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- Multiple imputation (Statistics) (4)
- Missing observations (Statistics) (3)
- Survival analysis (Biometry) (3)
- Cardiovascular system (2)
- Food habits (2)
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- HIV (2)
- Monte Carlo method (2)
- Multiple Imputation (2)
- Observation (Scientific method) (2)
- Raman spectroscopy (2)
- Violence (2)
- Women (2)
- AIDS (Disease) (1)
- African American men (1)
- Air quality (1)
- Alzheimer's disease (1)
- Analysis of Variance (1)
- Analysis of means (1)
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- Anaplasmosis (1)
- Artificial neural networks (1)
- Atmospheric temperature (1)
- Atmospheric waves (1)
- Babesiosis (1)
- Bayes method (1)
- Big data (1)
- Binary Classification (1)
- Biometry (1)
- Biostatistics (1)
- Birth weight (1)
Articles 1 - 28 of 28
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 …
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 …
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 …
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 …
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:
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.
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.
Raman Spectroscopy Of Blood Serum And Cerebrospinal Fluid And Multivariate Data Analysis For Alzheimer's Disease Diagnostics, Elena Ryzhikova
Raman Spectroscopy Of Blood Serum And Cerebrospinal Fluid And Multivariate Data Analysis For Alzheimer's Disease Diagnostics, Elena Ryzhikova
Legacy Theses & Dissertations (2009 - 2024)
The efficient and accurate diagnosis at the early stages of dementia is a key moment for effective treatment and productive research to find a new ways to combat the disease. It is especially true for Alzheimer's disease (AD) for which there is no effective cure, but several treatments are known to allow slowing down the degenerative processes. Alzheimer's disease (AD) displays only non-specific clinical symptoms of mental decline for decades after the initiation and is very challenging to differentiate even at the later stages when it becomes very aggressive. Despite the great need, current diagnostic tests are unable to diagnose …
New Matching Algorithm-- : Outlier First Matching (Ofm) And Its Performance On Propensity Score Analysis (Psa) Under New Stepwise Matching Framework (Smf), Yi Sun
Legacy Theses & Dissertations (2009 - 2024)
An observational study is an empirical investigation of treatment effect when randomized experimentation is not ethical or feasible (Rosenbaum 2009). Observational studies are common in real life due to the following reasons: a) randomization is not feasible due to the ethical or financial reason; b) data are collected from survey or other resources where the object and design of the study has not been determined (e.g. retrospective study using administrative records); c) little knowledge on the given region so that some preliminary studies of observational data are conducted to formulate hypotheses to be tested in subsequent experiments. When statistical analysis …
Roughened Random Forests For Binary Classification, Kuangnan Xiong
Roughened Random Forests For Binary Classification, Kuangnan Xiong
Legacy Theses & Dissertations (2009 - 2024)
Binary classification plays an important role in many decision-making processes. Random forests can build a strong ensemble classifier by combining weaker classification trees that are de-correlated. The strength and correlation among individual classification trees are the key factors that contribute to the ensemble performance of random forests. We propose roughened random forests, a new set of tools which show further improvement over random forests in binary classification. Roughened random forests modify the original dataset for each classification tree and further reduce the correlation among individual classification trees. This data modification process is composed of artificially imposing missing data that are …
Non-Likelihood Based Model Evaluation And Comparison With Application To Genetic And Clinical Hiv-1 Outcomes, Ashley Elise Giambrone
Non-Likelihood Based Model Evaluation And Comparison With Application To Genetic And Clinical Hiv-1 Outcomes, Ashley Elise Giambrone
Legacy Theses & Dissertations (2009 - 2024)
Although treatment for human immunodeficiency virus type-1 (HIV-1) has undergone drastic change and morbidity and mortality has decreased over time, the development of drug-resistant HIV-1 is of concern for the long-term antiretroviral treatment of infected individuals. Drug-resistant virus is known to manifest with potentially complex mutational patterns in the HIV-1 genotype sequence and is associated with decreased response to therapy. Resistance occurs either as a result of development of mutations in the viral genome under selective drug pressure or as a result of naturally occurring polymorphisms. The most effective treatment methods are still debated at this time; however, current treatment …
Augmenting Program Data With Secondary Data Sources To Improve The Quality Of Existing Statistics : Four Examples From The New York State Department Of Health Hospital-Acquired Infection Reporting Program, Valerie Benson Haley
Legacy Theses & Dissertations (2009 - 2024)
The objective of this dissertation is to illustrate the novel application of methods that can be used to improve the accuracy of hospital-acquired infection (HAI) rates. Public reporting of HAI rates is relatively new. New York was one of the first states to mandate reporting in acute care hospitals (2007), followed by national pay-for-reporting in 2011, and national value-based purchasing in 2013. Given the financial ramifications of public reporting, it is critical that the data are validated and adjusted for differences in underlying risk among patient populations so that hospital performance can be fairly compared. However, limited information on the …
Flexible Variable And Model Selection With Ordinal Categorical Responses And Multiple Covariates, Wan-Hsiang Hsu
Flexible Variable And Model Selection With Ordinal Categorical Responses And Multiple Covariates, Wan-Hsiang Hsu
Legacy Theses & Dissertations (2009 - 2024)
Ordered categorical responses are common in many applied studies; moreover, with the rapid growth of computational power and technologies, ultrahigh dimensional data becomes very widespread. For example, there could be ten thousands of dimensions in a gene expression data and of interest is to classify the disease stage with specific genes and predict a clinical prognosis by using these specific genes. However, there are some unique challenges, including (1) the curse of dimensionality and (2) the modeling strategy for allowing dynamic covariate effects. Thus, variable selection for mining ultrahigh dimensional data and flexible modeling strategy for allowing dynamic covariate effects …
Association Between Chemical Constituents Of Particulate Matter And Cardiovascular And Respiratory Morbidities In Nys, Rena Jones
Legacy Theses & Dissertations (2009 - 2024)
Improved understanding of health risks from short- and long-term exposure to fine particulate matter (PM2.5) constituents may explain seasonal and geographic heterogeneity in PM2.5-health associations and inform control efforts targeting PM sources. Few studies have examined PM species health effects; most have been limited by their exposure assessments and modeling approaches. The goals of this project were to improve the PM exposure assessment and explore relationships between PM2.5 species and health in acute and chronic contexts.
Variance-Mean Relationships To Analyze Large Survey Data With Application To Health Expenditure Data, Wenli Luo
Variance-Mean Relationships To Analyze Large Survey Data With Application To Health Expenditure Data, Wenli Luo
Legacy Theses & Dissertations (2009 - 2024)
A great deal of work has been done in cost analysis in the last several decades. However, relatively little has been done to learn how efficiently to address the relationship between the variance and mean of the response distribution and how this will affect the choice of an appropriate generalized linear model.