Digital Commons Network^™

Assessing Measurement Invariance In The Presence Of Testlets, Luis Andres Alvarado

Open Access Theses & Dissertations

Dealing with measurement invariance has been an issue of concern in confirmatory factor analysis for many years. It is important to establish measurement invariance across groups so that instruments may be validly used in multiple groups for comparison of the mean or summative scores. Throughout the years, many studies have considered testing for measurement invariance in factor models. However, there have been no studies that assess measurement invariance when so-called testlets should be modeled in the factor analytic model. Testlets add nuisance covariation to the model which can interfere when trying to detect measurement invariance. In the past, models have …

A Proposed Epithermal Model For The High Grade District, California, Michael Nicholas Feinstein

Open Access Theses & Dissertations

A historic gold mining district in northeastern California has not been incorporated into the global knowledge base for precious metal vein deposits. This study collected various data types which are important characteristics in the classification and understanding of vein deposits. The High Grade District (HGD) is a gold mining site located in the northeast corner of Modoc County, California, in the Warner Mountains. The Warner Mountains are composed of Tertiary eruptive centers, cropping out between valleys formed through extensional tectonics. Mineralization of the HGD displays abundant silicification, adularia, and gold; these characteristics are sufficient to classify mineralization as low-sulfidation epithermal …

Estimating Statistical Characteristics Under Interval Uncertainty And Constraints: Mean, Variance, Covariance, And Correlation, Ali Jalal-Kamali

Open Access Theses & Dissertations

In many practical situations, we have a sample of objects of a given type. When we measure the values of a certain quantity x for these objects, we get a sequence of values x1, . . . , xn. When the sample is large enough, then the arithmetic mean E of the values xi is a good approximation for the average value of this quantity for all the objects from this class. Other expressions provide a good approximation to statistical characteristics such as variance, covariance, and correlation.

The values xi come from measurements, and measurement is never absolutely accurate.

Often, …

Principal Differential Analysis With Covariates : A Simulation Study On The Effect Of The Smoothing Parameters, Indika Varuna Mallawaarachchi

Open Access Theses & Dissertations

Principal Differential Analysis deals with functional data. The word functional data refers to a collection of curves that are independent and measured on a dense grid of time points in an interval. These time points can be equally or unequally spaced. A differential equation is believed capable of capturing the features of these n curves.

Ramsay(1996) first introduced Principal Differential Analysis (PDA) as an alternative to the Principal Component Analysis(PCA). PDA finds a linear differential equation that captures features of a collection of curves, in order to have a low dimensional approximation for functional data. PDA is based on the …

Distributional Properties Of Inversions And Segmentation Algorithms For Rna Sequences, Sameera Dhananjaya Viswakula

Open Access Theses & Dissertations

Ribonucleic acid (RNA) is a long single stranded molecule made up of four types of nucleotide bases: Adenine (A), Cytosine(C), Guanine (G) and Uracil (U). It folds back on itself and forms C-G and A-U complementary base pairs. The set of such hydrogen-bonded pairs in an RNA molecule is called its secondary structure. Knowing the secondary structure of RNA is useful for understanding its biological function. Prediction of RNA secondary structure from the nucleotide sequence has been an important bioinformatics problem for over two decades.

The work in this thesis is motivated by the need to improve the secondary structure …

Drag Reduction Of A Modern Straight Truck, Drew Landman, Matthew Cragun, Mike Mccormick, Richard Wood

Mechanical & Aerospace Engineering Faculty Publications

A wind tunnel test program was conducted at the Langley Full Scale Tunnel (LFST) to evaluate the performance of five passive drag reduction configurations on a modern straight truck at full scale. Configurations were tested in a build-up fashion with results representing a cumulative effect. Tested configurations include a front valance, a front box fairing, a boat-tail, an ideal side-skirt, and a practical side-skirt. Configurations were evaluated over a nominal 9 degree yaw sweep to establish wind averaged drag coefficients using SAE J1252. Genuine replicate yaw sweeps were used in an uncertainty analysis. Results show up to 28% improvement in …

Geriatric Experience Following Cardiac Arrest At Six Interventional Cardiology Centers In The United States 2007-2011, David B. Seder Md, Nainesh Patel Md, John A. Mcpherson Md, Paul W. Mcmullan Md, Karl B. Kern Md, Barbara T. Unger Rn, J Browning, Sudip Nanda Md, Facp, Melkon Hacobian Md, Michael B. Kelley Md, Niklas Nielsen Md, Phd, Michael R. Mooney Md

Department of Medicine

No abstract provided.

Neurological And Cardiovascular Outcomes After Cardiac Arrest At Six Regional Interventional Cardiology Centers In The United States 2007-2011, David B. Seder Md, Nainesh Patel Md, John Mcpherson Md, Paul W. Mcmullan Md, Karl B. Kern Md, Barbara Unger Rn, J Browning, Sudip Nanda Md, Facp, Melkon Hacobian Md, Michael B. Kelley Md, Niklas Nielsen Md, Phd, Michael R. Mooney Md

Department of Medicine

No abstract provided.

Estimation And Forecasting Of Dynamic Conditional Covariance: A Semiparametric Multivariate Model, Xiangdong Long, Liangjun Su, Aman Ullah

Research Collection School Of Economics

We propose a semiparametric conditional covariance (SCC) estimator that combines the first-stage parametric conditional covariance (PCC) estimator with the second-stage nonparametric correction estimator in a multiplicative way. We prove the asymptotic normality of our SCC estimator, propose a nonparametric test for the correct specification of PCC models, and study its asymptotic properties. We evaluate the finite sample performance of our test and SCC estimator and compare the latter with that of PCC estimator, purely nonparametric estimator, and Hafner, Dijk, and Franses’s (2006) estimator in terms of mean squared error and Value-at-Risk losses via simulations and real data analyses.

Model Selection In Validation Sampling Data: An Asymptotic Likelihood-Based Lasso Approach, Chenlei Leng, Denis H. Y. Leung

Research Collection School Of Economics

We propose an asymptotic likelihood-based LASSO approach for model selection in regression analysis when data are subject to validation sampling. The method makes use of an initial estimator of the regression coefficients and their asymptotic covariance matrix to form an asymptotic likelihood. This ``working'' objective function facilitates the formulation of the LASSO and the implementation of a fast algorithm. Our method circumvents the need to use a likelihood set-up that requires full distributional assumptions about the data. We show that the resulting estimator is consistent in model selection and that the method has lower prediction errors than a model that …

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 …

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 …

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 …

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

PPRI Digital Library

No abstract provided.

Reconstructability Analysis Of Epistasis, Martin Zwick

Complex Systems 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 …

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

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 …

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 …

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 …

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.

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 …

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 …

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.

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.