Statistics and Probability Commons^™

Psychometric Properties Of A Year-End Form Four Chemistry Paper 1 In Selected Schools In Petaling Utama District, Mohamed Razali Rose Enne Emellia

Student Works (2020-2029)

The low-performance of science stream students in Chemistry especially in high-stakes testing, has alarmed the stakeholders. This problem has led to the need of analyzing the instruments used to measure the achievement of students. The present study examined the psychometric properties of multiple-choice questions in the Year-end Form Four Chemistry Paper 1 using the Rasch Model in the Klang Valley. A quantitative research design has been used for this study. The sample comprised of 435 Form Four Pure Science students from four randomly selected secondary schools in the Petaling Utama district. The Rasch analysis was conducted in two stages. The …

Preparing For The Future: The Effects Of Financial Literacy On Financial Planning For Young Professionals, Tanay Singh

Senior Theses

Purpose – Many people between the age of 20 and 34 have not considered planning financially for the future in any significant capacity and in doing so, they limit their potential savings. The purpose of this study is to examine what financial expectations are for people in the early stages of their career and determine if improving financial literacy and revealing financial realities helps to produce more accurate or realistic expectations. Ultimately, the goal is to better prepare participants in the study for the working world and increased responsibilities outside of the college/university environment by getting them to start thinking …

Multivariate Joint Models And Dynamic Predictions, Md Akhtar Hossain

Theses and Dissertations

The joint modeling of longitudinal and time-to-event data is an active area of statistical research that has received a lot of attention. The standard joint models, referred to as univariate joint models, allow simultaneous modeling of a single longitudinal outcome and a single time-to-event under an assumption of independent censoring. The majority of the joint modeling research in the last two decades has focused on extending and improving the univariate joint models. While many of the practical applications involve data on multivariate longitudinal outcomes and multiple timeto- events possibly informatively censored by some other terminal time-to-event, the developments of joint …

Studies Of Group Fused Lasso And Probit Model For Right-Censored Data, Tuan Quoc Do

Theses and Dissertations

This document is composed of three main chapters. In the first chapter, we study the mixture of experts, a powerful machine learning model in which each expert handles a different region of the covariate space. However, it is crucial to choose an appropriate number of experts to avoid overfitting or underfitting. A group fused lasso (GFL) term is added to the model with the goal of making the coefficients of the experts and the gating network closer together. An algorithm to optimize the problem is also developed using block-wise coordinate descent in the dual counterpart. Numerical results on simulated and …

Flexible Regression Models For Survival Data, Ennan Gu

Theses and Dissertations

Survival analysis is a branch of statistics to analyze the time-to-event data or survival data. One important feature of survival data is censoring, which means that not all the subjects’ survival time are observed directly. Among all the survival data, right-censored data are the most common type and consist of some exactly observed survival times and some right-censored observations. In this dissertation, we focus on studying flexible regression models for complicated right-censored survival data when the classical proportional hazards (PH) assumption is not satisfied. Flexible semiparametric regression models can largely avoid misspecification of parametric distributions and thus provide more modeling …

Bayesian Analysis Of Binary Diagnostic Tests And Panel Count Data, Chunling Wang

Theses and Dissertations

This dissertation mainly explores several challenging topics that arise in diagnostic tests and panel count data in the Bayesian framework. Binary diagnostic tests, particularly multiple diagnostic tests with repeated measures and diagnostic procedures with a large number of raters, are studied. For panel count data, most traditional methods only handle panel count data for a single type of recurrent event. In this dissertation, we primarily focus on the case with multiple types of recurrent events.

In Chapter 1, an introduction to the binary diagnostic tests data and panel count data is presented and related literature works are briefly reviewed. To …

Rotorcraft Blade Angle Calibration Methods, Brian David Calvert Jr.

Mechanical & Aerospace Engineering Theses & Dissertations

The most vital system of a rotorcraft is the rotor system due to its effects on the overall flight quality of the vehicle. Therefore, it is of importance to be able to accurately determine blade position during flight so that fine adjustments can be made to ensure a safe and efficient flight. In this study, a current calibration method focusing on the pitch, flap, and lead-lag blade angles is analyzed and found to have larger than acceptable error associated with the sensor calibrations. A literature review is conducted which reveals four novel methods that can potentially increase the accuracy of …

An Actuarial Approach To Personal Injury Protection Severity, Jason Colgrove

Undergraduate Honors Theses

Insurance companies examine the risk of financial losses for their policyholders as a way to accurately price insurance policies. Within the automobile insurance sector, the frequency of crashes and the associated liabilities started to increase in late 2013 when it had been on the decline for close to a decade. The purpose of this research focuses on the possible correlated variables that could lead to a better understanding of this change. To embark on this task, we teamed up with the Society of Actuaries, Casualty Actuarial Society, and the American Property Casualty Insurance Association to obtain data regarding frequency, severity, …

Conceptualization And Application Of Deep Learning And Applied Statistics For Flight Plan Recommendation, Nicholas C. Forrest

Theses and Dissertations

The Air Forces Pilot Training Next (PTN) program seeks a more efficient pilot training environment emphasizing the use of virtual reality flight simulators alongside periodic real aircraft experience. The PTN program wants to accelerate the training pace and progress in undergraduate pilot training compared to traditional undergraduate pilot training. Currently, instructor pilots spend excessive time planning and scheduling flights. This research focuses on methods to auto-generate the planning of in-flight events using hybrid filtering and deep learning techniques. The resulting approach captures temporal trends of user-specific and program-wide student performance to recommend a feasible set of graded flight events for …

An Analysis Of A Lighting Prediction Threshold For 45th Weather Squadron Electric Field Mill Data, Charles A. Skrovan

Theses and Dissertations

The mission of the 45th Weather Squadron (45 WS) is to “exploit the weather to assure safe access to air and space” for Patrick Air Force Base, Cape Canaveral Air Force Station (CCAFS), and Kennedy Space Center (KSC) in support of various operations (United States Air Force, n.d.). To support that mission the 45 WS hosts a suite of weather detection instruments that include a lightning warning system that consists of an array of 31 electric field mills (EFM) and a lightning detection and ranging system (Department of the Air Force, 1976). Electric field mills at Cape Canaveral continuously record …

Ground Weather Radar Signal Characterization Through Application Of Convolutional Neural Networks, Stephen M. Lee

Theses and Dissertations

The 45th Weather Squadron supports the space launch efforts out of the Kennedy Space Center and Cape Canaveral Air Force Station for the Department of Defense, NASA, and commercial customers through weather assessments. Their assessment of the Lightning Launch Commit Criteria (LLCC) for avoidance of natural and rocket triggered lightning to launch vehicles is critical in approving space shuttle and rocket launches. The LLCC includes standards for cloud formations, which requires proper cloud identification and characterization methods. Accurate reflectivity measurements for ground weather radar are important to meet the LLCC for rocket triggered lightning. Current linear interpolation methods for ground …

A New Liu Type Of Estimator For The Restricted Sur Estimator, Kristofer Månsson, B. M. Golam Kibria, Ghazi Shukur

Journal of Modern Applied Statistical Methods

A new Liu type of estimator for the seemingly unrelated regression (SUR) models is proposed that may be used when estimating the parameters vector in the presence of multicollinearity if the it is suspected to belong to a linear subspace. The dispersion matrices and the mean squared error (MSE) are derived. The new estimator may have a lower MSE than the traditional estimators. It was shown using simulation techniques the new shrinkage estimator outperforms the commonly used estimators in the presence of multicollinearity.

Sampling The Porridge: A Comparison Of Ordered Variable Regression With F And R2 And Multiple Linear Regression With Corrected F And R2 In The Presence Of Multicollinearity, Grayson L. Baird, Stephen L. Bieber

Journal of Modern Applied Statistical Methods

Differences between the multiple linear regression model with Corrected R² and Corrected F and the ordered variable regression model with R² and F when intercorrelation is present are illustrated with simulated and real-world data.

A Novel Penalized Log-Likelihood Function For Class Imbalance Problem, Lili Zhang

Doctor of Data Science and Analytics Dissertations

The log-likelihood function is the optimization objective in the maximum likelihood method for estimating models (e.g., logistic regression, neural network). However, its formulation is based on assumptions that the target classes are equally distributed and the overall accuracy is maximized, which do not apply to class imbalance problems (e.g., fraud detection, rare disease diagnoses, customer conversion prediction, cybersecurity, predictive maintenance). When trained on imbalanced data, the resulting models tend to be biased towards the majority class (i.e. non-event), which can bring great loss in practice. One strategy for mitigating such bias is to penalize the misclassification costs of observations differently …

Using Medical Claims Database To Develop A Population Disease Progression Model For Leuprorelin-Treated Subjects With Hormone-Sensitive Prostate Cancer, Yixuan Zou, Fei Tang, Jeffery C. Talbert, Chee M. Ng

Pharmacy Practice and Science Faculty Publications

Androgen deprivation therapy (ADT) is a widely used treatment for patients with hormone-sensitive prostate cancer (PCa). However, duration of treatment response varies, and most patients eventually experience disease progression despite treatment. Leuprorelin is a luteinizing hormone-releasing hormone (LHRH) agonist, a commonly used form of ADT. Prostate-specific antigen (PSA) is a biomarker for monitoring disease progression and predicting treatment response and survival in PCa. However, time-dependent profile of tumor regression and growth in patients with hormone-sensitive PCa on ADT has never been fully characterized. In this analysis, nationwide medical claims database provided by Humana from 2007 to 2011 was used to …

Predictive Validity Of Standards-Based And Curriculum-Embedded Assessments For Predicting Readiness At Kindergarten Entry, Elizabeth Ashton Decamilla

USF Tampa Graduate Theses and Dissertations

As with traditional K-12 educational settings, early childhood assessments have been a primary source of information determining whether early educational experiences have promoted children’s readiness to start school in kindergarten. The level of use of Kindergarten Entry Assessments (KEAs) has become more wide-spread to establish levels of school readiness at kindergarten entry.

This quantitative, correlational study of children in schools that have blended Head Start/Voluntary Prekindergarten funded programs examined the predictive relationships between the independent variables (i.e., VPK Assessments and Teaching Strategies GOLD) and the dependent variable of kindergarten readiness, as measured by the Work Sampling System™ (WSS). Additionally, the …

The Analytics Managers Ultimate Guide For Working With Universities, Robert J. Mcgrath

Faculty Publications

The challenges organizations are having related to finding (and retaining) deep analytical talent did not materialize out of thin air…or overnight. Analytics and Data science – and the role of the analytics professional – has evolved over the last several decades and has been fueled by our ability to capture and process increasingly larger and more complex variations of data and our desire to gain increasingly granular insights to fuel innovation and creativity. While many organizations recognize that a partnership with a university can be a resource to many of these challenges, the best way to start a conversation with …

A Permutation Test And Spatial Cross-Validation Approach To Assess Models Of Interspecific Competition Between Trees, David Allen, Albert Y. Kim

Statistical and Data Sciences: Faculty Publications

Measuring species-specific competitive interactions is key to understanding plant communities. Repeat censused large forest dynamics plots offer an ideal setting to measure these interactions by estimating the species-specific competitive effect on neighboring tree growth. Estimating these interaction values can be difficult, however, because the number of them grows with the square of the number of species. Furthermore, confidence in the estimates can be overestimated if any spatial structure of model errors is not considered. Here we measured these interactions in a forest dynamics plot in a transitional oak-hickory forest. We analytically fit Bayesian linear regression models of annual tree radial …

A Study Verifying The Dimensioning Of A Multivariate Dichotomized Sample In Exploratory Factor Analysis, Rosilei S. Novak, Jair M. Marques

Journal of Modern Applied Statistical Methods

The sample size dichotomized was related to the measure of sampling adequacy, considering the explanations provided by factors and commonalities. Monte Carlo simulation generated multivariate normal samples and varying the number of observations, the factor analysis was applied in each sample dichotomized. Results were modeled by polynomial regression based on the sample sizing.

Parametric And Non-Parametric Tests For The Comparison Of Two Samples Which Both Include Paired And Unpaired Observations, Ben Derrick, Paul White, Deirdre Toher

Journal of Modern Applied Statistical Methods

Samples that include both independent and paired observations cause a dilemma for researchers that covers the full breadth of empirical research. Parametric approaches for the comparison of two samples using all available observations are considered, under normality and non-normality. These approaches are compared to naive and newly proposed non-parametric alternatives.

Identification And Description Of Potentially Influential Social Network Members Using The Strategic Player Approach, Miles Q. Ott, Sara G. Balestrieri, Graham Diguiseppi, Melissa A. Clark, Michael Bernstein, Sarah Helseth, Nancy P. Barnett

Statistical and Data Sciences: Faculty Publications

Background: Diffusion of innovations theory posits that ideas and behaviors can be spread through social network ties. In intervention work, intervening upon certain network members may lead to intervention effects “diffusing” into the network to affect the behavior of network members who did not receive the intervention. The strategic players (SP) method, an extension of Borgatti’s Key Players approach, is used to balance the (sometimes) opposing goals of spreading the intervention to as many members of the target group as possible, while preventing the spread of the intervention to others. Objectives: We sought to test whether members of the SP …

Describing Quasi-Graphic Matroids, Nathan Bowler, Daryl Funk, Dan Slilaty

Mathematics and Statistics Faculty Publications

The class of quasi-graphic matroids recently introduced by Geelen, Gerards, and Whittle generalises each of the classes of frame matroids and liftedgraphic matroids introduced earlier by Zaslavsky. For each biased graph (G, B) Zaslavsky defined a unique lift matroid L(G, B) and a unique frame matroid F(G, B), each on ground set E(G). We show that in general there may be many quasi-graphic matroids on E(G) and describe them all: for each graph G and partition (B, L, F) of its cycles such that B satisfies the theta property and each cycle in L meets each cycle in F, there …

Inferences For Weibull-Gamma Distribution In Presence Of Partially Accelerated Life Test, Mahmoud Mansour, M A W Mahmoud Prof., Rashad El-Sagheer

Basic Science Engineering

In this paper, the point at issue is to deliberate point and interval estimations for the parameters of Weibull-Gamma distribution (WGD) using progressively Type-II censored (PROG-II-C) sample under step stress partially accelerated life test (SSPALT) model. The maximum likelihood (ML), Bayes, and four parametric bootstrap methods are used to obtain the point estimations for the distribution parameters and the acceleration factor. Furthermore, the approximate confidence intervals (ACIs), four bootstrap confidence intervals and credible intervals of the estimators have been gotten. The results of Bayes estimators are computed under the squared error loss (SEL) function using Markov Chain Monte Carlo (MCMC) …

Next-Generation Air Force Weather Metrics Via Bayes Cost Analysis, Brandon M. Bailey

Theses and Dissertations

This research proposes a new methodology for U.S. Air Force weather forecast metrics. Military weather forecasters are essentially statistical classifiers. They categorize future conditions into an operationally relevant category based on current data, much like an Artificial Neural Net or Logistic Regression model. There is extensive literature on statistically-based metrics for these types of classifiers. Additionally, in the U.S. Air Force, forecast errors (errors in classification) have quantifiable operational costs and benefits associated with incorrect or correct classification decisions. There is a methodology in the literature, Bayes Cost, which provides a structure for creating statistically rigorous metrics for classification decisions …

Analysis With Dynamic Bayesian Networks Compared To Simulation, Aaron J. Salazar

Theses and Dissertations

This research compares simulations to Dynamic Bayesian Networks in analyzing situations. The research applies models that have known output mean and variance. Queueing systems have theoretical values of the steady-state mean and variance for the number of entities in the system. Monte Carlo simulation development is broken down into two separate approaches: discrete-event simulation and time-oriented simulation. The discrete-event simulation uses pseudo-random numbers to schedule and trigger future events (i.e. customer arrivals and services) and is based on the generated objects.The time-oriented simulation utilizes fixed-width time intervals and updates the system state according to a stochastic process for the set …

Characterizing Uncertainty In Correlated Response Variables For Pareto Front Optimization, Peter A. Calhoun

Theses and Dissertations

Current research provides a method to incorporate uncertainty into Pareto front optimization by simulating additional response surface model parameters according to a Multivariate Normal Distribution (MVN). This research shows that analogous to the univariate case, the MVN understates uncertainty, leading to overconfident conclusions when variance is not known and there are few observations (less than 25-30 per response). This research builds upon current methods using simulated response surface model parameters that are distributed according to an Multivariate t-Distribution (MVT), which can be shown to produce a more accurate inference when variance is not known. The MVT better addresses uncertainty in …

Analysis And Forecasting Of The 360th Air Force Recruiting Group Goal Distribution, Tyler Spangler

Theses and Dissertations

This research utilizes monthly data from 2012-2017 to determine economic or demographic factors that significantly contribute to increased goaling and production potential in areas of the 360th Recruiting Groups. Using regression analysis, a model of recruiting goals and production is built to identify squadrons within the 360 RCGs zone that are capable of producing more or fewer recruits and the factors that contribute to this increased or decreased capability. This research identifies that a zones high school graduation rate, the number of recruiters, and the number of JROTC detachments in a zone are positively correlated with recruiting goals and that …

Some New Results On Stochastic Comparisons Of Coherent Systems Using Signatures, Ebrahim Amini-Seresht, Baha-Eldin Khaledi, Subhash C. Kochar

Mathematics and Statistics Faculty Publications and Presentations

We consider coherent systems with independent and identically distributed components. While it is clear that the system’s life will be stochastically larger when the components are replaced with stochastically better components, we show that, in general, similar results may not hold for hazard rate, reverse hazard rate, and likelihood ratio orderings. We find sufficient conditions on the signature vector for these results to hold. These results are combined with other well-known results in the literature to get more general results for comparing two systems of the same size with different signature vectors and possibly with different independent and identically distributed …

Effects Of Diabetes On The Output Of Farmer And Its Policy Implications, Syed Asif Ali Naqvi, Bilal Hussain, Syed Ale Raza Shah, Muhammad Sohail Amjad Makhdum

Kesmas

This study investigated the impact of diabetes on work performance of different farming communities from Punjab, Pakistan. This study was based on cross-sectional data. A representative sample of 374 farmers was collected from five selected districts. Three types of respondents were analyzed in the study e.g.,laborer, small and large growers. Poisson and logistic regression techniques were used for the sake of analysis. According to the investigated results for thelabor category, respondents with more age, less qualification, low earning per month (Rupees), and having positive record of family diabetes, would havemore leave per month. In the same way, findings for small …

Qualitative Exploration Of Experiences And Consequences Of Health-Related Stigma Among Indonesians With Hiv, Leprosy, Schizophrenia And Diabetes, Sarju Sing Rai, Irwanto Irwanto, Ruth M.H. Peters, Elena V. Syurina, Annisa Ika Putri, Altana Mikhakhanova, Denise Naniche, Marjolein B.M. Zweekhorst

Kesmas

Health-related stigma causes a negative impact on the lives of affected people and undermines the effectiveness of public health programs. This study aimedto explore experiences and consequences of stigma among people affected by four health conditions relevant in Indonesia– HIV (Human ImmunodeficiencyVirus), leprosy, schizophrenia and diabetes. In this qualitative study 40 people affected by the four health conditions in Jakarta and West Java, Indonesia–,were interviewed between March and June 2018. Data were analyzed thematically by following an integrative inductive-deductive approach. The experiencesand consequences of people with stigma were similar, but such experience were more severe among people affected by HIV, …