Statistics and Probability Commons^™

Linear Methods For Regression With Small Sample Sizes Relative To The Number Of Variables., Rajesh Sikder

Electronic Theses and Dissertations

In data sets where there are a small number of observations but a large number of variables observed for each observation, ordinary least squares estimation cannot be used for regression models. There are many alternative including stepwise regression, penalized methods such as ridge regression and the LASSO, and methods based on derived inputs such as principal components regression and partial least squares regression. In this thesis, these five methods are described. K-fold cross validation is also discussed as a way for determining regularization parameters for each method. The performance of these methods in estimation and prediction is also examined through …

Activation Of Trpa1 Nociceptor Promotes Systemic Adult Mammalian Skin Regeneration, Jenny J. Wei, Hali S. Kim, Casey A. Spencer, Donna Brennan-Crispi, Ying Zheng, Nicolette M. Johnson, Misha Rosenbach, Christopher Miller, Denis H. Y. Leung, George Cotsarelis, Thomas H. Leung

Research Collection School Of Economics

Adult mammalian wounds, with rare exception, heal with fibrotic scars that severely disrupt tissue architecture and function. Regenerative medicine seeks methods to avoid scar formation and restore the original tissue structures. We show in three adult mouse models that pharmacologic activation of the nociceptor TRPA1 on cutaneous sensory neurons reduces scar formation and can also promote tissue regeneration. Local activation of TRPA1 induces tissue regeneration on distant untreated areas of injury, demonstrating a systemic effect. Activated TRPA1 stimulates local production of interleukin-23 (IL-23) by dermal dendritic cells, leading to activation of circulating dermal IL-17–producing γδ T cells. Genetic ablation of …

A Bayesian Markov Chain Monte Carlo Approach To Uncertainty Quantification, Matthew Isaac

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Uncertainty quantification (UQ) is a framework used frequently in engineering analyses to understand how uncertainty in system inputs lead to uncertainty in the system output. An instability is observed in a UQ method proposed by Roy and Oberkampf and a Bayesian Markov Chain Monte Carlo approach to UQ is offered as an alternative. The Bayesian approach allows analysts to incorporate information from various available sources including observed measurements and expert opinion and to update the analysis and results as more information becomes available. An illustrative engineering example is provided as a platform to demonstrate the Bayesian UQ approach and to …

Marginal Methods And Software For Clustered Data With Cluster- And Group-Size Informativeness., Mary Elizabeth Gregg

Electronic Theses and Dissertations

Clustered data result when observations have some natural organizational association. In such data, cluster size is defined as the number of observations belonging to a cluster. A phenomenon termed informative cluster size (ICS) occurs when observation outcomes vary in a systematic way related to the cluster size. An additional form of informativeness, termed informative within-cluster group size (IWCGS), arises when the distribution of group-defining categorical covariates within clusters similarly carries information related to outcomes. Standard methods for the marginal analysis of clustered data can produce biased estimates and inference when data have informativeness. A reweighting methodology has been developed that …

A Novel Correction For The Adjusted Box-Pierce Test — New Risk Factors For Emergency Department Return Visits Within 72 Hours For Children With Respiratory Conditions — General Pediatric Model For Understanding And Predicting Prolonged Length Of Stay, Sidy Danioko

Computational and Data Sciences (PhD) Dissertations

This thesis represents the results of three research projects that underline the breadth and depth of my interests.

Firstly, I devoted some efforts to the well-known Box-Pierce goodness-of-fit tests for time series models which has been an important research topic over the last few decades. All previously proposed tests are focused on changes of the test statistics. Instead, I adopted a different approach that takes the best performing test and modifying the rejection region. Thus, I developed a semiparametric correction of the Adjusted Box-Pierce test that attains the best I error rates for all sample sizes and lags and outperforms …

D-Vine Pair-Copula Models For Longitudinal Binary Data, Huihui Lin

Mathematics & Statistics Theses & Dissertations

Dependent longitudinal binary data are prevalent in a wide range of scientific disciplines, including healthcare and medicine. A popular method for analyzing such data is the multivariate probit (MP) model. The motivation for this dissertation stems from the fact that the MP model fails even the binary correlations are within the feasible range. The reason being the underlying correlation matrix of the latent variables in the MP model may not be positive definite. In this dissertation, we study alternatives that are based on D-vine pair-copula models. We consider both the serial dependence modeled by the first order autoregressive (AR(1)) and …

Integrating Data Science Ethics Into An Undergraduate Major, Benjamin Baumer, Randi L. Garcia, Albert Y. Kim, Katherine M. Kinnaird, Miles Q. Ott

Statistical and Data Sciences: Faculty Publications

We present a programmatic approach to incorporating ethics into an undergraduate major in statistical and data sciences. We discuss departmental-level initiatives designed to meet the National Academy of Sciences recommendation for weaving ethics into the curriculum from top-to-bottom as our majors progress from our introductory courses to our senior capstone course, as well as from side-to-side through co-curricular programming. We also provide six examples of data science ethics modules used in five different courses at our liberal arts college, each focusing on a different ethical consideration. The modules are designed to be portable such that they can be flexibly incorporated …

Impact Of Lockdown In India: A Case Study Comparing Kanataka With International Model, Stelvin Sebastian, Aby Paul, Jeeva Joseph, Joel Joby, Sanjo Saijan, Jobin Kunjumon Vilapurathu

Kesmas

The COVID-19 was declared a pandemic and a global health emergency by WHO, prompting various countries to implement early and stringent social distancing protocols through lockdown, to flatten the epidemic curve. The objective of the present study was to assess the impacts and effectiveness of the lockdown protocol in Karnataka and Punjab, compared with the implementation of this method in Australia and the UK. This study involved the collection of data from different authorized databases, in two phases. The first phase included the time starting with the first-reported index case through the 14th day after the declaration of lockdown, for …

Pre-Testing Of The Who’S Educational Video: “How To Protect Yourself Against Covid-19”, Hilyatul Fadliyah, Manendra Muhtar, Munih Munih, Sylviasari Risgiantini, Weny Wulandary, Hadi Pratomo

Kesmas

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was declared a public health emergency in many countries, including Indonesia. The World Health Organization (WHO) released an educational video, entitled "How to Protect Yourself Against COVID-19", which explained how to prevent the spread of COVID-19. This study is a qualitative study that aims to pre-test this video, based on the Information, Education, Communication (IEC) theory, by analyzing teenagers’ perceptions of the video. The design used was a Rapid Assessment Procedure (RAP), and the data were collected by conducting in-depth interviews with participants, through …

Review Of Trial Therapies And Treatment For Covid-19: Lessons For Indonesia, Halma Zahro Mukhlida, Hilma Hasro Maulida, Gunanti Khairunnisa, Margaretha Josephine Mantrono, Risky Kusuma Hartono, Rindu Rindu, Eka R W Purnamasari, Rizky Fajar Meirawan

Kesmas

The infectious disease from Coronavirus Disease 2019, or COVID-19, has quickly spread world-wide since 2019. Therapies for managing COVID-19 have yet to be confirmed as medication for the severe sickness that the disease may cause. This study aimed to review the previous research of the efficacy of trial therapy and treatment to the patients in the hospital with COVID-19. Using PRISMA guidelines as a method for conducting a systematic literature review, a total of 67 articles were collected from several online journal databases. Various therapies were found that are effective in the treatment and management of COVID-19. In accordance with …

Uniform Random Variate Generation With The Linear Congruential Method, Joseph Free

PANDION: The Osprey Journal of Research and Ideas

This report considers the issue of using a specific linear congruential generator (LCG) to create random variates from the uniform(0,1) distribution. The LCG is used to generate multiple samples of pseudo-random numbers and statistical computation techniques are used to assess whether those samples could have resulted from a uniform(0,1) distribution. Source code is included with this report in the appendix along with annotations.

Lectures On Mathematical Computing With Python, Jay Gopalakrishnan

PDXOpen: Open Educational Resources

This open resource is a collection of class activities for use in undergraduate courses aimed at teaching mathematical computing, and computational thinking in general, using the python programming language. It was developed for a second-year course (MTH 271) revamped for a new undergraduate program in data science at Portland State University. The activities are designed to guide students' use of python modules effectively for scientific computation, data analysis, and visualization.

Adopt/Adapt
If you are an instructor adopting or adapting this open educational resource, please help us understand your use by filling out this form

Even Order Ranked Set Sampling With Auxiliary Variable, Muhammad Tayyab, Muhammad Noor Ul-Amin, Muhammad Hanif

Journal of Modern Applied Statistical Methods

Even order ranked set sampling (EORSS) is a novel proposed ranked set sampling scheme connected with an auxiliary variable correlated with the study variable. This scheme quantifies only the one sampling unit which is at even position from each ranking set by employing specific criteria. The performance of the ratio estimator under EORSS is compared to its contemporary estimators in simple random sampling (SRS), ranked set sampling (RSS), median ranked set sampling (MRSS) and quartile ranked set sampling (QRSS) exploiting the same number of quantified units. The simulation results proved that EORSS is an efficient alternative sampling scheme for ratio …

Objectives Driven Participatory Evaluation Model, Dustin R. Saalman

Journal of Modern Applied Statistical Methods

The ability to complete program evaluations of educational programming is typically restricted by the availability of resources, such as time, money and a trained evaluator. Although not a replacement for trained evaluators, promoting evaluative capacity and evaluative thinking within an organization can help mitigate this gap between talent and resources. Participatory evaluation is purported to increase organizational learning and promote evaluative thinking within an organization (Cousins & Whitmore, 1998). Objectives oriented evaluation is an easily understood evaluation method which provides a refined focus program outcome (Madaus & Stufflebeam, 1989). Using an internal evaluation of a new faculty onboarding course at …

Statistical Methodology To Establish A Benchmark For Evaluating Antimicrobial Resistance Genes Through Real Time Pcr Assay, Enakshy Dutta

Department of Statistics: Dissertations, Theses, and Student Research

Novel diagnostic tests are usually compared with gold standard tests for evaluating diagnostic accuracy. For assessing antimicrobial resistance (AMR) to bovine respiratory disease (BRD) pathogens, phenotypic broth microdilution method is used as gold standard (GS). The objective of the thesis is to evaluate the optimal cycle threshold (Ct) generated by real-time polymerase chain reaction (rtPCR) to genes that confer resistance that will translate to the phenotypic classification of AMR. Data from two different methodologies are assessed to identify Ct that will discriminate between resistance (R) and susceptibility (S). First, the receiver operating characteristic (ROC) curve was used to determine the …

Lattice Of Maximal-Primary Ideals In Quadratic Orders, Ryan Bridges

Mathematics & Statistics ETDs

An order is a subring of the ring of integers of an algebraic extension, Peruginelli and Zanardo classified the lattices of orders with prime index inside te ring of integers of quadratic extensions of the rational numbers. The lattices are quite striking and have different layered structure depending on whether the prime is inert, split, or ramified. This thesis considers the orders which have prime power index inside the Gaussian integers. This is a nice generalization of the work of Peruginelli and Zanardo, and succeeds in a few classifications of specific instances of orders derived from inert primes.

Maximum Likelihood Estimations Based On Upper Record Values For Probability Density Function And Cumulative Distribution Function In Exponential Family And Investigating Some Of Their Properties, Saman Hosseini, Parviz Nasiri, Sharad Damodar Gore

Journal of Modern Applied Statistical Methods

A useful subfamily of the exponential family is considered. The ML estimation based on upper record values are calculated for the parameter, Cumulative Density Function, and Probability Density Function of the subfamily. The relationship between MLE based on record values and a random sample are discussed, along with some properties of these estimators, and its utility is shown for large samples.

Maintaining Rich Dialogic Interactions In The Transition To Synchronous Online Learning, Hyunyi Jung, Corey Brady

Mathematical and Statistical Science Faculty Research and Publications

A central premise across a variety of educational research and policy documents is that students learn with greater understanding in classrooms where they engage in exploring, reasoning, and communicating about their thinking (Hiebert and Wearne, 1993; National Council of Teachers of English, 2016; National Council of Teachers of Mathematics, 2000). With the recent emergency transition to remote online instruction in higher education, opportunities for rich synchronous learning have been diminished in many courses. Most instructors have had to adapt rapidly from in-person classroom settings to online environments without sufficient time and training. Accordingly, college students have shared concerns about the …

Sars-Cov-2 Viral And Serological Testing When College Campuses Reopen: Some Practical Considerations, Isaac Chun-Hai Fung, Chi-Ngai Cheung, Andreas Handel

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

The coronavirus disease 2019 (COVID-19) pandemic prompted universities across the United States to close campuses in Spring 2020. Universities are deliberating whether, when, and how they should resume in-person instruction in Fall 2020. In this essay, we discuss some practical considerations for the use of 2 potentially useful control strategies based on testing: (1) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reverse transcriptase-polymerase chain reaction (RT-PCR) testing followed by case-patient isolation and quarantine of close contacts, and (2) serological testing followed by an “immune shield” approach, that is, low social distancing requirements for seropositive persons. The isolation of case-patients and …

The Comparison Between Maximum Weighted And Trimmed Likelihood Estimator Of The Simple Circular Regression Model, Ehab A. Mahmood, Habshah Midi, Abdul Ghapor Hussin

Journal of Modern Applied Statistical Methods

The Maximum Likelihood Estimator (MLE) was used to estimate unknown parameters of the simple circular regression model. However, it is very sensitive to outliers in data set. A robust method to estimate model parameters is proposed.