Statistical Models Commons^™

Utilizing Markov Chains To Estimate Allele Progression Through Generations, Ronit Gandhi

Honors Theses

All populations display patterns in allele frequencies over time. Some alleles cease to exist, while some grow to become the norm. These frequencies can shift or stay constant based on the conditions the population lives in. If in Hardy-Weinberg equilibrium, the allele frequencies stay constant. Most populations, however, have bias from environmental factors, sexual preferences, other organisms, etc. We propose a stochastic Markov chain model to study allele progression across generations. In such a model, the allele frequencies in the next generation depend only on the frequencies in the current one.

We use this model to track a recessive allele …

Comparing Machine Learning Techniques With State-Of-The-Art Parametric Prediction Models For Predicting Soybean Traits, Susweta Ray

Department of Statistics: Dissertations, Theses, and Student Work

Soybean is a significant source of protein and oil, and also widely used as animal feed. Thus, developing lines that are superior in terms of yield, protein and oil content is important to feed the ever-growing population. As opposed to the high-cost phenotyping, genotyping is both cost and time efficient for breeders while evaluating new lines in different environments (location-year combinations) can be costly. Several Genomic prediction (GP) methods have been developed to use the marker and environment data effectively to predict the yield or other relevant phenotypic traits of crops. Our study compares a conventional GP method (GBLUP), a …

Interval Estimation Of Proportion Of Second-Level Variance In Multi-Level Modeling, Steven Svoboda

The Nebraska Educator: A Student-Led Journal

Physical, behavioral and psychological research questions often relate to hierarchical data systems. Examples of hierarchical data systems include repeated measures of students nested within classrooms, nested within schools and employees nested within supervisors, nested within organizations. Applied researchers studying hierarchical data structures should have an estimate of the intraclass correlation coefficient (ICC) for every nested level in their analyses because ignoring even relatively small amounts of interdependence is known to inflate Type I error rate in single-level models. Traditionally, researchers rely upon the ICC as a point estimate of the amount of interdependency in their data. Recent methods utilizing an …

Statistical Methodology To Establish A Benchmark For Evaluating Antimicrobial Resistance Genes Through Real Time Pcr Assay, Enakshy Dutta

Department of Statistics: Dissertations, Theses, and Student Work

Novel diagnostic tests are usually compared with gold standard tests for evaluating diagnostic accuracy. For assessing antimicrobial resistance (AMR) to bovine respiratory disease (BRD) pathogens, phenotypic broth microdilution method is used as gold standard (GS). The objective of the thesis is to evaluate the optimal cycle threshold (Ct) generated by real-time polymerase chain reaction (rtPCR) to genes that confer resistance that will translate to the phenotypic classification of AMR. Data from two different methodologies are assessed to identify Ct that will discriminate between resistance (R) and susceptibility (S). First, the receiver operating characteristic (ROC) curve was used to determine the …

Evaluation Of Modern Missing Data Handling Methods For Coefficient Alpha, Katerina Matysova

College of Education and Human Sciences: Dissertations, Theses, and Student Research

When assessing a certain characteristic or trait using a multiple item measure, quality of that measure can be assessed by examining the reliability. To avoid multiple time points, reliability can be represented by internal consistency, which is most commonly calculated using Cronbach’s coefficient alpha. Almost every time human participants are involved in research, there is missing data involved. Missing data means that even though complete data were expected to be collected, some data are missing. Missing data can follow different patterns as well as be the result of different mechanisms. One traditional way to deal with missing data is listwise …

Statistical Investigation Of Road And Railway Hazardous Materials Transportation Safety, Amirfarrokh Iranitalab

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Transportation of hazardous materials (hazmat) in the United States (U.S.) constituted 22.8% of the total tonnage transported in 2012 with an estimated value of more than 2.3 billion dollars. As such, hazmat transportation is a significant economic activity in the U.S. However, hazmat transportation exposes people and environment to the infrequent but potentially severe consequences of incidents resulting in hazmat release. Trucks and trains carried 63.7% of the hazmat in the U.S. in 2012 and are the major foci of this dissertation. The main research objectives were 1) identification and quantification of the effects of different factors on occurrence and …

Essentials Of Structural Equation Modeling, Mustafa Emre Civelek

Zea E-Books Collection

Structural Equation Modeling is a statistical method increasingly used in scientific studies in the fields of Social Sciences. It is currently a preferred analysis method, especially in doctoral dissertations and academic researches. However, since many universities do not include this method in the curriculum of undergraduate and graduate courses, students and scholars try to solve the problems they encounter by using various books and internet resources.

This book aims to guide the researcher who wants to use this method in a way that is free from math expressions. It teaches the steps of a research program using structured equality modeling …

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 …

A Characterization Of A Value Added Model And A New Multi-Stage Model For Estimating Teacher Effects Within Small School Systems, Julie M. Garai

Department of Statistics: Dissertations, Theses, and Student Work

At both the national and state level there is increasing pressure to develop metrics to determine if school systems are meeting educational objectives. All states mandate some form of assessment by standardized tests. One method currently used to model student test scores is Value Added Modeling (VAM), which models student scores as a product of classroom and school environments. One VAM approach is the Tennessee Value Added Assessment System (TVAAS) which models student gains from year to year. Teacher effects are included in this layered model, which estimates the teacher’s added value to a student score through best linear unbiased …

Testing The Independence Hypothesis Of Accepted Mutations For Pairs Of Adjacent Amino Acids In Protein Sequences, Jyotsna Ramanan, Peter Revesz

School of Computing: Faculty Publications

Evolutionary studies usually assume that the genetic mutations are independent of each other. However, that does not imply that the observed mutations are independent of each other because it is possible that when a nucleotide is mutated, then it may be biologically beneficial if an adjacent nucleotide mutates too. With a number of decoded genes currently available in various genome libraries and online databases, it is now possible to have a large-scale computer-based study to test whether the independence assumption holds for pairs of adjacent amino acids. Hence the independence question also arises for pairs of adjacent amino acids within …

Beta-Binomial Kriging: A New Approach To Modeling Spatially Correlated Proportions, Aimee Schwab

Department of Statistics: Dissertations, Theses, and Student Work

Spatially correlated count data sets appear often in applied data analysis problems, but there is little consensus in the literature about how best to analyze the data. The two prevailing approaches provide accurate parameter estimates and predictions, at the cost of model interpretability and simplicity. This dissertation will present a new approach to modeling spatially correlated binomial observations: beta-binomial kriging. The model proposed here is a modified form of spatial kriging which assumes the data are generated from a correlated beta-binomial distribution. Given this assumption, the spatial parameters and predicted values can be estimated using simple matrix algebra. Beta-binomial kriging …

Best Practice Recommendations For Data Screening, Justin A. Desimone, Peter D. Harms, Alice J. Desimone

Department of Management: Faculty Publications

Survey respondents differ in their levels of attention and effort when responding to items. There are a number of methods researchers may use to identify respondents who fail to exert sufficient effort in order to increase the rigor of analysis and enhance the trustworthiness of study results. Screening techniques are organized into three general categories, which differ in impact on survey design and potential respondent awareness. Assumptions and considerations regarding appropriate use of screening techniques are discussed along with descriptions of each technique. The utility of each screening technique is a function of survey design and administration. Each technique has …

Spin Glass Reflection Of The Decoding Transition For Quantum Error Correcting Codes, Alexey Kovalev, Leonid P. Pryadko

Department of Physics and Astronomy: Faculty Publications

We study the decoding transition for quantum error correcting codes with the help of a mapping to random-bond Wegner spin models. Families of quantum low density parity-check (LDPC) codes with a finite decoding threshold lead to both known models (e.g., random bond Ising and random plaquette Z₂ gauge models) as well as unexplored earlier generally non-local disordered spin models with non-trivial phase diagrams. The decoding transition corresponds to a transition from the ordered phase by proliferation of "post-topological" extended defects which generalize the notion of domain walls to non-local spin models. In recently discovered quantum LDPC code families with …

Modeling The Dynamic Processes Of Challenge And Recovery (Stress And Strain) Over Time, Fan Yang

Department of Statistics: Dissertations, Theses, and Student Work

A dynamic process with challenge and recovery is an important branch in the family of stochastic processes. The dependent data of such processes are often observed over time, and hence, are time dependent. The purpose of this dissertation is to develop methods to characterize a dynamic process with challenge and recovery under different dimensionalities and error assumptions. In this dissertation, a univariate dynamic process under Gaussian assumption is discussed first and a bi-logistic model is developed by three different methods: compartment, additive, and Bayesian. Then the discussion is extended to a bivariate hysteresis system with challenge and recovery. Three methods: …

Retrieval Of Sub-Pixel-Based Fire Intensity And Its Application For Characterizing Smoke Injection Heights And Fire Weather In North America, David Peterson

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

For over two decades, satellite sensors have provided the locations of global fire activity with ever-increasing accuracy. However, the ability to measure fire intensity, know as fire radiative power (FRP), and its potential relationships to meteorology and smoke plume injection heights, are currently limited by the pixel resolution. This dissertation describes the development of a new, sub-pixel-based FRP calculation (FRP_f) for fire pixels detected by the MODerate Resolution Imaging Spectroradiometer (MODIS) fire detection algorithm (Collection 5), which is subsequently applied to several large wildfire events in North America. The methodology inherits an earlier bi-spectral algorithm for retrieving sub-pixel …

Significant Themes In 19th-Century Literature, Matthew L. Jockers, David Mimno

Department of English: Faculty Publications

External factors such as author gender, author nationality, and date of publication affect both the choice of literary themes in novels and the expression of those themes, but the extent of this association is difficult to quantify. In this work, we apply statistical methods to identify and extract hundreds of "topics" from a corpus of 3,346 works of 19th-century British, Irish, and American fiction. We use these topics as a measurable, data-driven proxy for literary themes. External factors may predict fluctuations in the use of themes and the individual word choices within themes. We use topics to measure the evidence …

Water Quality Models For Stormwater Runoff In Two Lincoln, Nebraska Urban Watersheds, Jake Fisher

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Water quality monitoring was conducted in two urban watersheds (Colonial Hills and Taylor Park) located in southeast Lincoln, NE over a three year period spanning from October 2008 through September 2011. In-line probes continuously measured for turbidity, conductivity, dissolved oxygen, and water temperature while other water quality constituents were analyzed for discrete water samples collected using grab and automatic sampling techniques. The water quality data was used to calculate event mean concentrations (EMCs) for sixteen storm events sampled over the duration of the project period. Three types of stormwater quality multiple linear regression models were developed for the estimation of …

Habitat Use And Abundance Patterns Of Sandhill Cranes In The Central Platte River Valley, Nebraska, 2003–2010, Todd Joseph Buckley

School of Natural Resources: Dissertations, Theses, and Student Research

The Central Platte River Valley (CPRV) in Nebraska is an important spring stopover area for the midcontinent population of sandhill cranes. Alterations to crop rotation and loss habitat in the CPRV pose a risk to the population. Personnel drove designated routes in the CPRV from 2003–2010 to record the presence of cranes in agricultural fields and estimate abundance. I developed and evaluated models to predict habitat use and flock sizes. Alfalfa was predicted to receive the highest use followed by corn, soybeans, winter wheat, grassland, and shrubland. Use of all habitats and flock size increased as field area increased. Flock …

Estimating Teacher Effects Using Value-Added Models, Jennifer L. Green

Department of Statistics: Dissertations, Theses, and Student Work

Value-added modeling is an alternative approach to test-based accountability systems based on the proportions of students scoring at or above pre-determined proficiency levels. Value-added modeling techniques provide opportunities to estimate an individual teacher’s effect on student learning, while allowing for the possibility to control for the effect of non-educational factors beyond a school system’s control, such as socioeconomic status. However, numerous considerations exist when using value-added models to estimate teacher effects and defining what the teacher effects really describe. Chapter 2 provides an introduction to value-added methodology by describing several value-added models available for estimating teacher effects and their respective …

Sequence Comparison And Stochastic Model Based On Multi-Order Markov Models, Xiang Fang

Department of Statistics: Dissertations, Theses, and Student Work

This dissertation presents two statistical methodologies developed on multi-order Markov models. First, we introduce an alignment-free sequence comparison method, which represents a sequence using a multi-order transition matrix (MTM). The MTM contains information of multi-order dependencies and provides a comprehensive representation of the heterogeneous composition within a sequence. Based on the MTM, a distance measure is developed for pair-wise comparison of sequences. The new method is compared with the traditional maximum likelihood (ML) method, the complete composition vector (CCV) method and the improved version of the complete composition vector (ICCV) method using simulated sequences. We further illustrate the application of …

The Em Algorithm For Group Testing Regression Models Under Matrix Pooling, Christopher R. Bilder, Boan Zhang

Department of Statistics: Faculty Publications

No abstract provided.

A Monte Carlo Power Analysis Of Traditional Repeated Measures And Hierarchical Multivariate Linear Models In Longitudinal Data Analysis, Hua Fang, Gordon P. Brooks, Maria L. Rizzo, Kimberly A. Espy, Robert S. Barcikowski

Developmental Cognitive Neuroscience Laboratory: Faculty and Staff Publications

The power properties of traditional repeated measures and hierarchical linear models have not been clearly determined in the balanced design for longitudinal studies in the current literature. A Monte Carlo power analysis of traditional repeated measures and hierarchical multivariate linear models are presented under three variance-covariance structures. Results suggest that traditional repeated measures have higher power than hierarchical linear models for main effects, but lower power for interaction effects. Significant power differences are also exhibited when power is compared across different covariance structures. Results also supplement more comprehensive empirical indexes for estimating model precision via bootstrap estimates and the approximate …

The Time Invariance Principle, Ecological (Non)Chaos, And A Fundamental Pitfall Of Discrete Modeling, Bo Deng

Department of Mathematics: Faculty Publications

This paper is to show that most discrete models used for population dynamics in ecology are inherently pathological that their predications cannot be independently verified by experiments because they violate a fundamental principle of physics. The result is used to tackle an on-going controversy regarding ecological chaos. Another implication of the result is that all continuous dynamical systems must be modeled by differential equations. As a result it suggests that researches based on discrete modeling must be closely scrutinized and the teaching of calculus and differential equations must be emphasized for students of biology.