Statistical Methodology Commons^™

Mix Proportion Design Of Tunnel Shotcrete Based On Diorite Manufactured Sand, Song Funing, Wang Zegang, Liu Naifei, Song Zhanping

Journal of China & Foreign Highway

Tunnel construction produces a large amount of waste slag, which cannot be effectively utilized due to various factors. By using tunnel slag to prepare manufactured sand to replace natural sand, resources can be saved; costs can be reduced, and the environment can be protected. Based on the Xi’an‒Shiyan high-speed railway project, the physical and mechanical properties of diorite along the tunnel were tested; the physical properties and concrete performance of manufactured sand and natural sand were comparatively studied, and the effects of water-binder ratio and sand ratio on the performance of shotcrete were analyzed by designing multiple sets of mix …

Surface Deep Well Dewatering Methods For Tertiary Water-Rich Semi-Diagenetic Section Of Wangjiazhai Tunnel, Liu Chengwen, Liu Gang, Xu Hua, Wei Meng

Journal of China & Foreign Highway

The tertiary semi-diagenetic sandstone of the Wangjiazhai Tunnel on the Yunnan Linqing Expressway is characterized by loose structure, low diagenetic strength, and poor cementation. The geological disasters such as collapse, water gushing, and mud bursting are very easy to happen when the tunnel passes through the water-rich section. With the surface deep well dewatering of the tertiary water-rich semi-diagenetic section of Wangjiazhai Tunnel as an example, the surface deep well dewatering methods and key parameters for tunnel crossing the tertiary water-rich semi-diagenetic section were discussed. Based on the single well surface dewatering test, the groundwater level and strata permeability of …

Ventilation Design And On-Site Effect Testing For Construction Of Multiple Working Faces In Tianshan Shengli Tunnel, Xiong Ziyi, Jia Haiyang, Suo Feiyu, Liu Weiwei, Chen Jianxun, Yang Ziyao, Wang Heqi

Journal of China & Foreign Highway

To explore the ventilation optimization and energy saving issues in the construction of multiple working faces in extra-long highway tunnels, the air volumes required for a single working face under drilling and blasting construction conditions and TBM tunneling conditions were determined respectively based on theoretical calculations. Combined with the tunnel construction organization scheme, two ventilation schemes were proposed, and they were compared and selected according to the configured power of axial fans. Based on the recommended scheme, the layout scheme of pollutant-discharging jet fans was designed, and its feasibility was finally verified by on-site measurements of pollutant concentrations. The research …

A Prediction Method For Scale Of Karst Cave Water Inrush And Mud Outburst Based On Comprehensive Advanced Geological Prediction, Yang Weilin, Xiao Huabo, Meng Lubo, Zhang Caihong, Chen Weidong, Wang Hao

Journal of China & Foreign Highway

To improve the accuracy of water inrush and mud outburst disaster prediction during tunnel construction through karst caves, a method of first forecasting the unfavorable geological conditions of karst caves and subsequently predicting water inrush and mud outburst geological disasters was proposed in this paper. First, a karst cave advanced prediction model based on the polynomial naive Bayes algorithm was established to predict the scale grade of karst caves. Secondly, taking the scale prediction results of karst caves as the input condition for water inrush and mud outburst, a support vector machine (SVM) grade prediction model for karst cave water …

Research On Recognition Of Highway Toll Vehicles Based On Dual-View Feature Fusion Network, Xiao Qiang, Chen Xinjia, Chen Jing, Zhao Bin, Yan Kaifeng, Ding Hongwei

Journal of China & Foreign Highway

To solve the practical problems in vehicle type classification on toll roads, a deep learning network based on dual-view feature fusion, named ETCLNet, was proposed in this paper. A dual-branch architecture was adopted by the network to extract the features of vehicle head and side body images, respectively, and combined with an innovatively designed multi-scale feature extraction module, namely IPFE, and an adaptive weighting-based bilinear feature fusion (AWBF) mechanism, efficient and fine-grained vehicle feature representation was achieved. Through the design of parallel multi-scale convolutions and residual connections, the problem of gradient vanishing was effectively alleviated, and the adaptability to complex …

Analysis Of Traffic Congestion Patterns In Continuous Bottleneck Construction Zones Of Highways Under Mixed Traffic Of Passenger And Freight Vehicles, Han Hailong, Song Tailong, Ma Tianyong, Fan Zhaodong, Chen Zhexin, Chen Liang

Journal of China & Foreign Highway

To investigate the traffic congestion pattern changes in continuous bottleneck sections of highway construction zones under mixed passenger and freight traffic conditions, the spatio-temporal evolution laws of vehicle speed and lane-changing trajectory distribution in construction sections with successive lane-narrowing bottlenecks were studied. Based on measured highway data, traffic flow simulation parameters were calibrated using a genetic algorithm. By taking traffic volume and the proportion of passenger and freight vehicles as entry points, a traffic simulation experiment for continuous bottleneck construction zones under multi-factor coupling effects was constructed, and the spatio-temporal variation characteristics of speed and lane-changing trajectory distribution in the …

Analysis Of Temperature Field Of Steel Box Girders During Steam Curing Construction Process Of Steel-Uhpc Composite Bridge Decks, Wu Shang, Zhang Yongjian

Journal of China & Foreign Highway

To clarify the influence of high-temperature steam curing of steel-ultra-high performance concrete (UHPC) lightweight composite bridge deck paving on the temperature field of the steel box girder, taking a certain bridge in Hunan Province as an example, finite element numerical simulation and actual bridge testing were conducted on the temperature field of the steel box girder during the high-temperature steam curing process of the bridge deck paving. The numerical calculations were generally consistent with the test results. The analysis results indicate that under the superimposed effect of solar radiation heating and high-temperature steam curing heating, the maximum temperature of the …

Summary And Prospect Of Typical Diseases In Energy Transport Channels In Winter Cold Regions Over Past 20 Years, Jia Qinlong, Hou Zhongfei, Yin Yanping

Journal of China & Foreign Highway

To investigate the typical disease characteristics of energy transport channels in winter cold regions and guide the design for extending road service life, the causes of diseases such as pavement reflective cracks, continuous potholes on bridge decks, and failures of bridge drainage systems were analyzed based on the 20-year operation data of a 531 km in-service expressway in the coal energy region of northern Shaanxi. The research results indicate that when the asphalt pavement thickness reaches 22 cm, the reflective crack spacing of the expressway operated for 15 years can be controlled to over 50 m. Basically, no base layer …

Road Design Methods For Brt Projects Based On French Standard System : A Case Study Of A Project In West Africa, Wang Meng, Wu Cheng

Journal of China & Foreign Highway

With the continuous advancement of China ’s “Belt and Road Initiative”, Chinese enterprises have become increasingly involved in international engineering markets, undertaking numerous transportation infrastructure projects, particularly in Africa and Southeast Asia. However, international engineering projects commonly face the challenge of inconsistent design standard systems across different countries, posing significant difficulties for Chinese enterprises during project implementation. To address this issue, the differences in BRT road design under Chinese and French standards were focused on in this study, and their respective design philosophies and methods were analyzed. Taking a BRT project in a West African country as an example, field …

Bias, Structure, And Inference In Applied Network Analysis, Anna Vasenina

Dartmouth College Ph.D Dissertations

This dissertation develops mathematical and statistical methods for extracting reliable information from network data across biological applications, with an emphasis on understanding what observed network structure can and cannot resolve. The first study leverages protein–protein interaction network topology in the c-di-GMP signaling system of Pseudomonas fluorescens, showing that node centrality measures accurately classify protein domain types and that physical interaction structure contributes statistically significant predictive power for biofilm formation phenotypes across nearly 200 environments, while gene expression does not. The second study examines sampling bias in lemur-plant trophic interaction networks in Madagascar, demonstrating that differential detection of diurnal versus …

Developing A Humpback Whale Vocalization Detector Using Machine Learning Models, Lucas Kantorowski

Master's Theses

Humpback whale songs are notoriously complex. Identification of humpback whale song units requires bioacousticians to tediously listen, analyze, and annotate collected sound data. Even sparse data requires listening to the entirety of the collected acoustic data. In this study, three hours of audio containing over one-thousand humpback whale song units was collected in Monterey Bay, California.

Prior studies have seen success using convolutional neural networks by performing image classification on hundreds of hours worth of spectrograms. Our study uses traditional machine learning models, as they are less computationally demanding, and require less data.

We use time splitting and Mel-frequency cepstrum …

A Predictive Coding Account Of Spatial Working Memory Following Prophylactic Levetiracetam Administration Prior To Traumatic Brain Injury, Omeima Mutwali

Dissertations, Theses, and Capstone Projects

Traumatic brain injury (TBI) symptom prevention and remediation is an important area of research that would benefit vulnerable groups, including active-duty and veteran soldiers. These patients can sustain penetrative forces in fields of combat or in training, which result in focal lesions that trigger inflammatory and degenerative processes in the brain. Both primary and secondary injuries are associated with changes to cognition, behavior and affective state. This disease poses increased risk of epileptogenesis, as well. Given these outcomes, prior research has evaluated levetiracetam (LEV) as a prophylactic treatment for seizures, cognitive deficits and negative emotionality. LEV acts as a presynaptic …

Multi-Level Variable Selection Using A Bart-Enhanced Mixed-Effects Framework, Keming Zhang, Yaoyao Li, Jungang Zou, Sijian Wang, Bernadette A. Fausto, Liangyuan Hu

College of Health Professions Faculty Papers

Selecting important individual- and cluster-level predictors has become increasingly critical in healthcare research, where data often exhibit hierarchical structures due to collection from multiple clusters. Mixed-effects models, which account for within-cluster correlation and between-cluster heterogeneity, are a natural approach for multilevel variable selection. However, currently available variable selection methods for multilevel data are predominantly based on mixed-effects models that impose restrictive parametric assumptions, potentially limiting their utility when the underlying relationships are nonlinear or involve interactions. While nonparametric methods have shown promise for variable selection in non-clustered data, they have been much less studied in the multilevel setting. Moreover, nonparametric …

Bayesian Spatiotemporal Model For Counterfactual Estimation In Socioeconomic Studies, Duwani W. Gonzalez

Statistical Science Theses and Dissertations

Impact evaluations of regional development programs often require estimating counterfactual outcomes for a small number of treated regions using survey-based areal data. In practice, evaluators typically rely on two-group quasi-experimental methods such as propensity score matching (PSM) and Difference-in-Differences (DiD). These approaches perform poorly when only a few regions receive treatment, and when the set of observed covariates is limited or only partially relevant. Moreover, they typically do not explicitly exploit the spatial and temporal dependence present in survey-based areal data such as in ACS (American Community Survey). This dissertation develops a family of Bayesian spatial predictive models for directly …

Mitigating Parameter Identifiability Issues Through Model Calibration On The Data-Informed Active Subspace: An Example In Tumor Growth, Allison L. Lewis, Rebecca A. Everett

Biology and Medicine Through Mathematics Conference

No abstract provided.

Using Effect Sizes, Confidence Intervals, And The Bayes Factor To Better Understand The T-Test, Analysis Of Variance, And Regression Results, Holmes Finch

Perspectives on Early Childhood Psychology and Education

Null hypothesis testing is a widely used paradigm for assessing research hypotheses across the social sciences. Despite their ubiquity, researchers have discussed a number of problems and limitations to hypothesis testing and have suggested alternatives that might provide greater depth and explanation of research results. The purpose of this paper is to describe the use of several such alternatives and to show how they can be integrated with one another and with null hypothesis testing in order to provide a more holistic view of research hypotheses.

The Impatience Of Winning: An Analysis Of Time Discounting, Predictive Modeling, And The Nba Draft, Alec R. Plante

Business and Economics Honors Papers

This paper examines whether NBA draft decisions can be better explained by incorporating non-geometric time discounting into a model of general manager decision making. Using a dataset of 285 NBA draft prospects over a 12-year period, the impact of college statistics on Value Over Replacement Player (VORP) is determined, and these impact values are then used to create a “predicted” VORP for the first 4 seasons of each player’s career: a projection of what a general manager might think of a prospect’s future value given their college statistics. Following this, geometric and hyperbolic time discounting models are applied to estimate …

Do Dreams Reflect Our Culture? A Statistical Analysis On Dream Narratives, Michal Kuderski

Honors Capstones

Dreams are often viewed as personal experiences, but they may also reflect cultural influences. This project investigates whether dream content varies across cultures by analyzing written dream reports from American, Japanese, and Peruvian college students using data from DreamBank.net. The study applies text analysis techniques to identify common themes and compares language patterns, including the use of ‘I’ and 'We,' to examine differences in self-focus. Statistical methods for count data are used to evaluate these patterns, along with resampling to address differences in sample size. Preliminary findings suggest that both dream themes and language use may vary by cultural …

Base Running: A Lost Art In Baseball, Ethan York

Departmental Honors & Graduate Capstone Projects

In an era of baseball dominated by home runs and launch angles, the subtle art of baserunning is often overlooked, despite its measurable impact on winning games. Baserunning Runs (BsR) addresses this gap by quantifying the number of runs a player contributes through performance on the basepaths, capturing value beyond traditional metrics like stolen bases. This study constructs multiple regression models that predict BsR for Major League Baseball (MLB) players based on baserunning-related statistics. The primary objective is to examine the association between BsR and key predictors, including stolen bases (SB), extra bases taken (EB), and sprint speed (SS), while …

The Item Response Warehouse: What It Is, How To Use It, And Targets For Potential Improvements, Savira D. Nadela, Hansol Lee, Nishka Jain, Ayaan Gupta, Xingyi Zhang, Benjamin W. Domingue

Chinese/English Journal of Educational Measurement and Evaluation | 教育测量与评估双语期刊

The Item Response Warehouse (IRW) is a repository of harmonized item response datasets designed to support secondary analysis and methodological research in psychological and educational measurement. This paper serves as a practical guide for researchers interested in using the IRW. We describe the structure of IRW datasets and the quantitative and qualitative metadata available for dataset selection, and we demonstrate how researchers can navigate the IRW website to explore and compare available tables. We further show how the IRW R and Python packages can be used to filter datasets programmatically, download response-level data, and generate standardized citations for reproducible research …

Ownership Duration In The U.S. Business Jet Market, Yuchen Hu

SACAD: Scholarly Activities

This study analyzes ownership duration in the U.S. business jet market using FAA registry data as of February 16, 2026 (N=12,359). The analysis reveals a structured distribution with a mean of 5.86 years and a median of 5.00 years. Crucially, retention varies by acquisition status: new aircraft owners exhibit an average hold of 7.36 years, whereas pre-owned aircraft holders show a significantly higher turnover of 5.11 years, with most resales occurring within a 3–7-year window. These findings suggest that ownership behavior is driven by structured asset management and lifecycle planning, providing a predictive framework for identifying aircraft replacement and trade-in …

Efficacy Analysis In Clinical Trials: A Comprehensive Review Of Statistical And Machine Learning Approaches, Dhrubajyoti Ghosh, Samhita Pal

Faculty Articles

Efficacy testing is a cornerstone of clinical trials, ensuring that medical interventions achieve their intended therapeutic effects. Over the decades, a wide range of statistical methodologies have been developed to address the complexities of clinical trial data, including parametric, nonparametric, Bayesian, and machine learning approaches. Parametric methods, such as t-tests, ANOVA, and LMMs, have traditionally been the foundation of efficacy testing due to their efficiency under well-defined assumptions. Nonparametric techniques, including the Friedman test, Brunner-Munzel test, and modern extensions like nparLD, have emerged as robust alternatives, particularly for skewed, ordinal, or non-normal data. Bayesian methodologies have enabled the incorporation of …

Bayesball : A Comprehensive Framework For Predicting Ucl Injury, Brady M. Pinter, Will Best Ph.D.

SPARK Symposium Presentations

Ulnar Collateral Ligament (UCL) reconstruction, commonly referred to as Tommy John Surgery, has seen a significant rise among Major League Baseball (MLB) pitchers, prompting growing interest in identifying the mechanical and performance-based factors that contribute to injury risk. While previous studies have examined these relationships using traditional frequentist approaches separately, this study combines multiple different model techniques to present a broad framework for finding significant predictors of UCL Surgery. These models include Lasso and Ridge Regression,  Principal Component Regression (PCR) , Partial Least Squares Regression (PLS) , Random Forest, Multiple Linear Regression, and a Bayesian Statistical Model. Using these models, …

Implementing A Clustering Framework On Distributional Bee Data, Roheel Nawaz

Research and Creativity Symposium

Understanding spatial patterns in biodiversity is important for identifying how ecological communities are structured across landscapes. Clustering methods provide a useful way to detect non-random species distributions and reveal potential environmental or geographic influences. In this study, we applied a clustering framework to a large long-term bee abundance dataset from the Mid-Atlantic United States to evaluate community structure across regions of Maryland, Delaware, and Washington, D.C.

The dataset included over 1,100 sites and more than 3,000 transects. Because sampling methods were not fully standardized, abundance data were converted to presence/absence and analyzed using the Jaccard index to measure site similarity. …

A General Weighting Theory For Ensemble Learning: Beyond Variance Reduction Via Spectral And Geometric Structure, Ernest Fokoue

Articles

Ensemble learning is traditionally justified as a variance-reduction strategy, explaining its strong performance for unstable predictors such as decision trees. This explanation, however, does not account for ensembles constructed from intrinsically stable estimators-including smoothing splines, kernel ridge regression, Gaussian process regression, and other regularized reproducing kernel Hilbert space (RKHS) methods whose variance is already tightly controlled by regularization and spectral shrinkage. This paper develops a general weighting theory for ensemble learning that moves beyond classical variance-reduction arguments. We formalize ensembles as linear operators acting on a hypothesis space and endow the space of weighting sequences with geometric and spectral constraints. …

Learning Ordinal Geometry: Semantic–Aware Kernels For Ordered Categorical Data, Ernest Fokoue

Articles

Ordinal data arise ubiquitously in survey research, psychology, medicine, economics, and recommender systems, yet kernel methods for such data typically rely on either nominal encodings or arbitrary numeric codings. The former discards order information; the lat- ter imposes a fictitious metric structure. This paper develops a principled framework for kernel design on ordinal scales and introduces a new class of Semantic–Aware Ordinal Ker- nels (SAOK) that simultaneously capture ordinal order and semantic proximity between categories. We begin by formalizing order–preserving embeddings of finite chains and characterizing a broad family of chain distances that are conditionally negative definite. Through Schoen- berg …

Selecting Without Replacement From A Population Of Bands Of Serially Connected Objects, James E. Marengo, Dominick Banasik, Joseph Voelkel, David L. Farnsworth

Articles

The sampling procedure from a finite population of objects that are serially attached into bands is described and analyzed. One object is randomly selected and removed at a time, which results in that object’s band being broken into two bands or shortened by one object. The main result gives the probability of choosing an object that is part of a band of serially connected objects of any specified size at each stage of the selection process.

Empirical Comparisons Of Partial Dimension Reduction Algorithms In High-Dimensional Regression, Nathan Greenfield

Master's Theses

In high-dimensional regression problems, dimension reduction methods are often used to address the challenges of multicollinearity and estimation instability. Partial dimension reduction extends these ideas by applying dimension reduction to a subset of the predictors, while the remaining predictors are modeled without compression. This approach is particularly useful when it is important to retain variability and interpretability in certain predictors.

This thesis investigates the empirical performance of partial dimension reduction algorithms and introduces a novel algorithm, Iterative Partial Residual (IPR). Two algorithms are considered: a baseline algorithm, Marginal Residual (MR), and the proposed IPR method. Their predictive performance is evaluated …

Statistical Analysis Of Log Transformation Effectiveness In Air Traffic Movement Forecasting During Covid-19 In South Africa, John Lehlaka Masekoameng

Journal of Aviation Technology and Engineering

This study evaluates the effectiveness of log transformation in enhancing multiple regression models used to forecast air traffic movements (ATMs) in South Africa during the COVID-19 pandemic. Using 60 monthly observations from October 2016 to September 2021, the analysis incorporates variables such as revenue, lockdown levels, COVID-19 metrics, exchange rates, gross domestic product, and population. Two models are compared: one using raw ATMs and another with log-transformed ATMs as the dependent variable.

While the untransformed model shows stronger explanatory power (R² = 0.904, adjusted R² = 0.891) compared to the log-transformed model (R² = 0.772, adjusted R² = 0.741), the …

Comparative Machine Learning Models For Disease Risk Prediction, Mercy Mawusi Agbley

Theses, Dissertations and Capstones

Accurate prediction of disease outcomes is crucial for improving clinical decision-making and enabling early intervention. This study compares the performance of various statistical and machine learning models for clinical risk prediction using two healthcare datasets: diabetic retinopathy and heart disease. The models assessed include Logistic Regression, LASSO, k-Nearest Neighbors (KNN), Support Vector Machines (SVM), Neural Networks, Random Forests, Gradient Boosting Machines (GBM), and a stacked ensemble model. Prior to modeling, datasets were split into train and test sets. Standardization was applied to numeric features whilst categorical features were one-hot encoded. These transformations were later applied to the test set. Principal …