Statistics and Probability Commons^™

Median Confidence Regions In A Nonparametric Model, Edsel A. Pena, Taeho Kim

Faculty Publications

The nonparametric measurement error model (NMEM) postulates that Xi=Δ+ϵi,i=1,2,…,n;Δ∈R with ϵi,i=1,2,…,n, IID from F(⋅)∈Fc,0, where Fc,0 is the class of all continuous distributions with median 0, so Δ is the median parameter of X. This paper deals with the problem of constructing a confidence region (CR) for Δ under the NMEM. Aside from the NMEM, the problem setting also arises in a variety of situations, including inference about the median lifetime of a complex system arising in engineering, reliability, biomedical, and public health settings, as well as in the economic arena such as when dealing with household income. Current methods …

Inflated Standard Errors Of Mcmc Estimates In Irt, Dongho Shin

Theses and Dissertations

Two widely used algorithms for estimating item response theory (IRT) parameters are Markov chain Monte Carlo (MCMC) and the EM algorithm. In general, the MCMC algorithm has advantages over the EM algorithm - for example, the MCMC algorithm allows one to estimate the desired posterior distribution and also works more straightforwardly with complex IRT models. This ease of use, allows one to implement the MCMC algorithm without carefully consideration. Previous studies, Hendrix (2011) and Lee (2016), noted that the estimated standard errors from the MCMC algorithm are larger than those from the EM algorithm. Therefore, this study investigate the reason …

Newsworthy Migrants: Sentiment And Text Analysis Of Dutch Newspapers, Nicholas J. Schmitz

Independent Study Project (ISP) Collection

Understanding how a migrant population is viewed and displayed by the host country has been a struggle for a long period of time for anyone studying migration. Traditional methods of collecting information were tedious, time intensive and expensive. However, Big data has been providing unique solutions to gaps in information in many different fields across the world. Media plays an important part in developing and assessing the public opinion on a topic. With the availability of a large number of online articles from historical time periods, it is possible to use quantitative analysis, such as text analytics, to can see …

Spatio-Temporal Analysis Of Precipitation And Flood Data From South Carolina, Haigang Liu

Theses and Dissertations

Spatio-temporal data are everywhere: we encounter them on TV, in newspapers, on computer screens, on tablets, and on plain paper maps. As a result, researchers in di- verse areas are increasingly faced with the task of modeling geographically-referenced and temporally-correlated data. In this dissertation, we propose two different spa- tiotemporal models to capture the behavior of rainfall and flood data in the state of South Carolina.

Both models are built using a Bayesian hierarchical framework, which involves specifying the true underlying process in the first level and the spatio-temporal ran- dom effect in the second level of the hierarchy. The …

Cluster Analysis Of Mixed-Mode Data, Yawei Liang

Theses and Dissertations

In the modern world, data have become increasingly more complex and often contain different types of features. Two very common types of features are continuous and discrete variables. Clustering mixed-mode data, which include both continuous and discrete variables, can be done in various ways. Furthermore, a continuous variable can take any value between its minimum and maximum. Types of continuous vari- ables include bounded or unbounded normal variables, uniform variables, circular variables, etc. Discrete variables include types other than continuous variables, such as binary variables, categorical (nominal) variables, Poisson variables, etc. Difficulties in clustering mixed-mode data include handling the association …

Enhancing Smes’ Data Analytics Capability Through University Tie-Ups, Gary Pan, Poh Sun Seow, Benjamin Huan Zhou Lee

Research Collection School Of Accountancy

Harnessing the power of data analytics, SMEs can now generate visualisations of the company's historical data to date, and predictions for the future - something which is nearly impossible before the era of big data.

Randomization Analysis Driven Software, Steph-Yves Louis

Theses and Dissertations

The application of a method of randomization for a clinical trial frequently summarizes to using Simple Randomization. Even though the latter method provides favorable characteristics, if the collected sample is not large enough, it still presents the highest chance of imbalance both marginally in the treatment groups and locally in terms of the covariates. Methods of Permuted Block Randomization, Urn Randomization, Stratified Permuted Block Randomization, and Minimization represent popular alternative methods that one should consider depending on the goal of the study. A comparison of the previously mentioned methods is carried to evaluate their performance with samples that are not …

Mle And Bayesian Methods To Analyze Data With Missing Values Below The Limit Of Detection, Xinxin Hu

Theses and Dissertations

As pesticides are widely used in agriculture, more and more people who work at places like farm are exposed to the pesticides. According to enviroment re- searches [Villarejo; 2003; Reigart and Roberts; 1999], being exposed to some kind of pesticides like Organophosphorus (OP) insecticides has significantly effected the health of farmworkers and their family. The actual level of pesticides can be detected with some limitation for now. However, it is hard to detect when the level is below the limit of detection (LOD). Therefore, the goal of our research is to propose several different methods to analyze data …

Regression For Pooled Testing Data With Biomedical Applications, Juexin Lin

Theses and Dissertations

Since first introduced by Dorfman in 1943, pooled testing has been widely used as a cost and time effective testing protocol in the variety of applications. This dis- sertation consists of three projects that reveal the use of pooling techniques in the disease prevention from the perspective of regression. For disease monitoring and control, individual covariates information are often of practical interest and yield meaningful interpretations. It is natural to model the outcome of interest, which can be either a disease status (binary) or a biomarker concentration index (continuous), with individual-specific covariates through a regression analysis. Chapter 2 focuses on …

Fixing Metric Fixation: A Review Of The Tyranny Of Metrics, Donald Roth

Faculty Work Comprehensive List

"We should heed the author’s warning that transparent metrics and scorecards are rarely going to be effective substitutes for institutional trust."

Posting about the book The Tyranny of Metrics from In All Things - an online journal for critical reflection on faith, culture, art, and every ordinary-yet-graced square inch of God’s creation.

https://inallthings.org/fixing-metric-fixation-a-review-of-the-tyranny-of-metrics/

Assessment And Correction Of Lidar-Derived Dems In The Coastal Marshes Of Louisiana, William M. Lauve

LSU Master's Theses

The onset of airborne light detection and ranging (lidar) has resulted in expansive, precise digital elevation models (DEMs). DEMs are essential for modeling complex systems, such as the coastal land margin of Louisiana. They are used for many applications (e.g. tide, storm surge, and ecological modeling) and by diverse groups (e.g. state and federal agencies, NGOs, and academia). However, in a marsh environment, it is difficult for airborne lidar to produce accurate bare-earth measurements and even accurate elevations are rarely verified by ground truth data. The accuracy of lidar in marshes is limited by the sensor’s resolution …

Tobacco Smoking And Dementia In A Kentucky Cohort: A Competing Risk Analysis, Erin L. Abner, Peter T. Nelson, Gregory A. Jicha, Gregory E. Cooper, David W. Fardo, Frederick A. Schmitt, Richard J. Kryscio

Epidemiology and Environmental Health Faculty Publications

Tobacco smoking was examined as a risk for dementia and neuropathological burden in 531 initially cognitively normal older adults followed longitudinally at the University of Kentucky’s Alzheimer’s Disease Center. The cohort was followed for an average of 11.5 years; 111 (20.9%) participants were diagnosed with dementia, while 242 (45.6%) died without dementia. At baseline, 49 (9.2%) participants reported current smoking (median pack-years = 47.3) and 231 (43.5%) former smoking (median pack-years = 24.5). The hazard ratio (HR) for dementia for former smokers versus never smokers based on the Cox model was 1.64 (95% CI: 1.09, 2.46), while the HR for …

Jmasm 51: Bayesian Reliability Analysis Of Binomial Model – Application To Success/Failure Data, M. Tanwir Akhtar, Athar Ali Khan

Journal of Modern Applied Statistical Methods

Reliability data are generated in the form of success/failure. An attempt was made to model such type of data using binomial distribution in the Bayesian paradigm. For fitting the Bayesian model both analytic and simulation techniques are used. Laplace approximation was implemented for approximating posterior densities of the model parameters. Parallel simulation tools were implemented with an extensive use of R and JAGS. R and JAGS code are developed and provided. Real data sets are used for the purpose of illustration.

Comparative Clinical Outcomes Between Direct Oral Anticoagulants And Warfarin Among Elderly Patients With Non-Valvular Atrial Fibrillation In The Cms Medicare Population, Alpesh Amin, Oluwaseyi Dina, Allison Keshishian, Amol Dhamane, Anagha Nadkarni, Eric Carda, Cristina Russ, Lisa Rosenblatt, Jack Mardekian, Huseyin Yuce, Christine L. Baker

Publications and Research

Atrial fibrillation (AF) prevalence increases with age; > 80% of US adults with AF are aged ≥ 65 years. Compare the risk of stroke/systemic embolism (SE), major bleeding (MB), net clinical outcome (NCO), and major adverse cardiac events (MACE) among elderly non-valvular AF (NVAF) Medicare patients prescribed direct oral anticoagulants (DOACs) vs warfarin. NVAF patients aged ≥ 65 years who initiated DOACs (apixaban, dabigatran, and rivaroxaban) or warfarin were selected from 01JAN2013-31DEC2015 in CMS Medicare data. Propensity score matching was used to balance DOAC and warfarin cohorts. Cox proportional hazards models estimated the risk of stroke/SE, MB, NCO, and MACE. 37,525 …

Six-Month Outcome Of Transient Ischemic Attack And Its Mimics, Alireza Sadighi, Vida Abedi, Alia C. Stanciu, Nada El Andary, Mihai Banciu, Neil Holland, Ramin Zand

Faculty Journal Articles

Background and Objective: Although the risk of recurrent cerebral ischemia is higher after a transient ischemic attack (TIA), there is limited data on the outcome of TIA mimics. The goal of this study is to compare the 6-month outcome of patients with negative and positive diffusion-weighted imaging (DWI) TIAs (DWI-neg TIA vs. DWI-pos TIA) and also TIA mimics.

Methods: We prospectively studied consecutive patients with an initial diagnosis of TIA in our tertiary stroke centers in a 2-year period. Every included patient had an initial magnetic resonance (MR) with DWI and one-, three-, and six-month follow-up visits. The primary outcome …

A Random Forests Approach To Assess Determinants Of Central Bank Independence, Maddalena Cavicchioli, Angeliki Papana, Ariadni Papana Dagiasis, Barbara Pistoresi

Journal of Modern Applied Statistical Methods

A non-parametric efficient statistical method, Random Forests, is implemented for the selection of the determinants of Central Bank Independence (CBI) among a large database of economic, political, and institutional variables for OECD countries. It permits ranking all the determinants based on their importance in respect to the CBI and does not impose a priori assumptions on potential nonlinear relationships in the data. Collinearity issues are resolved, because correlated variables can be simultaneously considered.

Data And Metrics: Do We Need Them? What Can They Tell Us? What Can't They?, Nathan L. Tintle

Faculty Work Comprehensive List

"In our increasingly data-centric world, how do we think about data? How should we think about data?"

Posting about ­­­­­­­­using data to make informed decisions from In All Things - an online journal for critical reflection on faith, culture, art, and every ordinary-yet-graced square inch of God’s creation.

https://inallthings.org/data-and-metrics-do-we-need-them-what-can-they-tell-us-what-cant-they/

Maximum Likelihood Estimation For The Generalized Pareto Distribution And Goodness-Of-Fit Test With Censored Data, Minh H. Pham, Chris Tsokos, Bong-Jin Choi

Journal of Modern Applied Statistical Methods

The generalized Pareto distribution (GPD) is a flexible parametric model commonly used in financial modeling. Maximum likelihood estimation (MLE) of the GPD was proposed by Grimshaw (1993). Maximum likelihood estimation of the GPD for censored data is developed, and a goodness-of-fit test is constructed to verify an MLE algorithm in R and to support the model-validation step. The algorithms were composed in R. Grimshaw’s algorithm outperforms functions available in the R package ‘gPdtest’. A simulation study showed the MLE method for censored data and the goodness-of-fit test are both reliable.

Feature Selection For Longitudinal Data By Using Sign Averages To Summarize Gene Expression Values Over Time, Suyan Tian, Chi Wang

Biostatistics Faculty Publications

With the rapid evolution of high-throughput technologies, time series/longitudinal high-throughput experiments have become possible and affordable. However, the development of statistical methods dealing with gene expression profiles across time points has not kept up with the explosion of such data. The feature selection process is of critical importance for longitudinal microarray data. In this study, we proposed aggregating a gene’s expression values across time into a single value using the sign average method, thereby degrading a longitudinal feature selection process into a classic one. Regularized logistic regression models with pseudogenes (i.e., the sign average of genes across time as predictors) …

Vulnerability Of Industrial Facilities In The Lower Mississippi River Industrial Corridor To Relative Sea Level Rise And Tropical Cyclone Storm Surge, Joseph Blake Harris

LSU Doctoral Dissertations

Relative sea level rise (RSLR) and tropical cyclone-induced storm surge are major threats to the Lower Mississippi River Industrial Corridor (LMRIC) which has approximately 120 industrial complexes located within the corridor. Spatial interpolation methods were applied to the 2004 National Oceanic and Atmospheric published Technical Report #50 subsidence dataset and cross-validation techniques were used to determine the accuracy of each method. Digital elevation models (DEMs) were created for the years 2025, 2050, and 2075, based on these predictive surface of subsidence rates. Future DEMs were utilized to model RSLR and determine the extent of storm surge on the LMRIC by …