Statistical Methodology Commons^™

Statistical Methods To Generate Artificial Slot Floor Data For The Advancement Of Casino Related Research, Courtney Bonner, Anastasia (Stasi) D. Baran, Jason D. Fiege, Saman Muthukumarana

International Conference on Gambling & Risk Taking

Abstract:

A common difficulty when researching gambling topics is the availability of high-quality data sets for development and testing. Due to the high level of secrecy within the gambling industry, if data is obtained for research purposes it is often prohibitively obfuscated, incomplete, or aggregated. Although these data have allowed for advancement in academic work, it leaves both the researchers and readers left wondering about what would be possible if more detailed data sets were available. To mitigate the paucity of data available to researchers, we present a Markov chain-based statistical process for producing artificial event data for a simulated …

Analytical Approach For Monitoring The Behavior Of Patients With Pancreatic Adenocarcinoma At Different Stages As A Function Of Time, Aditya Chakaborty Dr, Chris P. Tsokos Dr

Biology and Medicine Through Mathematics Conference

No abstract provided.

A Monte Carlo Analysis Of Nonprobability Sampling & Post Hoc Corrections, Julia Hong

Masters Theses & Specialist Projects

Nonprobability samples are often used in place of probability samples because the former are less trouble and less expensive. Unfortunately, it is difficult to determine how well a sample represents population parameters when using nonprobability samples. Researchers attempt to mitigate the disadvantages of nonprobability sampling by performing post hoc corrections, but this adjustment may not successfully undo the effects of nonprobability sampling. To examine these effects, a Monte Carlo simulation was conducted to create a pseudo-population from which samples were drawn. Forty-one conditions were replicated 10,000 times each, with each sample consisting of 100 observations. A post-stratification adjustment was made …

That’S My Deity: An Examination Of Online Lokean Cultures Through Log-Linear Modeling, Mary Bernstein

Senior Theses

A rise in online religious communities and the growth of so-called ‘Old World’ religions are reflected in the internet’s subcultures of Neopaganism, a growing religious movement that has been documented in America since the 1960s. The religions under this umbrella movement vary drastically and include belief systems such as Wicca, Druidry, and deity worship. Belief systems under this movement lack the traditional hierarchy found in structured religion and lack a singular sacred text. As such, believers usually find and support one another not through a physical sacred place of meeting, but through an online community that acts as sacred space. …

Prevalence Of Sars-Cov-2 Antibodies In Liberty University Student Population, Emily Bonus

Senior Honors Theses

In 2020, the virus SARS-CoV-2 gained attention as it spread around the world. Its antibodies are poorly understood, and little research focuses on those with few COVID-19 complications yet large numbers of close contacts: university students. This longitudinal study recorded SARS-CoV-2 antibody presence in 107 undergraduate Liberty University students twice during early 2021. After extensive data cleaning and the application of various statistical tests and ANOVAs, the data seems to show that in the case of COVID-19 infections, SARS-CoV-2 IgM antibodies are immediately produced, and then IgG antibodies follow later. However, the COVID-19 vaccine causes the production of both IgM …

Unlocking Potential: The School-To-Prison Pipeline For Students With Disabilities, Navena F. Chaitoo

Dissertations, Theses, and Capstone Projects

This research uses quasi-experimental, matched sampling to examine the school-to-prison pipeline for students with disabilities using data from the National Longitudinal Study of Adolescent to Adult Health. This study presents novel insights into an at-risk group that has faced disproportionate rates of school discipline and incarceration. The study finds school suspension to be associated with future involvement in the criminal legal system and lower educational attainment. Disability was not found to mediate the relationship between suspension and future involvement in the criminal legal system or the relationship between suspension and academic outcomes. However, disability was found to be a statistically …

Forecasting Remission Time Of A Treatment Method For Leukemia As An Application To Statistical Inference Approach, Mahmoud Mansour, Rashad El-Sagheer, Ahmed Galal Attia, Beha S. El-Desouky Prof.

Basic Science Engineering

In this paper, Weibull-Linear Exponential distribution (WLED) has been investigated whether being it is a well-fit distribution to a clinical real data. These data represent the duration of remission achieved by a certain drug used in the treatment of leukemia for a group of patients. The statistical inference approach is used to estimate the parameters of the WLED through the set of the fitted data. The estimated parameters are utilized to evaluate the survival and hazard functions and hence assessing the treatment method through forecasting the duration of remission times of patients. A two-sample prediction approach has been applied to …

Modeling And Fitting Two-Way Tables Containing Outliers, David L. Farnsworth

Articles

A model is proposed for two-way tables of measurement data containing outliers. The two independent variables are categorical and error free. Neither missing values nor replication are present. The model consists of the sum of a customary additive part that can be fit using least squares and a part that is composed of outliers. Recommendations are made for methods for identifying cells containing outliers and for fitting the model. A graph of the observations is used to determine the outliers’ locations. For all cells containing an outlier, replacement values are determined simultaneously using a classical missing-data tool. The result is …

Biasing Estimator To Mitigate Multicollinearity In Linear Regression Model, Abdulrasheed Bello Badawaire, Issam Dawoud, Adewale Folaranmi Lukman, Victoria Laoye, Arowolo Olatunji

Al-Bahir Journal for Engineering and Pure Sciences

A new two-parameter estimator was developed to combat the threat of multicollinearity for the linear regression model. Some necessary and sufficient conditions for the dominance of the proposed estimator over ordinary least squares (OLS) estimator, ridge regression estimator, Liu estimator, KL estimator, and some two-parameter estimators are obtained in the matrix mean square error sense. Theory and simulation results show that, under some conditions, the proposed two-parameter estimator consistently dominates other estimators considered in this study. The real-life application result follows suit.

Informative Hypothesis For Group Means Comparison, Dr. Teck Kiang Tan

Practical Assessment, Research, and Evaluation

Researchers often have hypotheses concerning the state of affairs in the population from which they sampled their data to compare group means. The classical frequentist approach provides one way of carrying out hypothesis testing using ANOVA to state the null hypothesis that there is no difference in the means and proceed with multiple comparisons if the null hypothesis is rejected. As this approach is not able to incorporate order, inequality, and direction into hypothesis testing, and neither does it able to specify multiple hypotheses, this paper introduces the informative hypothesis that allows more flexibility in stating hypothesis testing and is …

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 …

Examining The Relationship Between Stomiiform Fish Morphology And Their Ecological Traits, Mikayla L. Twiss

All HCAS Student Capstones, Theses, and Dissertations

Trait-based ecology characterizes individuals’ functional attributes to better understand and predict their interactions with other species and their environments. Utilizing morphological traits to describe functional groups has helped group species with similar ecological niches that are not necessarily taxonomically related. Within the deep-pelagic fishes, the Order Stomiiformes exhibits high morphological and species diversity, and many species undertake diel vertical migration (DVM). While the morphology and behavior of stomiiform fishes have been extensively studied and described through taxonomic assessments, the connection between their form and function regarding their DVM types, morphotypes, and daytime depth distributions is not well known. Here, three …

Learning Graphical Models Of Multivariate Functional Data With Applications To Neuroimaging, Jiajing Niu

All Dissertations

This dissertation investigates the functional graphical models that infer the functional connectivity based on neuroimaging data, which is noisy, high dimensional and has limited samples. The dissertation provides two recipes to infer the functional graphical model: 1) a fully Bayesian framework 2) an end-to-end deep model.

We first propose a fully Bayesian regularization scheme to estimate functional graphical models. We consider a direct Bayesian analog of the functional graphical lasso proposed by Qiao et al. (2019).. We then propose a regularization strategy via the graphical horseshoe. We compare both Bayesian approaches to the frequentist functional graphical lasso, and compare the …

Statistical Roles Of The G-Expectation Framework In Model Uncertainty: The Semi-G-Structure As A Stepping Stone, Yifan Li

Electronic Thesis and Dissertation Repository

The G-expectation framework is a generalization of the classical probability system based on the sublinear expectation to deal with phenomena that cannot be described by a single probabilistic model. These phenomena are closely related to the long-existing concern about model uncertainty in statistics. However, the distributions and independence in the G-framework are quite different from the classical setup. These distinctions bring difficulty when applying the idea of this framework to general statistical practice. Therefore, a fundamental and unavoidable problem is how to better understand G-version concepts from a statistical perspective.

To explore this problem, this thesis establishes a new substructure …

Regression-Based Methods For Dynamic Treatment Regimes With Mismeasured Covariates Or Misclassified Response, Dan Liu

Electronic Thesis and Dissertation Repository

The statistical study of dynamic treatment regimes (DTRs) focuses on estimating sequential treatment decision rules tailored to patient-level information across multiple stages of intervention. Regression-based methods in DTR have been studied in the literature with a critical assumption that all the observed variables are precisely measured. However, this assumption is often violated in many applications. One example is the STAR*D study, in which the patient's depressive score is subject to measurement error. In this thesis, we explore problems in the context of DTR with measurement error or misclassification considered in the observed data.

The first project deals with covariate measurement …

Copulas, Maximal Dependence, And Anomaly Detection In Bi-Variate Time Series, Ning Sun

Electronic Thesis and Dissertation Repository

This thesis focuses on discussing non-parametric estimators and their asymptotic behaviors for indices developed to characterize bi-variate time series. There are typically two types of indices depending on whether the distributional information is involved. For the indices containing the distributional information of the bivariate stationary time series, we particularly focus on the index called the tail order of maximal dependence (TOMD), which is an improvement of the tail order. For the indices without distributional information of the bivariate time series, we focus on an anomaly detection index for univariate input-output systems.

This thesis integrates three articles. The first article (Chapter …

Bias-Corrected Bagging In Active Learning With An Actuarial Application, Yangxuan Xu

Undergraduate Student Research Internships Conference

The variable annuity (VA) is a modern insurance product that offers certain guaranteed protection and tax-deferred treatment. Because of the inherent complexity of guarantees’ payoff, the closed-form solution of fair market values (FMVs) is often not available. Most insurance companies depend on Monte Carlo (MC) simulation to price the FMVs of these products, which is an extremely computational intensive and time-consuming approach. The metamodeling approach can be used to circumvent the heavy computation.

In the modeling stage, the bagged tree method has proved to outperform other parametric approaches. Also, a bias-corrected (BC) bagging model was tried and showed significant improvement …

The Q-Analogue Of The Extended Generalized Gamma Distribution, Wenhao Chen

Undergraduate Student Research Internships Conference

This project introduces a flexible univariate probability model referred to as the q-analogue of the Extended Generalized Gamma (or q-EGG) distribution, which encompasses the majority of the most frequently used continuous distributions, including the gamma, Weibull, logistic, type-1 and type-2 beta, Gaussian, Cauchy, Student-t and F. Closed form representations of its moments and cumulative distribution function are provided. Additionally, computational techniques are proposed for determining estimates of its parameters. Both the method of moments and the maximum likelihood approach are utilized. The effect of each parameter is also graphically illustrated. Certain data sets are modeled with q-EGG distributions; goodness of …

Practical T-Test Power Analysis With R, Teck Kiang Tan

Practical Assessment, Research, and Evaluation

Power analysis based on the analytical t-test is an important aspect of a research study to determine the sample size required to detect the effect for the comparison of two means. The current paper presents a reader-friendly procedure for carrying out the t-test power analysis using the various R add-on packages. While there is a growing of R users in the academic that uses R as the base for carrying out research, there is a lack of reference that discusses both frequentist and Bayesian approaches and point out their distinct features for t-test power analysis. The practical aspects of the …

Dynamic Prediction For Alternating Recurrent Events Using A Semiparametric Joint Frailty Model, Jaehyeon Yun

Statistical Science Theses and Dissertations

Alternating recurrent events data arise commonly in health research; examples include hospital admissions and discharges of diabetes patients; exacerbations and remissions of chronic bronchitis; and quitting and restarting smoking. Recent work has involved formulating and estimating joint models for the recurrent event times considering non-negligible event durations. However, prediction models for transition between recurrent events are lacking. We consider the development and evaluation of methods for predicting future events within these models. Specifically, we propose a tool for dynamically predicting transition between alternating recurrent events in real time. Under a flexible joint frailty model, we derive the predictive probability of …