhn, Walter Melvin, Sinjini Sikdar Jan 2023

Cheiloscopy Patterns In Individuals With And Without Parafunctional Oral Habits: A Cross-Sectional Observation Pilot Study, Emily Regan, Brenda Bradshaw, Ann Bruhn, Walter Melvin, Sinjini Sikdar

Dental Hygiene Faculty Publications

Purpose

Lip prints are unique and have potential for use as a human identifier. The purpose of this study was to observe possible cheiloscopy differences of individuals with and without parafunctional oral habits such as smoking, vaping, playing a wind instrument or using an asthma inhaler.

Methods

This IRB approved blinded cross-sectional observation pilot study collected lip prints from 66 individuals, three of which were excluded. Participants cleansed their lips, then lipstick was applied to the vermillion zones of the upper and lower lips. Adhesive tape was applied to the lips and prints were transferred to white bond paper for …


Prediction Of Rapid Early Progression And Survival Risk With Pre-Radiation Mri In Who Grade 4 Glioma Patients, Walia Farzana, Mustafa M. Basree, Norou Diawara, Zeina Shboul, Sagel Dubey, Marie M. Lockheart, Mohamed Hamza, Joshua D. Palmer, Khan Iftekharuddin Jan 2023

Prediction Of Rapid Early Progression And Survival Risk With Pre-Radiation Mri In Who Grade 4 Glioma Patients, Walia Farzana, Mustafa M. Basree, Norou Diawara, Zeina Shboul, Sagel Dubey, Marie M. Lockheart, Mohamed Hamza, Joshua D. Palmer, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Rapid early progression (REP) has been defined as increased nodular enhancement at the border of the resection cavity, the appearance of new lesions outside the resection cavity, or increased enhancement of the residual disease after surgery and before radiation. Patients with REP have worse survival compared to patients without REP (non-REP). Therefore, a reliable method for differentiating REP from non-REP is hypothesized to assist in personlized treatment planning. A potential approach is to use the radiomics and fractal texture features extracted from brain tumors to characterize morphological and physiological properties. We propose a random sampling-based ensemble classification model. The proposed …


Statistical Methods For Meta-Analysis In Large-Scale Genomic Experiments, Wimarsha Thathsarani Jayanetti Dec 2022

Statistical Methods For Meta-Analysis In Large-Scale Genomic Experiments, Wimarsha Thathsarani Jayanetti

Mathematics & Statistics Theses & Dissertations

Recent developments in high throughput genomic assays have opened up the possibility of testing hundreds and thousands of genes simultaneously. With the availability of vast amounts of public databases, researchers tend to combine genomic analysis results from multiple studies in the form of a meta-analysis. Meta-analysis methods can be broadly classified into two main categories. The first approach is to combine the statistical significance (pvalues) of the genes from each individual study, and the second approach is to combine the statistical estimates (effect sizes) from the individual studies. In this dissertation, we will discuss how adherence to the standard null …


Empirically Adjusted Weighted Ordered P-Values Method, Wimarsha Jayanetti, Sinjini Sikdar, N. Rao Chaganty Apr 2022

Empirically Adjusted Weighted Ordered P-Values Method, Wimarsha Jayanetti, Sinjini Sikdar, N. Rao Chaganty

College of Sciences Posters

Recent advancements in high-throughput technologies have enabled simultaneous inference of thousands of genes. With the abundance of public databases, it is now possible to rapidly access the results of several genomic studies, each of which includes the significance testing results of a large number of genes. Researchers frequently aggregate genomic data from multiple studies in the form of a meta-analysis. Most traditional meta-analysis methods aim at combining summary results to find signals in at least one of the studies. However, often the goal is to identify genes that are differentially expressed in a consistent pattern across multiple studies. Recently, a …


Review Of Copula For Bivariate Distributions Of Zero-Inflated Count Time Series Data, Dimuthu Fernando, Mohammed Alqawba, Manar Samad, Norou Diawara Jan 2022

Review Of Copula For Bivariate Distributions Of Zero-Inflated Count Time Series Data, Dimuthu Fernando, Mohammed Alqawba, Manar Samad, Norou Diawara

Mathematics & Statistics Faculty Publications

The class of bivariate integer-valued time series models, described via copula theory, is gaining popularity in the literature because of applications in health sciences, engineering, financial management and more. Each time series follows a Markov chain with the serial dependence captured using copula-based distribution functions from the Poisson and the zero-inflated Poisson margins. The copula theory is again used to capture the dependence between the two series.

However, the efficiency and adaptability of the copula are being challenged because of the discrete nature of data and also in the case of zero-inflation of count time series. Likelihood-based inference is used …