Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- COBRA (4)
- City University of New York (CUNY) (4)
- Minnesota State University, Mankato (2)
- Brigham Young University (1)
- Duquesne University (1)
-
- East Tennessee State University (1)
- Himmelfarb Health Sciences Library, The George Washington University (1)
- Marshall University (1)
- Southern Methodist University (1)
- University of Connecticut (1)
- University of Kentucky (1)
- University of Montana (1)
- University of Nebraska - Lincoln (1)
- University of North Florida (1)
- University of Southern Maine (1)
- Keyword
-
- Statistics (2)
- <p>Mathematics.</p> <p>Statistics.</p> <p>Medical sciences.</p> <p>Medical sciences -- Statistics.</p> <p>Probabilities.</p> <p>Diabetic retinopathy.</p> <p>Heart -- Diseases.</p> <p>Machine learning.</p> <p>Statistics -- Models.</p> (1)
- Activity driven network (1)
- Age-demographic model (1)
- Area under the curve (1)
-
- Asymptotic linearity (1)
- Atopic dermatitis; Burden of disease; Comorbidities; Dermatology; Disease severity; Healthcare resource utilization; Insurance claims database (1)
- Bayesian hierarchical model (1)
- Big data (1)
- Biting rate (1)
- COVID-19 pandemic (1)
- Central mean subspace (1)
- Classification, logistic regression, linear discriminant analysis, quadratic discriminant analysis, healthcare analytics, NHANES (1)
- Clinical Research (1)
- Clinical risk prediction (1)
- Closeness (1)
- Clustering (1)
- Coast Infrastructure (1)
- Coast Statistics (1)
- Coastal Counties (1)
- Coastal Zone Management (1)
- Cross-validation (1)
- Crossover (1)
- Cummulative Logit Model (1)
- Data mining (1)
- Data reduction (1)
- Demography (1)
- Diabetic retinopathy (1)
- Digital humanities (1)
- Dimension Reduction (1)
- Publication Year
- Publication
-
- Publications and Research (3)
- Electronic Theses and Dissertations (2)
- UW Biostatistics Working Paper Series (2)
- All Graduate Theses, Dissertations, and Other Capstone Projects (1)
- CHIP Documents (1)
-
- Department of Animal Science: Faculty Publications (1)
- Dissertations, Theses, and Capstone Projects (1)
- Global Health Faculty Publications (1)
- Graduate Student Theses, Dissertations, & Professional Papers (1)
- Johns Hopkins University, Dept. of Biostatistics Working Papers (1)
- Journal of Nonprofit Innovation (1)
- Journal of Undergraduate Research at Minnesota State University, Mankato (1)
- Maine Collection (1)
- Statistical Science Theses and Dissertations (1)
- Statistics Faculty Publications (1)
- Theses, Dissertations and Capstones (1)
- U.C. Berkeley Division of Biostatistics Working Paper Series (1)
- UNF Graduate Theses and Dissertations (1)
- Publication Type
- File Type
Articles 1 - 22 of 22
Full-Text Articles in Vital and Health Statistics
Reexamining The Croton Aqueduct: A Ward-Level Microhistorical Analysis Of Infrastructure And Cholera Mortality In 1849 New York City, Alexandria R. Toothman
Reexamining The Croton Aqueduct: A Ward-Level Microhistorical Analysis Of Infrastructure And Cholera Mortality In 1849 New York City, Alexandria R. Toothman
Dissertations, Theses, and Capstone Projects
This work reexamines the Croton Aqueduct’s role in public health by shifting analysis from the citywide level to the ward level, revealing that infrastructure expansion did not produce uniform benefits across New York City. When the Croton Aqueduct opened in 1842, it was celebrated as an achievement that would deliver pure water and eliminate disease. However, only seven years after its opening, in 1849, cholera returned with greater force in the Sixth Ward. This work shows that the uneven distribution of Croton infrastructure corresponded with uneven cholera mortality rates, challenging narratives that present Croton as a singular triumph of urban …
Comparative Machine Learning Models For Disease Risk Prediction, Mercy Mawusi Agbley
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 …
A Comparative Study Of Classification Methods For Healthcare Analytics, Xueting Zhao
A Comparative Study Of Classification Methods For Healthcare Analytics, Xueting Zhao
UNF Graduate Theses and Dissertations
This thesis presents a comparative study of logistic regression, Linear Discriminant Analy- sis (LDA), and Quadratic Discriminant Analysis (QDA) for binary classification in healthcare analytics, integrating theoretical derivation, simulation, and real-data application. A facto- rial simulation study crosses the covariance structure (equal vs. unequal), predictor correla- tion (ρ ∈ {0, 0.5, 0.9}), dimensionality (p ∈ {2, 5, 10}) and sample size (n ∈ {50, 100, 200}) across 54 scenarios with 1,000 Monte Carlo replicates each. Three main findings emerge. Logistic regression and LDA are nearly interchangeable when the assumption of equal-covariance holds. QDA achieves substantially better discrimi- nation when class-specific …
Exploring The Diagnostic Potential Of Radiomics-Based Pet Image Analysis For T-Stage Tumor Diagnosis, Victor Aderanti
Exploring The Diagnostic Potential Of Radiomics-Based Pet Image Analysis For T-Stage Tumor Diagnosis, Victor Aderanti
Electronic Theses and Dissertations
Cancer is a leading cause of death globally, and early detection is crucial for better
outcomes. This research aims to improve Region Of Interest (ROI) segmentation
and feature extraction in medical image analysis using Radiomics techniques
with 3D Slicer, Pyradiomics, and Python. Dimension reduction methods, including
PCA, K-means, t-SNE, ISOMAP, and Hierarchical Clustering, were applied to highdimensional features to enhance interpretability and efficiency. The study assessed the ability of the reduced feature set to predict T-staging, an essential component of the TNM system for cancer diagnosis. Multinomial logistic regression models were developed and evaluated using MSE, AIC, BIC, and Deviance …
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
Journal of Nonprofit Innovation
Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.
Imagine Doris, who is …
Dynamic Prediction For Alternating Recurrent Events Using A Semiparametric Joint Frailty Model, Jaehyeon Yun
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 …
Modeling Covid-19 Spread In Small Colleges, Riti Bahl, Nicole Eikmeier, Alexandra Fraser, Matthew Junge, Felicia Keesing, Kukai Nakahata, Lily Reeves
Modeling Covid-19 Spread In Small Colleges, Riti Bahl, Nicole Eikmeier, Alexandra Fraser, Matthew Junge, Felicia Keesing, Kukai Nakahata, Lily Reeves
Publications and Research
We develop an agent-based model on a network meant to capture features unique to COVID-19 spread through a small residential college. We find that a safe reopening requires strong policy from administrators combined with cautious behavior from students. Strong policy includes weekly screening tests with quick turnaround and halving the campus population. Cautious behavior from students means wearing facemasks, socializing less, and showing up for COVID-19 testing. We also find that comprehensive testing and facemasks are the most effective single interventions, building closures can lead to infection spikes in other areas depending on student behavior, and faster return of test …
A Mathematical Model For Malaria With Age-Heterogeneous Biting Rate, Sho Kawakami
A Mathematical Model For Malaria With Age-Heterogeneous Biting Rate, Sho Kawakami
All Graduate Theses, Dissertations, and Other Capstone Projects
We propose a mathematical model for malaria with age-heterogeneous biting rate from mosquitos. The existence of the model, the local behavior of the disease free equilibrium are explored. Furthermore the model is extended to an optimal control problem and the corresponding adjoint equations and optimality conditions are derived. Age dependent parameter values are estimated and numerical simulations are carried out for the model. The new model better accounts for difference in biting rates of mosquitos to different age groups, and improvements in stability to the explicit algorithm. The optimal control is also shown to depend on the age distribution of …
Identifying Risk Factors Related To Premature Birth Through Binary Logistic And Proportional Odds Ordinal Logistic Regression, Clayton Elwood
Identifying Risk Factors Related To Premature Birth Through Binary Logistic And Proportional Odds Ordinal Logistic Regression, Clayton Elwood
Electronic Theses and Dissertations
Premature birth has been identified as the single greatest cause of death worldwide in children under the age of five. This thesis will implement binary logistic regression and proportional odds ordinal logistic regression to predict different levels of premature birth and identify associated risk factors. The models will be built from the Center for Disease Control and Prevention's 2014 Vital Statistics Natality Birth Data containing nearly 4 million live births within the United States. Odds ratios and confidence intervals on risk factors were produced utilizing binary logistic regression.
Statistical Modeling Of Influenza-Like-Illness In Montana Using Spatial And Temporal Methods, Benjamin A. Stark
Statistical Modeling Of Influenza-Like-Illness In Montana Using Spatial And Temporal Methods, Benjamin A. Stark
Graduate Student Theses, Dissertations, & Professional Papers
Studying air pollution and public health has been a historically important question in science. It has long been hypothesized that severe air pollution conditions lead to negative implications in basic human health. Primarily, areas thats are prone to severe degrees of human pollution are the focus of such studies. Such research relating to less populated areas are scarce, and this scarcity raises the question of how such pollution dynamics (human-made and natural) influence human health in more rural areas.
The aim of this study is to explore this hole in research; in particular we explore possible links between air pollution …
The Impact Of Truncating Data On The Predictive Ability For Single-Step Genomic Best Linear Unbiased Prediction, Jeremy T. Howard, Thomas A. Rathje, Caitlyn E. Bruns, Danielle F. Wilson-Wells, Stephen D. Kachman, Matthew L. Spangler
The Impact Of Truncating Data On The Predictive Ability For Single-Step Genomic Best Linear Unbiased Prediction, Jeremy T. Howard, Thomas A. Rathje, Caitlyn E. Bruns, Danielle F. Wilson-Wells, Stephen D. Kachman, Matthew L. Spangler
Department of Animal Science: Faculty Publications
Simulated and swine industry data sets were utilized to assess the impact of removing older data on the predictive ability of selection candidate estimated breeding values (EBV) when using single-step genomic best linear unbiased prediction (ssGBLUP). Simulated data included thirty replicates designed to mimic the structure of swine data sets. For the simulated data, varying amounts of data were truncated based on the number of ancestral generations back from the selection candidates. The swine data sets consisted of phenotypic and genotypic records for three traits across two breeds on animals born from 2003 to 2017. Phenotypes and genotypes were iteratively …
Some Dimension Reduction Strategies For The Analysis Of Survey Data, Jiaying Weng, Derek S. Young
Some Dimension Reduction Strategies For The Analysis Of Survey Data, Jiaying Weng, Derek S. Young
Statistics Faculty Publications
In the era of big data, researchers interested in developing statistical models are challenged with how to achieve parsimony. Usually, some sort of dimension reduction strategy is employed. Classic strategies are often in the form of traditional inference procedures, such as hypothesis testing; however, the increase in computing capabilities has led to the development of more sophisticated methods. In particular, sufficient dimension reduction has emerged as an area of broad and current interest. While these types of dimension reduction strategies have been employed for numerous data problems, they are scantly discussed in the context of analyzing survey data. This …
Burden Of Atopic Dermatitis In The United States: Analysis Of Healthcare Claims Data In The Commercial, Medicare, And Medi-Cal Databases, Sulena Shrestha, Raymond Miao, Li Wang, Jingdong Chao, Huseyin Yuce, Wenhui Wei
Burden Of Atopic Dermatitis In The United States: Analysis Of Healthcare Claims Data In The Commercial, Medicare, And Medi-Cal Databases, Sulena Shrestha, Raymond Miao, Li Wang, Jingdong Chao, Huseyin Yuce, Wenhui Wei
Publications and Research
Comparative data on the burden of atopic dermatitis (AD) in adults relative to the general population are limited. We performed a large-scale evaluation of the burden of disease among US adults with AD relative to matched non-AD controls, encompassing comorbidities, healthcare resource utilization (HCRU), and costs, using healthcare claims data. The impact of AD disease severity on these outcomes was also evaluated.
Mechanistic Mathematical Models: An Underused Platform For Hpv Research, Marc Ryser, Patti Gravitt, Evan R. Myers
Mechanistic Mathematical Models: An Underused Platform For Hpv Research, Marc Ryser, Patti Gravitt, Evan R. Myers
Global Health Faculty Publications
Health economic modeling has become an invaluable methodology for the design and evaluation of clinical and public health interventions against the human papillomavirus (HPV) and associated diseases. At the same time, relatively little attention has been paid to a different yet complementary class of models, namely that of mechanistic mathematical models. The primary focus of mechanistic mathematical models is to better understand the intricate biologic mechanisms and dynamics of disease. Inspired by a long and successful history of mechanistic modeling in other biomedical fields, we highlight several areas of HPV research where mechanistic models have the potential to advance the …
Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret
Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret
UW Biostatistics Working Paper Series
We have frequently implemented crossover studies to evaluate new therapeutic interventions for genital herpes simplex virus infection. The outcome measured to assess the efficacy of interventions on herpes disease severity is the viral shedding rate, defined as the frequency of detection of HSV on the genital skin and mucosa. We performed a simulation study to ascertain whether our standard model, which we have used previously, was appropriately considering all the necessary features of the shedding data to provide correct inference. We simulated shedding data under our standard, validated assumptions and assessed the ability of 5 different models to reproduce the …
Spatiotemporal Meta-Analysis: Reviewing Health Psychology Phenomena Over Space And Time., Blair T. Johnson
Spatiotemporal Meta-Analysis: Reviewing Health Psychology Phenomena Over Space And Time., Blair T. Johnson
CHIP Documents
This supplemental material is meant to support this article:
Johnson, B. T., Crowley, E., & Marrouch, N. Spatiotemporal meta-analysis: Reviewing health psychology phenomena over space and time. Health Psychology Review.
Specifically, it is a database of GDPs per capita for nations in the world between 1800 and 2015. It is archived here to support an online supplement to this article.
GDP per capita
An Evolutionary Vaccination Game In The Modified Activity Driven Network By Considering The Closeness, Dun Han, Mei Sun
An Evolutionary Vaccination Game In The Modified Activity Driven Network By Considering The Closeness, Dun Han, Mei Sun
Publications and Research
In this paper, we explore an evolutionary vaccination game in the modified activity driven network by considering the closeness. We set a closeness parameter p which is used to describe the way of connection between two individuals. The simulation results show that the closeness p may have an active role in weakening both the spreading of epidemic and the vaccination. Besides, when vaccination is not allowed, the final recovered density increases with the value of the ratio of the infection rate to the recovery rate λ/μ. However, when vaccination is allowed the final density of recovered individual first increases and …
Mathematical Modeling Of Tick-Borne Encephalitis In Humans, Amanda Kriesel, Michael Meyer, Geoffrey Peterson
Mathematical Modeling Of Tick-Borne Encephalitis In Humans, Amanda Kriesel, Michael Meyer, Geoffrey Peterson
Journal of Undergraduate Research at Minnesota State University, Mankato
Tick-Borne Encephalitis is a virus that affects ones nervous system and is transmitted from tick to human through tick bite. In recent years, the number of cases of tick-borne encephalitis in Europe has been increasing. This mathematical biological model of Tick-Borne Encephalitis was created in order to further our understanding of such phenomenon, as well as study the relationship between vectors and their hosts. Specifically, we will investigate the population model of ticks in certain regions and its correlation to tick-borne encephalitis infections in the region.
Statistical Inference For Data Adaptive Target Parameters, Mark J. Van Der Laan, Alan E. Hubbard, Sara Kherad Pajouh
Statistical Inference For Data Adaptive Target Parameters, Mark J. Van Der Laan, Alan E. Hubbard, Sara Kherad Pajouh
U.C. Berkeley Division of Biostatistics Working Paper Series
Consider one observes n i.i.d. copies of a random variable with a probability distribution that is known to be an element of a particular statistical model. In order to define our statistical target we partition the sample in V equal size sub-samples, and use this partitioning to define V splits in estimation-sample (one of the V subsamples) and corresponding complementary parameter-generating sample that is used to generate a target parameter. For each of the V parameter-generating samples, we apply an algorithm that maps the sample in a target parameter mapping which represent the statistical target parameter generated by that parameter-generating …
Is The Number Of Sick Persons In A Cohort Constant Over Time?, Paula Diehr, Ann Derleth, Anne Newman, Liming Cai
Is The Number Of Sick Persons In A Cohort Constant Over Time?, Paula Diehr, Ann Derleth, Anne Newman, Liming Cai
UW Biostatistics Working Paper Series
Objectives: To estimate the number of persons in a cohort who are sick, over time.
Methods: We calculated the number of sick persons in the Cardiovascular Health Study (CHS), a cohort study of older adults followed up to 14 years, using eight definitions of “healthy” and “sick”. We projected the number in each health state over time for a birth cohort.
Results: The number of sick persons in CHS was approximately constant for 14 years, for all definitions of “sick”. The estimated number of sick persons in the birth cohort was approximately constant from ages 55-75, after which it decreased. …
Ranking Usrds Provider-Specific Smrs From 1998-2001, Rongheng Lin, Thomas A. Louis, Susan M. Paddock, Greg Ridgeway
Ranking Usrds Provider-Specific Smrs From 1998-2001, Rongheng Lin, Thomas A. Louis, Susan M. Paddock, Greg Ridgeway
Johns Hopkins University, Dept. of Biostatistics Working Papers
Provider profiling (ranking, "league tables") is prevalent in health services research. Similarly, comparing educational institutions and identifying differentially expressed genes depend on ranking. Effective ranking procedures must be structured by a hierarchical (Bayesian) model and guided by a ranking-specific loss function, however even optimal methods can perform poorly and estimates must be accompanied by uncertainty assessments. We use the 1998-2001 Standardized Mortality Ratio (SMR) data from United States Renal Data System (USRDS) as a platform to identify issues and approaches. Our analyses extend Liu et al. (2004) by combining evidence over multiple years via an AR(1) model; by considering estimates …
The Maine Coast, A Statistical Source, Maine Coastal Program
The Maine Coast, A Statistical Source, Maine Coastal Program
Maine Collection
The Maine Coast, A Statistical Source
Maine Coastal Program, Natural Resource Planning Division, Maine State Planning Office , Augusta, Maine
First Printing June 1978 - Second Printing September 1978
Contents: Preface / Introduction / Chapter 1 - Demography / Chapter 2 - Land Use and Taxation / Chapter 3 - Economy / Chapter 4 - Housing / Chapter 5 - Transportation / Chapter 6 - Education / Chapter 7 - Recreation / Chapter 8 - Social Services / Chapter 9 - Natural Resources / References / Index