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Evaluating The Long-Term Effects Of Logging Residue Removals In Great Lakes Aspen Forests, Michael I. Premer 2015 Michigan Technological University

Evaluating The Long-Term Effects Of Logging Residue Removals In Great Lakes Aspen Forests, Michael I. Premer

Dissertations, Master's Theses and Master's Reports

Commercial aspen (Populus spp.) forests of the Great Lakes region are primarily managed for timber products such as pulp fiber and panel board, but logging residues (topwood and non-merchantable bolewood) are potentially important for utilization in the bioenergy market. In some regions, pulp and paper mills already utilize residues as fuel in combustion for heat and electricity, and progressive energy policies will likely cause an increase in biomass feedstock demand. The effects of removing residues, which have a comparatively high concentration of macronutrients, is poorly understood when evaluating long-term site productivity, future timber yields, plant diversity, stand dynamics, and …


Comparing Group Means When Nonresponse Rates Differ, Gabriela M. Stegmann 2015 University of North Florida

Comparing Group Means When Nonresponse Rates Differ, Gabriela M. Stegmann

UNF Graduate Theses and Dissertations

Missing data bias results if adjustments are not made accordingly. This thesis addresses this issue by exploring a scenario where data is missing at random depending on a covariate x. Four methods for comparing groups while adjusting for missingness are explored by conducting simulations: independent samples t-test with predicted mean stratification, independent samples t-test with response propensity stratification, independent samples t-test with response propensity weighting, and an analysis of covariance. Results show that independent samples t-test with response propensity weighting and analysis of covariance can appropriately adjust for bias. ANCOVA is the stronger method when …


The Bootstrap Estimation In Time Series, Yun Liu 2015 Michigan Technological University

The Bootstrap Estimation In Time Series, Yun Liu

Dissertations, Master's Theses and Master's Reports

Time series, a special case in dependent data sequence, is widely used in many fields. In time series, linear process models are quite popularly used. General form of linear process indicates the time dependence property of time series, AR(p), MA(q) and ARMA(p;,q) models are all linear process models. In this report, simulations are based on the simplest models of these linear process models, such as AR(1), MA(1) and ARMA(1,1) models. AR(1)-SEASON, which is developed based on AR(1) model by changing the weight of residuals, is also considered in this report. To deal with dependent data sequence, common methods which aim …


A Qualitative Assessment: Adult Perceptions Of Collaboration As Mitigation For Statistics Anxiety, Karl James Kinkead 2015 Walden University

A Qualitative Assessment: Adult Perceptions Of Collaboration As Mitigation For Statistics Anxiety, Karl James Kinkead

Walden Dissertations and Doctoral Studies

Math anxiety, defined as feelings of apprehension and fear of courses involving mathematics, often interferes with student learning in a variety of college-level courses. A related phenomenon, statistics anxiety, affects the performance of many students in statistics courses. Researchers have found evidence that including collaborative problem solving as an instructional methodology is effective at reducing the negative effects of statistics anxiety. The purpose of this qualitative case study was to explore adult perceptions of collaborative problem solving as an instructional methodology focused on improving the learning environment in a business statistics course. Behaviorist, constructivist, and adult learning theories provided the …


The Distribution Of Type 1 Diabetes Onset In The United States By Demographic Factors, Margaret Beckstrand 2015 Walden University

The Distribution Of Type 1 Diabetes Onset In The United States By Demographic Factors, Margaret Beckstrand

Walden Dissertations and Doctoral Studies

Type 1 diabetes (T1D) is a chronic and lifelong condition, often diagnosed in childhood. Patients with T1D are at elevated risks of associated health complications, comorbidities, and mortality. Occurrence, clinical presentation, and complications related to T1D differ by age of onset, ethnicity, and gender. The last reported population-based estimates regarding the burden of T1D in children using the National Health and Nutrition Examination Survey (NHANES) were published in 2008, and these estimates were not well stratified by age of onset, ethnicity, and gender. The purpose of this study was to examine these demographics within the conceptual framework of the hygiene …


A Meta-Analysis Of Association Between One-Carbon Metabolism Gene Polymorphisms And Risk Of Prostate Cancer, Mahmood Tazari 2015 Walden University

A Meta-Analysis Of Association Between One-Carbon Metabolism Gene Polymorphisms And Risk Of Prostate Cancer, Mahmood Tazari

Walden Dissertations and Doctoral Studies

Prostate cancer is the most common cancer among men. The purpose of this quantitative, meta-analysis study was to examine one-carbon metabolism gene polymorphisms in a group of genes to determine their association with prostate cancer risk. The genetic epidemiology theory provided the framework for the study. The data collected were from published articles. From over 2,800 individual studies, 20 articles were retained for results and data abstraction, following the title, abstract screen, and full text screening in the second phase. The data were analyzed by a meta-analysis statistical method, combining the results from selected studies to estimate the overall association. …


A Model For Determining Drivers Of Phenology In Western United States Rangelands, Joseph R. St. Peter 2015 University of Montana - Missoula

A Model For Determining Drivers Of Phenology In Western United States Rangelands, Joseph R. St. Peter

Graduate Student Theses, Dissertations, & Professional Papers

Plant phenology has long been used as an indicator of climate. Recent changes in plant phenology are evidence of the influence of climate change. Modeling plant phenology has become an effective tool to understand the impacts of climate change. Using machine learning techniques I developed a modeling process for accurately predicting phenology across a diverse landscape. This model uses individual site data to set site specific climate thresholds for plant phenology. This model also identifies the limiting factors to vegetation phenology for rangelands in the western United States. NDVI remotely sensed data was used to quantify land surface phenology and …


Day Of The Week Effect In Returns And Volatility Of The S&P 500 Sector Indices, Juan Liu 2015 Missouri University of Science and Technology

Day Of The Week Effect In Returns And Volatility Of The S&P 500 Sector Indices, Juan Liu

Masters Theses

"Previous studies have shown that returns associated with the stock market or foreign exchange's futures show variations across the day of the week. On such study, that employs a modified GARCH model for estimation, shows that returns associated with the S&P 500 stock index is highest on Wednesday and lowest returns on Monday. The same study shows that volatility is highest on Fridays and lowest on Wednesdays. In this study we investigate if this day-of-the-week effect on returns and volatility is present in the different sectors that constitute the S&P 500 index. The data set used provides daily returns from …


Towards Analytical Techniques For Optimizing Knowledge Acquisition, Processing, Propagation, And Use In Cyberinfrastructure, Leonardo Octavio Lerma 2015 University of Texas at El Paso

Towards Analytical Techniques For Optimizing Knowledge Acquisition, Processing, Propagation, And Use In Cyberinfrastructure, Leonardo Octavio Lerma

Open Access Theses & Dissertations

For many decades, there has been a continuous progress in science and engineering applications.

A large part of this progress comes from the new knowledge that researchers acquire, propagate, and use. This new knowledge has revolutionized many aspects of our life, from driving to communications to shopping.

Somewhat surprisingly, there is one area of human activity which is the least impacted by the modern technological progress: the very processes of acquiring, processing, and propagating information. When we decide where to place sensors, which algorithm to use for processing the data – we rely mostly on our own intuition and on …


A Bayes Approach In Step-Stress Accelerated Life Testings, Hao Yang Teng 2015 University of Texas at El Paso

A Bayes Approach In Step-Stress Accelerated Life Testings, Hao Yang Teng

Open Access Theses & Dissertations

A Bayesian analysis for the Weibull proportional hazard (PH) model is presented. A comparison between the Weibull PH model and the Weibull cumulative exposure (CE) model is made graphically and mathematically. The PH model is as flexible as the CE model in fitting step-stress data and the mathematical form of the PH model enables researchers to do Bayesian inferencemuch easier than the CE model. In addition, the PH model has the desirable proportional hazard property. A convex tent prior is used for Bayesian analysis. Markov chain Monte Carlo methods are used for posterior inferences. In this study, we adopt two …


Pre-Tuned Ridge Regression And Its Extension To Generalized Linear Models, Yaa Tawiah Wonkye 2015 University of Texas at El Paso

Pre-Tuned Ridge Regression And Its Extension To Generalized Linear Models, Yaa Tawiah Wonkye

Open Access Theses & Dissertations

Ridge regression is regularization or shrinkage method and a common approach in dealing with multicollinearity in conventional regression analysis. Ridge regression is widely used by statistical analyst since it is one of the best compared to other regularization methods. Also, the introduction of high dimension and ultra-high dimensional data has become an issue of concern and ridge regression is one way of dealing with such data. One of the key issues associated with ridge regression is the determination of the tuning or ridge parameter. The common practice is to fit ridge regression for a different number of values of tuning …


Key Factors Driving Personnel Downsizing In Multinational Military Organizations, Ilksen Gorkem, Resit Unal, Pilar Pazos 2015 Old Dominion University

Key Factors Driving Personnel Downsizing In Multinational Military Organizations, Ilksen Gorkem, Resit Unal, Pilar Pazos

Engineering Management & Systems Engineering Faculty Publications

Although downsizing has long been a topic of research in traditional organizations, there are very few studies of this phenomenon in military contexts. As a result, we have little understanding of the key factors that drive personnel downsizing in military setting. This study contributes to our understanding of key factors that drive personnel downsizing in military organizations and whether those factors may differ across NATO nations’ cultural clusters. The theoretical framework for this study was built from studies in non-military contexts and adapted to fit the military environment.

This research relies on historical data from one of the largest multinational …


Statistical Engineering: A Causal-Stochastic Modeling Research Update, Teddy Steven Cotter 2015 Old Dominion University

Statistical Engineering: A Causal-Stochastic Modeling Research Update, Teddy Steven Cotter

Engineering Management & Systems Engineering Faculty Publications

In the ASEM-IAC 2012, Cotter (2012) summarized prior works that led to the proposal for statistical engineering, identified the gaps in knowledge that statistical engineering needs to address, explored additional gaps in knowledge not addressed in the prior works, set forth a working definition of and body of knowledge for statistical engineering, and set forth proposals of potential systems contributions the Engineering Management profession could make toward the development of statistical engineering. In 2014, the ASQ Statistics Division, DOT&E, NASA, and IDA co-sponsored a Statistical Engineering Agreement to jointly research development of the discipline of statistical engineering. The statistics community …


Proof-Of-Concept Of Environmental Dna Tools For Atlantic Sturgeon Management, Jameson Hinkle 2015 Virginia Commonwealth University

Proof-Of-Concept Of Environmental Dna Tools For Atlantic Sturgeon Management, Jameson Hinkle

Theses and Dissertations

Abstract

The Atlantic Sturgeon (Acipenser oxyrinchus oxyrinchus, Mitchell) is an anadromous species that spawns in tidal freshwater rivers from Canada to Florida. Overfishing, river sedimentation and alteration of the river bottom have decreased Atlantic Sturgeon populations, and NOAA lists the species as endangered. Ecologists sometimes find it difficult to locate individuals of a species that is rare, endangered or invasive. The need for methods less invasive that can create more resolution of cryptic species presence is necessary. Environmental DNA (eDNA) is a non-invasive means of detecting rare, endangered, or invasive species by isolating nuclear or mitochondrial DNA (mtDNA) from the …


Characteristics Associated With Willingness To Participate In A Randomized Controlled Behavioral Clinical Trial Using Home-Based Personal Computers And A Webcam, Hiroko H. Dodge, Yuriko Katsumata, Jian Zhu, Nora Mattek, Molly Bowman, Mattie Gregor, Katherine Wild, Jeffrey A Kaye 2014 Oregon Health & Science University

Characteristics Associated With Willingness To Participate In A Randomized Controlled Behavioral Clinical Trial Using Home-Based Personal Computers And A Webcam, Hiroko H. Dodge, Yuriko Katsumata, Jian Zhu, Nora Mattek, Molly Bowman, Mattie Gregor, Katherine Wild, Jeffrey A Kaye

Biostatistics Faculty Publications

BACKGROUND: Trials aimed at preventing cognitive decline through cognitive stimulation among those with normal cognition or mild cognitive impairment are of significant importance in delaying the onset of dementia and reducing dementia prevalence. One challenge in these prevention trials is sample recruitment bias. Those willing to volunteer for these trials could be socially active, in relatively good health, and have high educational levels and cognitive function. These participants' characteristics could reduce the generalizability of study results and, more importantly, mask trial effects. We developed a randomized controlled trial to examine whether conversation-based cognitive stimulation delivered through personal computers, a webcam …


Statistical Inference For The Mean Outcome Under A Possibly Non-Unique Optimal Treatment Strategy, Alexander R. Luedtke, Mark J. van der Laan 2014 University of California, Berkeley

Statistical Inference For The Mean Outcome Under A Possibly Non-Unique Optimal Treatment Strategy, Alexander R. Luedtke, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

We consider challenges that arise in the estimation of the value of an optimal individualized treatment strategy defined as the treatment rule that maximizes the population mean outcome, where the candidate treatment rules are restricted to depend on baseline covariates. We prove a necessary and sufficient condition for the pathwise differentiability of the optimal value, a key condition needed to develop a regular asymptotically linear (RAL) estimator of this parameter. The stated condition is slightly more general than the previous condition implied in the literature. We then describe an approach to obtain root-n rate confidence intervals for the optimal value …


Statistical Partition Problem For Exponential Populations And Statistical Surveillance Of Cancers In Louisiana, Jin Gu 2014 LSU New Orleans

Statistical Partition Problem For Exponential Populations And Statistical Surveillance Of Cancers In Louisiana, Jin Gu

LSU New Orleans Theses and Dissertations

In this dissertation, we consider the problem of partitioning a set of

k population with respect

to a control population. For this problem some multistage methodologies are proposed and their

properties are derived. Using the Monte Carlo simulation techniques, the small and moderate

sample size performance of the proposed procedure are studied.

We have also considered at statistical surveillance of various cancers in Louisiana.


Mediation Analysis Of Gestational Age, Congenital Heart Defects, And Infant Birth-Weight, Adane F. Wogu, Christopher A. Loffredo, Ionut Bebu, George Luta 2014 George Washington University

Mediation Analysis Of Gestational Age, Congenital Heart Defects, And Infant Birth-Weight, Adane F. Wogu, Christopher A. Loffredo, Ionut Bebu, George Luta

GW Biostatistics Center

Background

In this study we assessed the mediation role of the gestational age on the effect of the infant’s congenital heart defects (CHD) on birth-weight.

Methods

We used secondary data from the Baltimore-Washington Infant Study (1981–1989). Mediation analysis was employed to investigate whether gestational age acted as a mediator of the association between CHD and reduced birth-weight. We estimated the mediated effect, the mediation proportion, and their corresponding 95% confidence intervals (CI) using several methods.

Results

There were 3362 CHD cases and 3564 controls in the dataset with mean birth-weight of 3071 (SD = 729) and 3353 (SD = 603) …


A More Efficient Nonparametric Test Of Symmetry Based On Overlapping Coefficient, Hani M. Samawi, Robert L. Vogel 2014 Georgia Southern University

A More Efficient Nonparametric Test Of Symmetry Based On Overlapping Coefficient, Hani M. Samawi, Robert L. Vogel

Biostatistics: Faculty Publications

In this paper we provide a more efficient nonparametric test of symmetry based on the empirical overlap coefficient using kernel density estimation applied to an extreme order statistics, namely extreme ranked set sampling. Our simulation investigation reveals that our proposed test of symmetry is at least as powerful as currently available tests of symmetry. Intensive simulation is conducted to examine the power of the proposed test. An illustration is provided using cardiac output and body weight of neonates in a neonatal intensive care unit.


Methods For Identifying Regions Of Brain Activation Using Fmri Meta-Data, Meredith A. Ray 2014 University of South Carolina - Columbia

Methods For Identifying Regions Of Brain Activation Using Fmri Meta-Data, Meredith A. Ray

Theses and Dissertations

Functional neuroimaging is a relatively young discipline within the neurosciences that has led to significant advances in our understanding of the human brain and progress in neuroscientific research related to public health. Accurately identifying activated regions in the brain showing a strong association with an outcome of interest is crucial in terms of disease prediction and prevention. Functional magnetic resonance imaging (fMRI) is the most widely used method for this type of study as it has the ability to measure and identify the location of changes in tissue perfusion, blood oxygenation, and blood volume. In practice, the three-dimensional brain locations …


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