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- Multiple imputation (Statistics) (4)
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Articles 1 - 30 of 48
Full-Text Articles in Physical Sciences and Mathematics
Evaluating The Health Impacts Of Fruit And Vegetable Intake At The Individual Level And Food Pantry Level Among Food Pantry Users, Jiacheng Chen
Evaluating The Health Impacts Of Fruit And Vegetable Intake At The Individual Level And Food Pantry Level Among Food Pantry Users, Jiacheng Chen
Legacy Theses & Dissertations (2009 - 2024)
Background: Chronic diseases impose heavy burdens on individuals and the healthcare system in the US. Many factors were found to be associated with chronic diseases, including demographics, family history, social environmental factors, and individual behavioral factors such as diet and physical activity. Among those factors, fruit and vegetable intake can have substantial health impacts via a variety of causal pathways. Fruit and vegetable (F&V) consumption is generally lower among individuals living in households experiencing food insecurity and rely on food assistance programs. Decreased F&V intake among food pantry users may negatively impact health. However, conducting quantitative analysis on this population …
Metabolic Alterations And Cardiovascular Risk After Hepatitis C Cure In Subjects With Or At Risk For Hiv, Christophe Maxime Fokoua Dongmo
Metabolic Alterations And Cardiovascular Risk After Hepatitis C Cure In Subjects With Or At Risk For Hiv, Christophe Maxime Fokoua Dongmo
Legacy Theses & Dissertations (2009 - 2024)
Background. Hepatitis C virus (HCV) infection engenders substantial metabolic changes. These changes are altered when the virus is cleared after successful treatment. We measured these metabolic alterations that occur after HCV cure; further, we assessed whether these alterations differed in subgroups defined by patients’ characteristics.
Multiple Imputation In High-Dimensional Data With Variable Selection, Qiushuang Li
Multiple Imputation In High-Dimensional Data With Variable Selection, Qiushuang Li
Legacy Theses & Dissertations (2009 - 2024)
This dissertation focuses on the development of multiple imputation models and algorithms for high-dimensional data with variable selection structures. Leveraging on the multivariate linear mixed-effects model with missing responses for clustered data, we incorporate the variable selection routines using spike-and-slab priors within the Bayesian variable selection framework. Specific choice of these priors allow us to "force'' variables of importance (e.g. design variables or variables known to play role in missingness mechanism) into the imputation models. Our ultimate goal is to improve computational speed by removing unnecessary variables. Markov chain Monte Carlo techniques have been designed to sample from the implied …
Stability And Differential Privacy Of Stochastic Gradient Methods, Zhenhuan Yang
Stability And Differential Privacy Of Stochastic Gradient Methods, Zhenhuan Yang
Legacy Theses & Dissertations (2009 - 2024)
Recently there are a considerable amount of work devoted to the study of the algorithmic stability as well as differential privacy (DP) for stochastic gradient methods (SGM). However, most of the existing work focus on the empirical risk minimization (ERM) and the population risk minimization problems. In this paper, we study two types of optimization problems that enjoy wide applications in modern machine learning, namely the minimax problem and the pairwise learning problem.
Sampling Distribution Of Non-Overlap Indices Using Bootstrapping Procedure : A Monte Carlo Simulation Study And Empirical Demonstration, Xinyun Xu
Legacy Theses & Dissertations (2009 - 2024)
Statistics can be either parametric or non-parametric, depending on whether distributional assumptions about the data and sampling distributions are required. Parametric and non-parametric approaches each include a variety of inferential methods. These methods can be seen in the field of single-case experimental design (SCED). By reviewing one of the most used groups of statistics for SCED research (Jamshidi et al., 2022; Maggin et al., 2011), the non-overlap indices, one major issue arose. It is challenging to make inferences and interpretations about non-overlap indices. The main reason for this issue is that non-overlap indices have inconsistent and unknown sampling distributions (under …
Impact Of Inconsistent Imputation Models In Mediation Analysis, Bo Ye
Impact Of Inconsistent Imputation Models In Mediation Analysis, Bo Ye
Legacy Theses & Dissertations (2009 - 2024)
In this dissertation, we study the impact of inconsistent imputation methods in mediation analysis and its application. We present the study in three papers.
Conditional And Marginal Imputation Models For Multilevel Data, Gang Liu
Conditional And Marginal Imputation Models For Multilevel Data, Gang Liu
Legacy Theses & Dissertations (2009 - 2024)
This dissertation study extends sequential hierarchical regression imputation (SHRIMP) methods to multilevel datasets with three levels of nesting and proposes a marginal method based on marginalized multilevel model (MMM) framework. Specifically, the proposed model consists of two levels such that the first level relates the marginal mean of responses with covariates through a generalized regression model and the second level includes subject specific random effects within the same generalized regression model. To draw the inference on the population-averaged or subject-specified coefficients, the hierarchical regression and/or MMM is applied as the imputation and estimation models. We employ Markov Chain Monte Carlo …
Finite Mixture Models : Applications To Length Of Stay For Delivery Hospitalizations, Eva Williford
Finite Mixture Models : Applications To Length Of Stay For Delivery Hospitalizations, Eva Williford
Legacy Theses & Dissertations (2009 - 2024)
In the United States (U.S.), childbirth is the most common reason for hospitalization, and the maternal mortality rate per 100,000 (2017-2018) is markedly elevated in the U.S. (17.4) compared to neighboring Canada (10), the United Kingdom (7), and Japan (5) (Trends in Maternal Mortality, 2000 to 2017: Estimates by WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division). These data, the increased focus on addressing severe maternal morbidity and mortality to improve patient outcomes and reduce healthcare costs is well deserved. These women often have a longer delivery length of stay (LOS) and experience complications of varying …
Three Essays On Model Selection, Fangning Li
Three Essays On Model Selection, Fangning Li
Legacy Theses & Dissertations (2009 - 2024)
In empirical research, we often need to address the issue of what model to use given a collection of candidate models. Conventionally, we use model selection to choose one best model from the collection of candidate models based on some model selection criteria. Model averaging is a generalization of model selection in the sense that it assigns weights to candidate models and uses a weighted average to construct an aggregated model. Usually model averaging provides better performance than model selection which chooses a single candidate model based on AIC or BIC.
A Comparative Spatial And Climate Analysis Of Human Granulocytic Anaplasmosis And Human Babesiosis In New York State (2013-2018), Collin J. O'Connor
A Comparative Spatial And Climate Analysis Of Human Granulocytic Anaplasmosis And Human Babesiosis In New York State (2013-2018), Collin J. O'Connor
Legacy Theses & Dissertations (2009 - 2024)
Human granulocytic anaplasmosis (HGA) and human babesiosis are tick-borne diseases spread by Ixodes scapularis (the blacklegged or deer tick) and are the result of infection with Anaplasma phagocytophilum and Babesia microti, respectively. In New York State (NYS), incidence rates of these diseases increased concordantly until around 2013, when rates of HGA began to increase more rapidly than human babesiosis, and the spatial extent of the diseases diverged. Surveillance data of tick-borne pathogens (2007 to 2018) and reported human cases of HGA (n=4,297) and human babesiosis (n=2,986) (2013 to 2018) from the New York State Department of Health (NYSDOH) showed a …
Parsimonious Covariate Selection For Interval Censored Data, Yi Cui
Parsimonious Covariate Selection For Interval Censored Data, Yi Cui
Legacy Theses & Dissertations (2009 - 2024)
Interval censored outcomes widely arise in many clinical trials and observational studies. In many cases, subjects are only followed-up periodically. As a result, the event of interest is known only to occur within a certain interval. We provided a method to select the parsimonious set of covariates associated with the interval censored outcome. First, the iterative sure independence screening (ISIS) method was applied to all interval censored time points across subjects to simultaneously select a set of potentially important covariates; then multiple testing approaches were used to improve the selection accuracy through refining the selection criteria, i.e. determining a refined …
An Analysis Of Income And Other Associative Demographics To Charity Donation And Volunteerism, Christine Lynn Klotz
An Analysis Of Income And Other Associative Demographics To Charity Donation And Volunteerism, Christine Lynn Klotz
Legacy Theses & Dissertations (2009 - 2024)
Nongovernmental organizations have a vast institutional presence across the United States. Each year, there is an ever-increasing body of charitable organizations which span, enhance and characterize the civil sphere. Overall, charities occupy an important institutional role in society, and the individuals who help to sustain charities encompass a vital social role. This paper is particularly concerned with analyzing charitable donation and volunteering dynamics on the individual level. Using the 2014 General Social Survey data on charitableness, this paper estimates the probability of engaging in volunteerism and charitable donation within the nonprofit sector based on income level. These results suggest that …
The Effect Of Maternal Dietary Habits During Pregnancy On Neonate Leptin Methylation Patterns And Gestational Age, Sean Fitzpatrick
The Effect Of Maternal Dietary Habits During Pregnancy On Neonate Leptin Methylation Patterns And Gestational Age, Sean Fitzpatrick
Legacy Theses & Dissertations (2009 - 2024)
The health of a newborn baby is inextricably linked to the health status of its mother and in turn the mother’s diet during pregnancy. Leptin (LEP) is an adipokine hormone involved in metabolism regulation and has been linked fetal development through the hypothalamic-pituitary-adrenal axis (HPA). Prior work suggests that gestational epigenetic alterations the LEP gene may be sensitive to adverse exposures during pregnancy, which in turn could explain variation in neonate outcomes. However, no prior work has examined this possibility explicitly. The objective of this study was to investigate the association between dietary patterns of mothers during pregnancy and their …
Spatial Boundary Detection And Estimation Of Jet Stream As A Key Factor For Tornado Environments, Mingzeng Sun
Spatial Boundary Detection And Estimation Of Jet Stream As A Key Factor For Tornado Environments, Mingzeng Sun
Legacy Theses & Dissertations (2009 - 2024)
Understanding the impact of spatial patterns and processing features on health is a key element in public health and epidemiology fields. This thesis investigates these fundamental tasks using two approaches: high dimensional Kolmogorov-Zurbenko Adaptive smoothing and spatial boundary identification by rolling variation algorithm.
Depression, Sensation-Seeking Behavior And Violence As Mediators Of The Association Between Childhood Adversity And Substance Use Disorder, Calvin Wong
Legacy Theses & Dissertations (2009 - 2024)
Background:
Non-Stationary Counts With Mixture Distributions, Ziqiang Lin
Non-Stationary Counts With Mixture Distributions, Ziqiang Lin
Legacy Theses & Dissertations (2009 - 2024)
We study a new non--stationary mixture Pengram and thinning model for time series of counts that include the effect of covariate variables on the outcome variable. Properties of the model and performance are discussed. It has a simpler likelihood function than the non--stationary INAR(1) model and therefore MLE estimators for the model's parameters are easier to find. Therefore the model offers an alternative to non--stationary INAR(1).
Race, Ethnicity, And The Great Recession : A National Evaluation Of Mortgages And Subprime Lending, 2004-2010, Meghan M. O'Neil
Race, Ethnicity, And The Great Recession : A National Evaluation Of Mortgages And Subprime Lending, 2004-2010, Meghan M. O'Neil
Legacy Theses & Dissertations (2009 - 2024)
The dissertation analyzes multilevel models to predict mortgage origination and the allocation of subprime credit pre-and-post Great Recession. With representative samples from two full years of mortgage applications filed in the top 100 U.S. metropolitan areas, the dissertation uncovers evidence of persistent disparities by race and neighborhood minority concentration despite controls for socioeconomic, demographic, assimilation and housing variables. Mortgage outcomes varied by applicant race, neighborhood racial composition and neighborhood racial change. Findings suggest evidence of Fair Housing Act violations and disparate impacts towards minority homebuyers and minority neighborhoods. Results lend support for spatial assimilation theories in explaining much of the …
Stress-Strength Estimation And Its Applications In Clinical Trials, Dinesh Kumar
Stress-Strength Estimation And Its Applications In Clinical Trials, Dinesh Kumar
Legacy Theses & Dissertations (2009 - 2024)
Stress Strength model P(X
Spatio-Temporal Frequency Separation With Application Of Kolmogorov-Zurbenko Filters To The Multivariate Analysis Of Melanoma Prevalence, Edward Valachovic
Spatio-Temporal Frequency Separation With Application Of Kolmogorov-Zurbenko Filters To The Multivariate Analysis Of Melanoma Prevalence, Edward Valachovic
Legacy Theses & Dissertations (2009 - 2024)
Time Series Analysis is the observation of variables recorded across time. Observations are visualized and analysis often performed in the native time domain. It is common for a time series to be the dependent variable of more than one factor. Several factors can have concurrent and combined effects. The time domain presents an obstacle due to constructive and destructive interference of factors at each time point. Unless effects are clearly pronounced and separable, the entanglement of factors along with the presence and intensity of random variation can obscure true relationships.
Irrational Eigenvalues Of The Discrete Laplacian: A Study Of Simplical Complexes, Brian Bollen
Irrational Eigenvalues Of The Discrete Laplacian: A Study Of Simplical Complexes, Brian Bollen
Psychology
We study the behavior of eigenvalues of the discrete Laplacian of an abstract simplicial complex K when subdividing a single face of K . We show that if K is a simplex, performing this kind of restricted subdivision twice on a single face produces irrational eigenvalues for the discrete Laplacian.
Raman Spectroscopy And Chemometrics For Forensic Bloodstain Analysis : Species Differentiation, Donor Age Estimation, And Dating Of Bloodstains, Kyle C. Doty
Legacy Theses & Dissertations (2009 - 2024)
The field of forensic science is constantly growing, so the advancement of old and unreliable techniques is at the forefront of what will lead to future progress and improvement. Current methods for identification and analysis of bloodstains are underwhelming due to the insignificant amount of information provided in a destructive, unreliable, and unsafe manner. As is the purpose of this research, creating new methodologies that are rapid, nondestructive, robust, statistically reliable, and safe would significantly advance the way bloodstains are currently analyzed, while providing more useful and relevant information for investigations and criminal proceedings. Raman spectroscopy, along with advanced statistical …
Association Between Hiv And Violence Among Female Commercial Sex Workers In Ukraine : Analysis Of Bio-Behavioral Surveillance Conducted In 2015-2016, Ganna Momotyuk
Legacy Theses & Dissertations (2009 - 2024)
A cross-sectional analysis investigated the association between HIV and violence in female commercial sex workers (FCSW) in Ukraine between 10/2015 and 01/2016. Methods: 3,885 FCSW from a total of 4,300 were questioned about behavioral and social demographics and tested for HIV in mobile testing van. Results: of the 3,885 respondents, 5.89% were HIV positive, and 47.00% had experienced violence. We tested for and found that drug use was an effect modifier for the association between HIV and violence. Analyses were stratified by injecting drug use and no injecting drug use. High risk for HIV was found in the non-IDU stratum …
Computationally Efficient Multiple Imputation Routines In Clustered Data, Tugba Akkaya-Hocagil
Computationally Efficient Multiple Imputation Routines In Clustered Data, Tugba Akkaya-Hocagil
Legacy Theses & Dissertations (2009 - 2024)
Presence of missing data in correlated data settings is a non-trivial problem. Inference by multiple imputation offers a viable solution to analysts. However, the missing data problem is typically more complicated due to diverse measurement scales, skip patterns, bounds and restrictions. Sequential regression imputation also known as variable-by-variable imputation has emerged as a popular imputation modeling technique, especially in the complex data structures. In this dissertation, we develop three methods to handle incomplete data in hierarchically nested and non-nested multilevel data structures using sequential regression imputation approach.
Socio-Demographic Determinants Of Racial Disparities In Stage At Diagnosis Of Prostate Cancer In New York State, Christophe Maxime Fokoua Dongmo
Socio-Demographic Determinants Of Racial Disparities In Stage At Diagnosis Of Prostate Cancer In New York State, Christophe Maxime Fokoua Dongmo
Legacy Theses & Dissertations (2009 - 2024)
ABSTRACT
Kz Spatial Wave Separation With Applications To Atmospheric Data, Ming Luo
Kz Spatial Wave Separation With Applications To Atmospheric Data, Ming Luo
Legacy Theses & Dissertations (2009 - 2024)
Unlike one-dimensional wave reconstruction, reconstruction 2D spatial wave via Fourier Transform doesn’t look like a non-parametric algorithm. In other words, we need the wave frequency and wave direction information to recover the spatial wave via Fourier Transform, especially when the stress of noise is present. The direct consequence is that accurate estimations of wave parameters are need for reconstructing of spatial waves. To this end, we propose to improve the accuracy of motion image scale detection and parameter estimations with optimization based on Kolmogorov-Zurbenko periodogram (KZP) information. Related methods and algorithms are denoted under the name of Kolmogorov-Zurbenko wave separations. …
Causal Inference In Observational Studies With Clustered Data, Meng Wu
Causal Inference In Observational Studies With Clustered Data, Meng Wu
Legacy Theses & Dissertations (2009 - 2024)
In this thesis, we study causal inference in observational studies with clustered data.
Estimating Survival Distributions, Important Covariates And Time-Varying Associations, Yan Wu
Estimating Survival Distributions, Important Covariates And Time-Varying Associations, Yan Wu
Legacy Theses & Dissertations (2009 - 2024)
There are three papers each on a different topic in this thesis. The first paper proposes a new objective methodology to estimate any subject specific survival distribution with potential time-varying effect by adjusting approximated polynomial censored survival function with estimated censoring distribution under three different assumptions: uniform censoring, independent censoring and non-informative censoring. The coefficients of the polynomial censored survival function and underlying censoring probability are estimated at each event or censoring time point across the study time frame, which naturally accommodates potential non-proportional hazards along with time-varying effect. An extensive simulation study indicates that the proposed methods usually perform …
Two Step Parsimonious Variable Selection For Right Censored Continuous Survival Time Models, Anju Menon
Two Step Parsimonious Variable Selection For Right Censored Continuous Survival Time Models, Anju Menon
Legacy Theses & Dissertations (2009 - 2024)
Variable selection is fundamental in any kind of statistical modeling. There has been ex- tensive research by different authors on methods of variable selection from linear regression models to more complex non-linear applications. Modeling survival data especially poses challenges because of a more complicated data structure as the time variable T is usually subject to censoring. This thesis presents a two step objective approach to choose between several candidate models based on the the ability of the model to predict survival times using loss functions. Once potentially important variables are selected using a screening method called Iterative Sure Independence Screening(ISIS) …
Developing A Weibull Model Extension To Estimate Cancer Latency Times, Diana L. Nadler
Developing A Weibull Model Extension To Estimate Cancer Latency Times, Diana L. Nadler
Legacy Theses & Dissertations (2009 - 2024)
More than one-third of all Americans will be diagnosed with cancer sometime in their lives. Though their illness may be invisible now, it presents a great, and largely unexamined, opportunity to find and treat their cancers early. Early detection represents one of the most promising approaches to reduce the growing cancer burden by identifying cancer while it is localized and curable, preventing not only mortality, but also reducing morbidity and costs.
What We Can Learn From Small Units Of Analysis, Andrew Palmer Wheeler
What We Can Learn From Small Units Of Analysis, Andrew Palmer Wheeler
Legacy Theses & Dissertations (2009 - 2024)
The dissertation is aimed at advancing knowledge of the correlates of crime at small geographic units of analysis. I begin by detailing what motivates examining crime at small places, and show how aggregation creates confounds that limit causal inference. Local and spatial effects are confounded when using aggregate units, so when the researcher wishes to distinguish between these two types of effects it should guide what unit of analysis is chosen. To illustrate these differences, I generate simulations of what happens to effect estimates when you aggregate a micro level spatial effects model or presume a neighborhood effects model.