Statistical Methodology Commons^™

Section Form Of Open-Cut Tunnel By Ultra-Large-Diameter Shield Empty-Push Technology, Sun Chao, Zhang Guangwei

Journal of China & Foreign Highway

Based on the engineering background of the open-cut section by the shield machine with overall movement in the rapid transformation project of Wanghai Road,Shenzhen City,the structural stress and economy of three types of section forms under construction and operation conditions were analyzed to determine the optimal section design.The load-structure model was used to analyze the parameters affecting the internal force of the optimal section.The research results show that the top and bottom plates and side walls in the scheme with ribs set at the corner (scheme 3) have uniform force,and force during the construction period is close to that during …

Application Research Of Bim Technology In Highway Prefabricated Bridge Scheme Design, Li Jinlong, Wang Xinnan, Liu Dongsheng, Chen Zhongzhi

Journal of China & Foreign Highway

At present,the highway bridge scheme requires continuous adjustments and upgrading due to iterative updates of design data and refined investigation of the surrounding environment of the bridge site.This paper upgraded the traditional route design software,developed a GIS-integrated platform,built a three-dimensional environment with design data as the core,and created a bridge scheme model through parametric intelligent design.It also evaluated and optimized the bridge scheme based on the integration of the bridge model and the surrounding environment.The results show that by using BIM technology,the forward design of a bridge scheme based on a three-dimensional environment is realized.This approach automates the scale statistics …

Application Of Superelevation Detection Technology In Ship Collision Prevention System Of Cross-Sea Bridges, Song Xiaodong, Duan Min, Ren Quanli, Hu Jianan, Yang Naiheng, Chen Jingwen, Tong Jianrong

Journal of China & Foreign Highway

Cross-sea bridges are an important component of national infrastructure and an important regional transportation hub,which have a significant impact on economic development,regional integration,and cultural exchange.Ship superelevation is an important factor that threatens the safety of bridges.Therefore,superelevation detection is an important means to improve the service level of channel navigation,standardize the navigation order of ships in the water area near the bridge,and enhance the ship collision prevention ability of bridges.This paper conducted theoretical analysis and engineering feasibility research on superelevation detection by using laser alignment,laser ranging,optoelectronic detection,LiDAR detection,and machine vision.According to the superelevation detection requirements of the Hong Kong-Zhuhai-Macao Bridge,two technical …

Industrial Design And Economic Analysis Of Steel Box Girder Bridge With Conventional Span, Cui Bing, Chen Kun

Journal of China & Foreign Highway

To improve the industrial construction level of steel bridges,a prefabricated continuous steel box girder bridge was designed in this study,which is suitable for bidirectional four lanes and six lanes with spans ranging from 40 m to 80 m.The overall dimensions and local structures of the steel box girder bridge were determined according to the specifications and engineering experience,and the load-bearing capacity was checked.Modular industrial products were designed by defining the vertical and horizontal modular divisions for the steel box girders,resulting in 21 standardized modular components.Based on the concept of life cycle,an economic analysis of the prefabricated steel box girder bridge …

Design And Simulation Evaluation Of Converged Toll Collection Schemes For Senegalese Highways, Lai Zengcheng, Zhang Ning, Yang Shichun, Ding Xueqi, Ji Yanjie

Journal of China & Foreign Highway

The Senegalese highway toll collection system is inefficient,and significant congestion and delays frequently occur at toll stations in the face of sudden traffic surges during holidays.This paper examined the limitations of the existing toll collection methods on Senegalese highways and combined the image detection algorithm and electronic license plate recognition technology with the existing MTC and ETC toll collection methods to construct a converged toll collection method based on vehicle information recognition.The paper aimed to optimize the Senegalese highway toll collection system,reduce its cost of use,and improve the efficiency of toll collection.The BPV Thiès toll station in Senegal was selected …

Parametric Analysis Of Composite Slab With Steel Bar Trusses At Construction Stages, Zhang Junhao, He Jun, Tan Chao, Feng Sidong, Wang Zitong

Journal of China & Foreign Highway

To clarify the structural behavior of composite slab with steel bar trusses at key construction stages including hoisting and concrete post-pouring,a composite beam bridge with a main span of 60 m in Georgia ’s E60 Highway was investigated.A finite element model was developed by using ABAQUS to simulate the construction process and analyze the influence of parameters such as prefabricated bottom slab material,number of hoisting points,slab thickness,and number of steel bar trusses on the principal stress of concrete and mid-span deflection.The results indicate that ultra-high-performance concrete (UHPC ) prefabricated bottom slabs prevent plastic damage and enhance slab stiffness.Normal concrete (NC) …

An Analytical Prior Selection Procedure For Empirical Bayesian Analysis Using Resampling Techniques: A Simulation-Based Approach Using The Pancreatic Adenocarcinoma Data From The Seer Database, Aditya Chakraborty, Mohan D. Pant

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Introduction: In the field of medical research, empirical Bayesian analysis has emerged as an increasingly applicable approach. This statistical framework offers greater flexibility, enabling researchers to incorporate prior information and rigorously estimate parameters of interest. However, the selection of suitable prior distributions can be a challenging endeavor, with profound implications for the resulting inferences. To address this challenge, this study proposes a new analytical procedure that leverages resampling techniques to guide the choice of priors in Bayesian analysis. Subject and Methods: The study group consisted of patients who had been diagnosed and had died of pancreatic adenocarcinoma (cause-specific death) who …

Meditation In Qualitative Research For Bracketing And Beyond, Katalin Grajzel

Research Methods and Statistics: Graduate Student Scholarship

In this study, I recounted my experience using mantra meditation during a phenomenological study for the purposes of bracketing. The efficacy and purpose of bracketing have been debated from Husserl (1931), whose aimed was to achieve objectivity, to Heidegger (1962) who advocated for immersion of the researcher, through the French school (Merleau-Ponty, 1964) of middle ground, by whom bracketing was seen as the process to unearth and suspend biases for the better understanding of participants’ experiences (Arsel, 2017; Creswell & Creswell, 2017; Creswell & Poth, 2016; Fischer & Guzel, 2023). In this study, however, I propose another approach to bracketing …

Beyond Homogeneity: Exploring Causal Heterogeneity In Psychopathology, Philip B. Vinh

Theses and Dissertations

Traditional models in psychiatric research often impose assumptions of causal homogeneity, treating population-level associations as reflective of uniform underlying mechanisms. This dissertation challenges that assumption by introducing statistical and machine learning frameworks designed to detect and model causal heterogeneity in the development of psychopathology. Central to this approach is the advancement of finite mixture structural equation modeling (FM-SEM) to identify latent subgroups characterized by distinct, and sometimes opposing, causal pathways.

The dissertation comprises three integrated empirical studies. The first introduces mixDoC, a finite mixture extension of the classical Direction of Causation (DoC) model applied to twin data, enabling the detection …

Understanding The Challenges And Satisfaction Among The Medical Professional Preceptors, Cornelia Ko

West Chester University Doctoral Projects

This study evaluates the Penn Medicine Family Medicine Clerkship program through a mixed-methods approach, exploring the challenges and factors influencing the satisfaction of medical professional preceptors when precepting students. A quantitative survey with 54 preceptor participants reveals the top challenges preceptors face: workload, conflicts with patient care, and limited clinical space. Despite this, there is strong support for the program, with 89% of preceptors enjoying the role and 85% expressing willingness to continue to precept for the next three years. Finally, data analysis shows no statistical correlation between preceptor motivation with gender, ethnicity, age group, years of serving, or total …

Predicting Superconducting Critical Temperature From Composition-Derived Features: A Transparent Linear And Regularized Regression Study, Md Ahiduzzaman

Data Science and Data Mining

We study prediction of superconducting critical temperature (Tc) from 81 composition-derived descriptors across 21,263 materials. To keep the analysis transparent and repro- ducible, we focus on linear models: Ordinary Least Squares (OLS), Ridge, Lasso, and Elastic Net (ENet). All models share a single evaluation protocol (5-fold cross-validation with standardized inputs) and are compared on RMSE, MAE, and R2. On this feature set, OLS attains the best cross-validated performance (RMSE = 17.6 K, MAE = 13.3 K , R2 = 0.735), with Lasso/ENet essentially tied next (RMSE ≈ 17.7 K , R2 ≈ 0.734); Ridge underperforms (RMSE = 18.9 K , …

Comparative Analysis Of Lasso, Ridge, And Elastic Net For Variable Selection In High-Dimensional Maize Data, Md Ahiduzzaman

Data Science and Data Mining

In high-dimensional genomic data analysis, traditional linear regression techniques often struggle due to the presence of a large number of predictor variables relative to observations. Penalized regression methods such as LASSO, Ridge, and Elastic Net have emerged as effective solutions by imposing regularization, which helps in managing multicollinearity and enhancing prediction accuracy. This study applies these techniques to the Maize dataset to model the time to male flowering, selecting relevant genetic markers as predictors. Our findings suggest that Elastic Net is particularly effective for high-dimensional data with correlated variables, achieving a balance between prediction accuracy and variable selection. The results …

Hybrid Mixtures Of Factor Analyzers For High Dimensional Data, Kazeem Abiodun Kareem

Dissertations, Master's Theses and Master's Reports

Factor analysis is a powerful tool for modeling latent structures in high-dimensional data, traditional approaches assume a single global structure, limiting their ability to capture heterogeneity. The Mixture of Factor Analyzers (MFA) extends classical factor analysis by modeling data as a mixture of Gaussian-distributed local subspaces, effectively uncovering cluster-specific latent structures. However, MFA relies on Gaussian mixtures, making it sensitive to outliers and ill-suited for heavy-tailed data. The Mixture of $t$-Factor Analyzers (M$t$FA) addresses these limitations by incorporating multivariate $t$-distributions, improving robustness. Despite their advantages, both MFA and M$t$FA face significant computational challenges in high-dimensional settings, particularly due to costly …

“Regression To The Mean”: The Confluence Of Eugenics And Statistics In The 19th And 20th Centuries, Emrys G. King

Pomona Senior Theses

The work of this thesis is twofold — first, qualitatively characterizing the confluence between the British eugenics and statistics movements in the late 19th and early 20th centuries, and second, quantitatively analyzing the effect of this foundation on pedagogical materials in the growing field of statistics between 1880 and 1970. Towards the first goal, the history of the method of least squares, state statistics, and positive and negative eugenics are outlined, followed by a close reading of the foundational texts authored by Francis Galton and Karl Pearson that introduced linear regression. Towards the latter goal, English-language statistics textbooks published between …

Optimal Data Splitting Methods, Sujay Mudalgi

Theses and Dissertations

In predictive modeling, effective data splitting is crucial for creating statistically representative training and validation sets. The state-of-the-art data splitting methods are based on minimizing the energy distance between the split subsets. However, there are a number of limitations in the existing methods, which this dissertation aims to address. First, the existing methods were computationally inefficient. Thus, Chapter 2 proposes a method to scale up these approaches for big data. Here, we introduce scalable Twinning (s-Twinning), which significantly improves the execution speed of data splitting without sacrificing accuracy. Second, the existing methods did not consider the predictive relationship in the …

Complex Missing Data Problems In Education Surveys, Thomas Wesley Robertson

Electronic Theses & Dissertations (2024 - present)

Missing data are a nearly universal problem in human subjects research, including in education. However, reporting and addressing missing data is an issue, despite guidelines from the APA style guide and the What Works Clearinghouse, as well as guidance from prominent statisticians on the best methods to use. Prior research conducted in 2004 and 2014 found that in the field of education, most studies do not report or address missing data. In addition, no study has looked specifically at how missing data are reported and addressed in complex surveys. The current study has two main objectives: first, to determine if …

Safeguard Cyberspace In Ransomware Era: Risk Analysis & Cyber Insurance, Li Huang

Electronic Theses & Dissertations (2024 - present)

The increasing frequency and severity of ransomware attacks pose significant challenges for organizational cybersecurity. Fragmentation across disciplines in cyber defense has created practical gaps in the development of the necessary capabilities needed to address rapidly evolving cyber threats. This study explores the impact of ransomware attacks and the evolving role of cyber insurance as a proactive cybersecurity partner. Bridging the gap between actuarial science and cyber risk management, it proposes an interdisciplinary framework that quantifies the impact of ransomware and integrates cyber insurance into cybersecurity strategies.

The primary contribution of this study is methodology. We present a framework that remains …

Theoretical Foundations And Applied Performance Of Periodicity-Aware Imputation: Variable Bandpass Block Bootstrap Methods For Incomplete Time Series, Asmaa Ahmad

Electronic Theses & Dissertations (2024 - present)

Time series data are prevalent across a wide range of disciplines, including health surveillance, public policy, and environmental monitoring. In the presence of underlying cyclical patterns, the integrity of time series analysis depends critically on the ability to detect, model, and impute structured missing data without compromising the temporal structure. This dissertation introduces and validates a novel imputation framework that integrates the Variable Bandpass Periodic Block Bootstrap (VBPBB) into multiple imputation procedures, improving the accuracy, robustness, and interpretability of time series models under high rates of missingness and noise. The overarching goal of this dissertation was to develop and evaluate …

Evaluation Of Practical Methods To Determine If A Karst Creek Is Gaining Or Losing: Case Study Of Leith Creek, Elizabeth Jones

Graduate Theses/Dissertations

Karst landscapes are abundant in Missouri, with features such as caves, springs, and sinkholes that form through the dissolution of limestone. Leith Creek is a small stream in Polk County, Missouri fed by two springs and the shallow unconfined Springfield Plateau aquifer, a highly karstified aquifer which is made up of limestone and minor interbedded shale-mudstone units. To determine if Leith Creek is gaining or losing, stream flow, water chemistry and temperature sensors were monitored. Stream flow results required multiple visits to take measurements while temperature sensors required two visits, one to install the dataloggers and another to remove the …

Modeling Non-Normal Distributions With Mixed Third-Order Polynomials Of Standard Normal And Logistic Variables, Mohan D. Pant, Aditya Chakraborty, Ismail El Moudden

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Continuous data associated with many real-world events often exhibit non-normal characteristics, which contribute to the difficulty of accurately modeling such data with statistical procedures that rely on normality assumptions. Traditional statistical procedures often fail to accurately model non-normal distributions that are often observed in real-world data. This paper introduces a novel modeling approach using mixed third-order polynomials, which significantly enhances accuracy and flexibility in statistical modeling. The main objective of this study is divided into three parts: The first part is to introduce two new non-normal probability distributions by mixing standard normal and logistic variables using a piecewise function of …