Physical Sciences and Mathematics Commons^™

Dna Methylation And Its Association With Prenatal Exposures And Pregnancy Outcomes, Jennifer Straughen

USF Tampa Graduate Theses and Dissertations

Altered DNA methylation may lead to suboptimal fetal programming, increasing the risk of adverse pregnancy outcomes such as small for gestational age (SGA); however, few studies have examined the associations between DNA methylation, prenatal exposures, and fetal outcomes. Cross-sectional data from a larger, ongoing study were used to assess the impact of prenatal smoking on gene specific methylation of umbilical cord blood derived DNA and to investigate the association between gene-specific methylation and risk of SGA. The association between gene-specific DNA methylation and birthweight was also assessed. Maternal and infant covariates were abstracted from medical records, cigarette smoke exposure was …

Evaluation Of Common Inherited Variants In Mitochondrial-Related And Microrna-Related Genes As Novel Risk Factors For Ovarian Cancer, Jennifer Permuth Wey

USF Tampa Graduate Theses and Dissertations

Epithelial ovarian cancer (EOC) is a leading cause of morbidity and mortality among women in the United States, and the etiology is incompletely understood. Common, low penetrant genetic variants such as single nucleotide polymorphisms (SNPs) likely contribute to a significant proportion of EOC. We examined whether SNPs in two understudied yet biologically important types of genes, mitochondrial-related and miRNA-related genes, may contribute to EOC susceptibility using data from a large, homogeneous study population of 1,815 EOC cases and 1,900 controls (frequency-matched on age-group and race/ethnicity) genotyped through stage 1 of an ongoing genome-wide association study. Inter-individual variation in genes involved …

Oracle And Multiple Robustness Properties Of Survey Calibration Estimator In Missing Response Problem, Kwun Chuen Gary Chan

UW Biostatistics Working Paper Series

In the presence of missing response, reweighting the complete case subsample by the inverse of nonmissing probability is both intuitive and easy to implement. However, inverse probability weighting is not efficient in general and is not robust against misspecification of the missing probability model. Calibration was developed by survey statisticians for improving efficiency of inverse probability weighting estimators when population totals of auxiliary variables are known and when inclusion probability is known by design. In missing data problem we can calibrate auxiliary variables in the complete case subsample to the full sample. However, the inclusion probability is unknown in general …

Modification And Improvement Of Empirical Likelihood For Missing Response Problem, Kwun Chuen Gary Chan

UW Biostatistics Working Paper Series

An empirical likelihood (EL) estimator was proposed by Qin and Zhang (2007) for a missing response problem under a missing at random assumption. They showed by simulation studies that the finite sample performance of EL estimator is better than some existing estimators. However, the empirical likelihood estimator does not have a uniformly smaller asymptotic variance than other estimators in general. We consider several modifications to the empirical likelihood estimator and show that the proposed estimator dominates the empirical likelihood estimator and several other existing estimators in terms of asymptotic efficiencies. The proposed estimator also attains the minimum asymptotic variance among …

Modification And Improvement Of Empirical Liklihood For Missing Response Problem, Gary Chan

UW Biostatistics Working Paper Series

An empirical likelihood (EL) estimator was proposed by Qin and Zhang (2007) for a missing response problem under a missing at random assumption. They showed by simulation studies that the finite sample performance of EL estimator is better than some existing estimators. However, the empirical likelihood estimator does not have a uniformly smaller asymptotic variance than other estimators in general. We consider several modifications to the empirical likelihood estimator and show that the proposed estimator dominates the empirical likelihood estimator and several other existing estimators in terms of asymptotic efficiencies. The proposed estimator also attains the minimum asymptotic variance among …

Minimum Description Length Measures Of Evidence For Enrichment, Zhenyu Yang, David R. Bickel

COBRA Preprint Series

In order to functionally interpret differentially expressed genes or other discovered features, researchers seek to detect enrichment in the form of overrepresentation of discovered features associated with a biological process. Most enrichment methods treat the p-value as the measure of evidence using a statistical test such as the binomial test, Fisher's exact test or the hypergeometric test. However, the p-value is not interpretable as a measure of evidence apart from adjustments in light of the sample size. As a measure of evidence supporting one hypothesis over the other, the Bayes factor (BF) overcomes this drawback of the p-value but lacks …

Predicting Treatment Efficacy Via Quantitative Mri: A Bayesian Joint Model, Jincao Wu, Tim Johnson

The University of Michigan Department of Biostatistics Working Paper Series

The prognosis for patients with high-grade gliomas is poor, with a median survival of one year. Treatment efficacy assessment is typically unavailable until 5{6 months post diagnosis. Investigators hypothesize that quantitative MRI (qMRI) can assess treatment efficacy three weeks after therapy starts, thereby allowing salvage treatments to begin earlier. The purpose of this work is to build a predictive model of treatment efficacy using qMRI data and to assess its performance. The outcome is one-year survival status. We propose a joint, two-stage Bayesian model. In stage I, we smooth the image data with a multivariate spatio-temporal pairwise dierence prior. We …

Efficient Measurement Error Correction With Spatially Misaligned Data, Adam A. Szpiro, Lianne Sheppard, Thomas Lumley

UW Biostatistics Working Paper Series

Association studies in environmental statistics often involve exposure and outcome data that are misaligned in space. A common strategy is to employ a spatial model such as universal kriging to predict exposures at locations with outcome data and then estimate a regression parameter of interest using the predicted exposures. This results in measurement error because the predicted exposures do not correspond exactly to the true values. We characterize the measurement error by decomposing it into Berkson-like and classical-like components. One correction approach is the parametric bootstrap, which is effective but computationally intensive since it requires solving a nonlinear optimization problem …

Global Dimension Of Ci: Compete Or Collaborate, Arden L. Bement Jr.

PPRI Digital Library

No abstract provided.

Reconstructability Analysis Of Epistasis, Martin Zwick

Systems Science Faculty Publications and Presentations

The literature on epistasis describes various methods to detect epistatic interactions and to classify different types of epistasis. Reconstructability analysis (RA) has recently been used to detect epistasis in genomic data. This paper shows that RA offers a classification of types of epistasis at three levels of resolution (variable-based models without loops, variable-based models with loops, state-based models). These types can be defined by the simplest RA structures that model the data without information loss; a more detailed classification can be defined by the information content of multiple candidate structures. The RA classification can be augmented with structures from related …

Like Mother Like Child: An Investigation Of Mother Characteristics And Child Temperaments, Tempus Fugitt

Statistics

Much research has gone into what biological and social factors raise the risk of children developing cognitive, social, or behavioral problems. This project looks at what characteristics of the mother are significantly associated with different temperaments in the child which may predict problems developed in the child later in life. These characteristics include mother’s age, her education level, household income, parenting attitudes, involvement with the child, and drug and alcohol use. Data was used from the Fragile Families and Child Wellbeing Study conducted by the Office of Population Research at Princeton University. Cumulative logistic regression was used to analyze the …

Optimal Designs Approach To Portfolio Selection, Etukudo A. I.

CBN Journal of Applied Statistics (JAS)

In order to obtain the best tradeoff between risk and return, optimization algorithms are particularly useful in asset allocation in a portfolio mix. Such algorithms and proper solution techniques are very essential to investors in order to circumvent distress in business outfits. In this paper, we show that by minimizing the total variance of the portfolio involving stocks in two Nigerian banks which is a measure of risk, optimal allocation of investible funds to the portfolio mix is obtained. A completely new solution technique – modified super convergent line series algorithm which makes use of the principles of optimal designs …

Relationship Between Inflation And Stock Market Returns: Evidence From Nigeria, Omotor G. Douglason

CBN Journal of Applied Statistics (JAS)

The linkage between stock prices and inflation has been subjected to extensive research in the past decades and has arouse the interests of academics, researchers, practitioners and policy makers globally, particularly since the 1990s. The issue has been the apparent anomaly of the negative relationship between inflation and stock market returns as most studies in the industrialized economies have shown. This paper investigates this relationship using monthly and quarterly data of Nigeria for the period 1985 to 2008. The findings of this paper seem to suggest that stock market returns may provide an effective hedge against inflation in Nigeria.

Statistics For National Development, Sani I. Doguwa

CBN Journal of Applied Statistics (JAS)

Good statistics that has been collected according to agreed good practices are crucial as a tool for development. Gross domestic product (GDP) and other measures of economic activity such as Gross National Income (GNI) together with their individual components, show how the economy is responding to government policy and other influences. The balance of payments can demonstrate the requirement for policy adjustments and is also one of the indicators scrutinised by potential foreign investors in the country. Agricultural statistics clearly have implications for longer-term planning, particularly if they show a move away from the land into urban areas or a …

Monetary And Fiscal Policy Interactions In Nigeria: An Application Of A State-Space Model With Markov-Switching, Chuku V. Chuku

CBN Journal of Applied Statistics (JAS)

This paper uses quarterly data to explore the monetary and fiscal policy interactions in Nigeria between 1970 and 2008. As a preliminary exercise, the paper examines the nature of fiscal policies in Nigeria using a vector autoregression (VAR) model. The simulated generalized impulse response graphs generated from the VAR estimation provides evidence of a non-Ricardian fiscal policy in Nigeria. Further, the paper analyzes the interactions between monetary and fiscal policies by applying a State-space model with Markov-switching to estimate the time-varying parameters of the relationship. The evidence indicates that monetary and fiscal policies in Nigeria have interacted in a counteractive …

Is The Stock Market A Leading Indicator Of Economic Activity In Nigeria?, Alvan E. Ikoku

CBN Journal of Applied Statistics (JAS)

In an effort to address the lacuna in leading indicator studies of African economies and Nigeria in particular, this paper examines the causal relationships among stock market prices, real GDP and the index of industrial production in Nigeria, using quarterly data from 1984Q1 to 2008Q4. Granger causality tests indicate bidirectional causality between stock prices and GDP but no causality between stock prices and industrial production or between GDP and industrial production. Stock prices and GDP are found to be cointegrated, leading to the estimation of vector error correction models. Out-of-sample forecasts constructed with AR(1), ARIMA, structural ARIMA, and VEC models …

Factors, Preventions And Correction Methods For Non-Response In Sample Surveys, Godwin Nwanzu Amahi

CBN Journal of Applied Statistics (JAS)

Missing survey data occur because of unit and item non-response. This is practically independent of the method of data collection. As a result of the bias that non-response sometimes introduces in survey estimates, identifying factors that promote it, and taking measures of prevention and correction methods are clearly necessary. The standard method to compensate for unit non-response is by weighting adjustment, while item non-responses are handled by some form of imputation. This paper reviews factors that give rise to nonresponse and the corresponding methods used for its prevention and control. It also discusses their properties.

Addressing The Problem Of Non-Response And Response Bias, Fabian C. Okafor

CBN Journal of Applied Statistics (JAS)

Survey planners and analysts in Nigeria have devoted much more attention to sampling errors at the expense of nonsampling errors (non-response and response errors). Sampling error is the degree to which the sample estimate differs from the average value of the characteristic due to chance. The present discussion will be centered on non-sampling error, which may present serious deficiencies in the statistics and render the survey useless. According to Platek and Gray (1986), “Non-response has been generally recognized as important measure of the quality of data since it affects the estimates by introducing a possible bias in the estimates and …

A Multivariate Latent Variable Model For Mixed – Data From Continuous And Ordinal Responses With Possibility Of Missing Responses, Ehsan B. Samani, M. Ganjali

Applications and Applied Mathematics: An International Journal (AAM)

A joint model for multivariate mixed ordinal and continuous outcomes with potentially non-random missing values in both types of responses is proposed. A full likelihood-based approach is used to obtain maximum likelihood estimates of the model parameters. Some modified Pearson residuals are also introduced where the correlation between responses are taken into account. The joint modelling of responses with the possibility of missing values requires caution since the interpretation of the fitted model highly depends on the missing mechanism assumptions that are unexaminable in a fundamental sense. A common way to investigate the influence of perturbations of model components on …

Feedback Control Of A Bioinspired Plate-Beam System, Cody W. Ray, Belinda A. Batten, John R. Singler

Mathematics and Statistics Faculty Research & Creative Works

In this paper we present a model for a plate-beam system to represent a bioinspired flexible wing. Using a Galerkin based finite element approximation to the system, we compute functional gains that can be used for sensor placement and show that a piezoceramic actuator on the beam can be used for camber control

Poisson Process Monitoring, Test And Comparison, Qing Chen

UNLV Theses, Dissertations, Professional Papers, and Capstones

The task of determining whether a sudden change occurred in the generative parameters of a time series generates application in many areas. In this thesis, we aim at monitoring the change-point of a Poisson process by method, which is characterized by a forward-backward testing algorithm and several overall error control mechanisms. With the application of this proposed method, we declare that Mount Etna is not a simple Poissonian volcano, because two different regimes divided by the change point, January 30th 1974, are identified. The validation procedures, used in a complementary fashion, by the formal hypothesis tests and graphical method will …

Concomitants Of Upper Record Statistics For Bivariate Pseudo–Weibull Distribution, Muhammad Ahsanullah, Saman Shahbaz, Muhammad Qaiser Shahbaz, Muhammad Mohsin

Applications and Applied Mathematics: An International Journal (AAM)

In this paper the Bivariate Pseudo–Weibull distribution has been defined as a compound distribution of two random variables to model the failure rate of component reliability. The distribution of r–th concomitant and joint distribution of r–th and s–th concomitant of record statistics of the resulting distribution have been derived. Single and product moments alongside the correlation coefficient have also been obtained. Recurrence relation for the single moments has also been obtained for the resulting distributions.

Reliability Measures Of A Three-State Complex System: A Copula Approach, Mangey Ram

Applications and Applied Mathematics: An International Journal (AAM)

Improvement in reliability and production play a very important role in system design. The two key factors, considered in predicting system reliability, are failure distribution of the component and system configuration. This research discusses the mathematical modeling of a highly reliable complex system, which is in three states i.e. normal, partial failed (degraded state) and complete failed state. The system, partial failed is due to the partial failure of internal components or redundancies and completely failed is due to catastrophic failure of the system. Repair rates are general functions of the time spent. All the transition rates are constant except …

Approximate Approach To The Das Model Of Fractional Logistic Population Growth, S. Das, P. K. Gupta, K. Vishal

Applications and Applied Mathematics: An International Journal (AAM)

In this article, the analytical method, Homotopy perturbation method (HPM) has been successfully implemented for solving nonlinear logistic model of fractional order. The fractional derivatives are described in the Caputo sense. Using initial value, the explicit solutions of population size for different particular cases have been derived. Numerical results show that the method is extremely efficient to solve this complicated biological model.

Robust Interval Estimation Of A Treatment Effect In Observational Studies Using Propensity Score Matching, Scott F. Kosten

Dissertations

Estimating the treatment effect between a treatment group and a control group in an observational study is a challenging problem in statistics. Without random assignment of subjects, there are likely to be differences between the treatment group and control group on a set of baseline covariates. If one of these baseline covariates is correlated to the response variable, then the difference in sample means between the groups is likely to be a biased estimate of the true treatment effect.

Propensity score matching has become an increasingly popular strategy for reducing bias in estimates of the treatment effect. This reduction in …

Confidence Intervals And Tests On The Difference Of Means Of Two Delta Distributions, Karen Grace Villarente Rosales

Dissertations

Various research fields produce data that are lognormally distributed and inflated with zero values. This type of data follows a delta distribution. In this study, we want to extensively investigate different interval and hypothesis testing methods for comparing the means of two delta populations to see which methods are optimal under different conditions of the populations.

For confidence intervals, existing MVUE methods are extended to two sample cases and compared to classical and two proposed robust methods. We investigated the performance of the classical Student's t, Welch t, and Wilcoxon-based interval to see if these methods really perform badly on …

Reference Priors For Exponential Families With Increasing Dimension, Bertrand Clarke, Subhashis Ghosal

Department of Statistics: Faculty Publications

In this article, we establish the asymptotic normality of the posterior distribution for the natural parameter in an exponential family based on independent and identically distributed data. The mode of convergence is expected Kullback-Leibler distance and the number of parameters p is increasing with the sample size n. Using this, we give an asymptotic expansion of the Shannon mutual information valid when p = pm increases at a sufficiently slow rate. The second term in the asymptotic expansion is the largest term that depends on the prior and can be optimized to give Jeffrey's prior as the reference prior in …

Coronary Heart Disease Mortality And Long-Term Exposure To Ambient Particulate Air Pollutants In Elderly Nonsmoking California Residents, Lie Hong Chen

Loma Linda University Electronic Theses, Dissertations & Projects

The purpose of this study is to assess the effect of long-term concentrations of ambient PM on risks of all causes, cardiopulmonary, coronary heart disease (CHD), total cancer, and any mention of nonmalignant respiratory disease (NMRD) mortality.

The health effects of long-term ambient air pollution have been studied with up to 30 years of follow-up in the AHSMOG cohort, a cohort of 6,338 nonsmoking white California adults. Monthly concentrations of ambient air pollutants [particulate matter(PMio), Ozone (O3), sulfur dioxide (SO2), nitrogen dioxide (NO2) or particulate matter

In the AHSMOG cohort, each increment of 10 |ig/m3 in PMio in two-pollutant models …

An Investigation Of Process Parameters To Optimize The Fiber Diameter Of Electrospun Vascular Scaffolds Through Experimental Design, Steffi Wong

Biomedical Engineering

No abstract provided.

Influence Of Sex On Long-Term Outcomes After Percutaneous Coronary Intervention With The Paclitaxel-Eluting Coronary Stent: Results Of The "Taxus Woman" Analysis, Ghada W. Mikhail Md, Robert T. Gerber Md, Phd, David A. Cox Md, Stephen G. Ellis Md, John M. Lasala Md, Phd, John A. Ormiston Mbchb, Gregg W. Stone Md, Mark A. Turco Md, Anita A. Joshi Phd, Donald S. Baim Md, Antonio Colombo Md

Department of Medicine

No abstract provided.