Statistics and Probability Commons^™

Evaluating Ai Sentiment Analysis, Aakriti Shah

Honors Program Theses

This paper presents a comparative analysis of human and AI performance on a sentiment analysis task involving the coding of qualitative data from community program transcripts. The results demonstrate promising but imperfect agreement between two AI models, Claude and Bing, versus three human annotators and one expert annotator using the Community Capitals framework categories. While both models achieved fair alignment with human judgment, confusion patterns emerged involving metaphorical language and text overlapping multiple categories. The findings provide a case study for benchmarking conversational AI systems against human baselines to reveal limitations and target improvements. Key gaps center around distinguishing between …

A Qualitative Analysis Of Construct Measurement Techniques Used In Industrial/Organizational Research, Benjamin Michael, Andrea F. Snell, Katie Rosneck

Williams Honors College, Honors Research Projects

This project aims to challenge the appropriateness of the methodological strategies and tools utilized within psychological research. We will look at the types of statistical modeling used and the context in which they are used, such as measurement modeling, confirmatory factor analysis, and bifactor analysis within survey development, as well as the use of psychological constructs such as extraversion and leadership. The objective of this research is to search for and recognize patterns from the content of some of the top journal articles in the field of industrial and organizational psychology. The information gained from analyzing the content of the …

Applications For Functional Data Analysis, Kacy D. Kane

Graduate Research Theses & Dissertations

Functional Data Analysis is often used in the study of data that exists over a continuum, such as time. There are two datasets that will be considered here. For the first study we have a dataset on the efficacy of a lobectomy in reduction or elimination of epileptic seizures in patients. After an initial analysis of the dataset from a multinomial model perspective, we found that there were outliers in our dataset. From there, we considered a Multinomial Mixture Model to aid in the detection of outliers. In our second dataset we are considering a social robotics dataset where the …

Macroeconomic Factors Influencing Foreign Direct Investment In Some Selected Countries In Africa, Richard Essel Mensah

Graduate Research Theses & Dissertations

This paper investigates the possible factors that influence foreign direct investment inflow rate to Africa after controlling for other macroeconomic factors. Using the heterogenous Toeplitz mixed method on a sample of 23 countries from 1998 – 2020, we find evidence of the statistical significance of a relationship between the amount of trade done in Africa and the FDI inflow rate in Africa. We also find a statistical relationship between the labor force participation rate and the FDI inflow rate to Africa. Although the Fixed effect and GLM method did not find the relationship between LFP rate and FDI inflow to …

Impacts Of Covid-19 On Industrial Growth In The United States, Emily G. Warthman, Charles J. Landis

Williams Honors College, Honors Research Projects

COVID-19 has caused massive ramifications on all parts of life in the world and industry growth/decline is not immune to it. This report will analyze nine different industries’ profit and revenue from quarterly data during the years 2009-2022. Forecast models will be generated using various methods and different techniques of validating to predict the values from Q2 2020- Q4 2022 based on historical data. After which, a comparison will be conducted between those predicted values to the actual average revenue and profit generated by order of greatest error percentage made. Thorough research will then be completed to determine if there …

Modeling The Bidirectional Relationship Between Shared-Patient Physician Networks And Patient Longitudinal Treatment Patterns: Application To Physician Risky-Prescribing, Xin Ran

Dartmouth College Ph.D Dissertations

Risky-prescribing is a pressing public health concern in the United States. Opioids, benzodiazepines, and non-benzodiazepine sedative-hypnotics (sedative-hypnotics) are three commonly-prescribed but potentially risky drug groups, prescribed alone or in combination. Physician shared-patient networks provide a unique perspective in studying physician network characteristics and structures, as well as their association with the delivery of health care. Understanding how physician shared-patient networks are related to their prescribing may inform network-based interventions targeting risky-prescribing, which is yet to be fully studied.

We investigated patient receipt of risky prescriptions and physician risky-prescribing intensity through the scope of shared-patient networks. We used retrospective Medicare insurance …

การเปรียบเทียบวิธีการใส่ค่าสูญหาย ในการวิเคราะห์การถดถอยโลจิสติก เมื่อตัวแปรตามมีการสูญหายแบบนอนอิกนอร์เรเบิล, อภิชาติ ฉัตรเรืองเลิศ

Chulalongkorn University Theses and Dissertations (Chula ETD)

งานวิจัยนี้มีวัตถุประสงค์เพื่อเปรียบเทียบวิธีการใส่ค่าสูญหาย ในการวิเคราะห์การถดถอยโลจิสติก เมื่อตัวแปรตามมีการสูญหายแบบนอนอิกนอร์เรเบิล วิธีการที่ใช้ศึกษา คือ วิธี Complete Case Analysis (CC) วิธี Mode Imputation (MODE) วิธี Expectation Maximization Algorithm (EM) วิธี Multiple Imputation (MI) วิธี Hard Cutoff Augmentation (HARDCUT) วิธี Parceling Augmentation (PARCELING) และวิธี Fuzzy Augmentation (FUZZY) งานวิจัยนี้ใช้การจำลองข้อมูลในการศึกษาตามขนาดของตัวอย่าง ร้อยละของการสูญหายของข้อมูล และระดับของการสูญหายแบบนอนอิกนอร์เรเบิล การจำลองข้อมูลในแต่ละสถานการณ์จะกระทำ 5,000 รอบ โดยมีเกณฑ์ที่ใช้เปรียบเทียบประสิทธิภาพของวิธีการใส่ค่าสูญหาย ได้แก่ ค่าเฉลี่ยของค่าเฉลี่ยความคลาดเคลื่อนกำลังสอง (Average Mean Squared Error: AMSE) ของค่าประมาณความน่าจะเป็นของการเกิดเหตุการณ์ที่สนใจ (P(Y = 1)) และค่าประสิทธิภาพสัมพัทธ์ (Relative Efficiency: RE) จากผลการทดลองสรุปได้ว่า ค่า AMSE จะลดลงเมื่อขนาดของตัวอย่างใหญ่ขึ้น และจะมีค่ามากขึ้นเมื่อร้อยละของการสูญหายของข้อมูลเพิ่มขึ้น เมื่อพิจารณาผลของระดับของการสูญหายแบบนอนอิกนอร์เรเบิลต่อค่า AMSE พบว่ามีเพียง AMSE ของวิธี MODE เท่านั้นที่มีแนวโน้มเพิ่มขึ้น เมื่อระดับของการสูญหายแบบนอนอิกนอร์เรเบิลเพิ่มขึ้น และเมื่อพิจารณาค่า RE โดยเปรียบเทียบ AMSE ของวิธี CC กับวิธีการใส่ค่าสูญหายวิธีอื่น พบว่า วิธี EM และวิธี FUZZY ให้ค่า AMSE เท่ากับ AMSE ของวิธี CC ในขณะที่ AMSE ของวิธีอื่น ๆ มีค่าน้อยกว่า AMSE ของวิธี CC

Exploring Information Leakage In Historical Stock Market Data, Edison Hua

Dissertations and Theses

Information leakage is a major concern for traders who want to execute large orders without affecting the market price. In this paper, we explore the sources and effects of information leakage in historical stock market data using various methods and metrics. We first define information leakage as a pattern caused by a trader that would otherwise not occur without the trader’s activity. Using historical data, the direct impact of a potential large trade cannot be measured, but we consider a minimal impact large trade to be one that minimizes changes to the established trading data. We then analyze how information …

Shallow Water Coral Distribution And Its Response To Climate Change, Amaury De Jesus

Dissertations and Theses

Shallow water corals are one of the main reef-building organisms that secrete carbonates as their skeletons, and therefore, are one of the major sinks of CO2 in the ocean. These reef builders are also very crucial to marine environments and human society. As the global energy demand continues rising, fossil fuel burning increases at a faster pace despite the increase in energy supply using clean and renewable energy. The increase of CO2 in the atmosphere has been shown to exacerbate global warming and may cause ocean acidification, threatening the habitat of shallow-water corals. Many recent observations show alarming signs of …

Application Of Sentiment Analysis And Machine Learning Techniques To Predict Daily Cryptocurrency Price Returns, Edward Wu

CMC Senior Theses

This paper examines the effects of social media sentiment relating to Bitcoin on the daily price returns of Bitcoin and other popular cryptocurrencies by utilizing sentiment analysis and machine learning techniques to predict daily price returns. Many investors think that social media sentiment affects cryptocurrency prices. However, the results of this paper find that social media sentiment relating to Bitcoin does not add significant predictive value to forecasting daily price returns for each of the six cryptocurrencies used for analysis and that machine learning models that do not assume linearity between the current day price return and previous daily price …

Investigating Collaborative Explainable Ai (Cxai)/Social Forum As An Explainable Ai (Xai) Method In Autonomous Driving (Ad), Tauseef Ibne Mamun

Dissertations, Master's Theses and Master's Reports

Explainable AI (XAI) systems primarily focus on algorithms, integrating additional information into AI decisions and classifications to enhance user or developer comprehension of the system's behavior. These systems often incorporate untested concepts of explainability, lacking grounding in the cognitive and educational psychology literature (S. T. Mueller et al., 2021). Consequently, their effectiveness may be limited, as they may address problems that real users don't encounter or provide information that users do not seek.

In contrast, an alternative approach called Collaborative XAI (CXAI), as proposed by S. Mueller et al (2021), emphasizes generating explanations without relying solely on algorithms. CXAI centers …

Additive P-Value Combination Test, Xing Ling

Dissertations, Master's Theses and Master's Reports

This dissertation includes four Chapters. A brief description of each chapter is organized as follows.

In Chapter 1, some developments on multiple hypotheses tests are introduced. Some preliminaries about the definition and the assumption are included.

In Chapter 2, a Stable Combination Test is proposed to combine $p$-values from multiple hypotheses tests. We show the proposed method controls the family-wise error rate at the target level and maintains asymptotically optimal power even when the elementary p-values from the individual hypotheses are dependent.

In Chapter 3, a deeper dig into the additive p-value combination test is performed. A common idea behind …

Variability In Causal Effects On A Binary Outcome And Noncompliance In A Multisite Randomized Trial, Xinxin Sun

Theses and Dissertations

Noncompliance to treatment assignment is widespread in randomized trials and presents challenges in causal inference. In the presence of noncompliance, the most commonly estimated effect of treatment assignment, also known as intent-to-treat (ITT) effect, is biased. Of interest in this setting is the complier average causal effect (CACE), the ITT effect among compliers. Further complication arises when the outcome variable is partially observed.

My research focuses on estimating the distribution of a site-specific CACE in a multisite randomized controlled trial (MRCT) by maximum likelihood (ML). Assuming compliance missing at random (MAR). We express the likelihood as an integral with respect …

Reassessing Replication: Addressing The Replication Crisis From A Statistical Perspective, Alicia Richards Phd

Theses and Dissertations

In 2015, Open Science Framework directly replicated 100 psychology studies and found astonishingly low replication rates. Since, researchers have suggested factors that may have influenced the low rates, including the metrics used to assess replications. The definitions used to decide whether a replication study was successful all suffer from flaws. Therefore, we propose a new metric for assessing replication that can estimate the likelihood a study successfully replicated rather than forcing a binary choice and accounts for study design limitations.

Using equivalence study techniques, we first propose a new metric to assess replication, defining a successful replication as one where …

Early Termination In Phase Ii Clinical Trials: Admissible Designs Using Decreasingly Informative Priors, Chen Wang

Theses and Dissertations

In Phase II clinical trials, Thall and Simon’s Bayesian posterior probability design is commonly implemented to allow for an early termination to determine whether a new treatment warrants further investigation in a larger-scale Phase III trial; this in turn requires a pre-selected prior distribution based on known clinical opinion or historical information. Moreover, this Bayesian approach can result in an issue of inflating type I error rate by monitoring interim data to inform early termination decisions. Alternatively, a Bayesian approach with the decreasingly informative prior (DIP), which is an informative yet skeptical prior, can be implemented to overcome the contentious …

Model-Based Imputation Of Below Detection Limit Missing Data And Group Selection In Bayesian Group Index Regression, Matthew Carli

Theses and Dissertations

Investigations into the association between chemical exposure and health outcomes are increasingly focused on the role of chemical mixtures, as opposed to individual chemicals. The analysis of chemical mixture data required the development of novel statistical methods, one of these being Bayesian group index regression. A statistical challenge common to all chemical mixture analyses is the ubiquitous presence of below detection limit (BDL) data. We propose an extension of Bayesian group index regression that treats both regression effects and missing BDL observations as parameters in a model estimated through a Markov Chain Monte Carlo algorithm that we refer to as …

Integrative Post-Gwas Analyses Of Psychiatric Disorders: Identifying Putative Risk Genes And Gene Sets Using Transcriptome, Proteome And Methylome Information, Huseyin Gedik

Theses and Dissertations

Genome-wide association studies (GWAS) of psychiatric disorders (PD) yield numerous loci with significant signals, but often they do not implicate specific protein coding genes. Because GWAS risk loci are enriched in expression/protein/methylation quantitative loci (e/p/mQTL, hereafter xQTL), transcriptome/proteome/methylome-wide association studies (T/P/MWAS, hereafter XWAS), which integrate information from GWAS and x-level (mRNA, protein or DNA methylation levels) coming from largest xQTL studies, can link GWAS signals to effects on specific genes. For gene level analyses, researchers use mendelian randomization (MR) methods to fine-map the association between x-levels and trait. However, none of the previous studies ever jointly analyzed XWAS of multiple …

Dynamic Overnight Effect On Next Day Stock Market Forecasting, Thomas J. Lee

Graduate Research Theses & Dissertations

Using a cross section of stocks that have high frequency trading data from 2007 to 2018, we document whether various intraday momentum patterns found in the financial literature over the years continue to hold over time. The first half hour return on the market is often seen as having predictive power over the last half hour of trading, or overnight returns are thought to reverse in the next day's first half hour of trading. We find that while there is some evidence for these patterns, especially in the earlier years, these patterns tend to weaken over time as investors take …

The Impact Of Faculty Composition On Cost Per Student: A Mixed Model Approach, Arun Sleeba

Graduate Research Theses & Dissertations

This thesis aims to explore whether research universities in the United States, specifically those classified as Carnegie I or II institutions, utilize part time contingent faculty(rPTF) as a cost saving strategy. Additionally, it sought to determine if there was a differential impact on total costs when comparing public and private universities. Employing a linear mixed effects model with random intercept and slopes, this study analyzed the relationship between rPTF (ratio of part-time to total faculty) and total cost. This study did not provide substantial evidence to support the notion despite observing a negative correlation between rPTF and total cost. Regarding …

Enhanced Maximum Likelihood Models For Underreported Variables: Extending To Multiple Claims Dimension, Shalaka Sudhanshu Sarpotdar

Graduate Research Theses & Dissertations

This thesis builds upon the foundations laid out in Xia et al. [2023], which explored the utilizationof Maximum Likelihood approach to model misrepresentation data in Generalized Linear Models (GLM) ratemaking models. We introduce the concept of “underreported variables”, a form of insurance misrepresentation where insured individuals provide inaccurate information about risk factors that influence insurance eligibility, premiums, and insured amounts. Unlike fraudulent misrepresentation, underreported variables arise from a lack of awareness regarding the insured’s mental and physical health conditions, rather than fraudulent intent. The study rigorously tests the proposed model using health insurance data and extends its applicability to other …