Biometry Commons^™

Using Camera-Based Unmarked Spatial Capture-Recapture Modeling To Estimate Reintroduced Elk (Cervus Canadensis) Population Parameters And Distribution In Southeastern Kentucky, Claire Marie Muia

Theses and Dissertations--Forestry and Natural Resources

Estimation of population parameters is important for wildlife management decisions. Elk reintroduced to southeastern Kentucky experienced early irruptive population growth and are currently monitored using a statewide harvest-based statistical population reconstruction model (SPR) across the Kentucky Elk Restoration Zone (KERZ). Because the SPR model is spatially coarse and difficult to scale to the smaller management units comprising the KERZ, we conducted a spatially explicit capture-recapture study using a clustered camera-trapping array deployed for 10 weeks from June–August 2024 to estimate elk population parameters within Management Unit 4. Due to a lack of resights of GPS-marked elk, population parameters were estimated …

Disparities In The Prevalence Of Hospitalizations And In-Hospital Mortality Due To Acute Myocardial Infarction Among Patients With Non-Alcoholic Fatty Liver Disease: A Nationwide Retrospective Study, Umar Hayat, Faisal Kamal, Muhammad Kamal, Wasique Mirza, Tariq Ahmad, Manesh Gangwani, Dushyant Dahiya, Hassam Ali, Shiva Naidoo, Sara Humayun, Hayrettin Okut, Muhammad Aziz

Division of Gastroenterology and Hepatology Faculty Papers

Background: Non-alcoholic liver disease (NAFLD) may be associated with cardiovascular diseases; however, only a few studies have analyzed this relationship. We aimed to assess the epidemiologic data and the association between NAFLD and acute myocardial infarction (AMI) in the United States. Methods: The National Inpatient Sample (NIS) database 2016-2019 was queried using ICD10-CM diagnostic codes to identify hospitalizations of AMI + NAFLD. Essential demographic variables were analyzed to determine the disparities in the prevalence of AMI hospitalizations and deaths among NAFLD patients. Univariate and multivariate logistic regression models determined the association between NAFLD and AMI hospitalizations and death. …

Utilizing New Technologies To Measure Therapy Effectiveness For Mental And Physical Health, Jonathan Ossie

Dissertations

Mental health is quickly becoming a major policy concern, with recent data reporting increasing and disproportionately worse mental health outcomes, including anxiety, depression, increased substance abuse, and elevated suicidal ideation. One specific population that is especially high risk for these issues is the military community because military conflict, deployment stressors, and combat exposure contribute to the risk of mental health problems.

Although several pharmacological approaches have been employed to combat this epidemic, their efficacy is mixed at best, which has led to novel nonpharmacological approaches. One such approach is Operation Surf, a nonprofit that provides nature-based programs advocating the restorative …

The Classification Of Basket Neural Cells In The Mammalian Neocortex, Sreya Pudi

Senior Theses

Basket neuronal cells of the mammalian neocortex have been classically categorized into two or more groups. Originally, it was thought that the large and small types are the naturally occurring groups that emerge from reasons that relate to neurobiological function and anatomical position. Later, a study based on anatomical and physiological features of these neurons introduced a third type, the net basket cell which is intermediate in size as compared to the large and small types. In this study, multivariate analysis was used to test the hypothesis that the large and small types are morphologically distinct groups. The results of …

Splitting Up A Complex Mess: The Effectiveness Of Statistical Analysis On Delimiting Species Complexes, Sara N. Schoen

Masters Theses, 2020-current

Recent studies have highlighted a need for more refined tools in species delimitation. This is especially true when considering diversity within species complexes, where members are morphologically similar and traditional tools have thus far failed to provide clearly defined boundaries between species. This project seeks to refine our traditional tools of species delimitation and apply new tools to the challenges created by species complexes. The focus organisms of this study are the anurans of the Limnonectes kuhlii complex. This species complex comprises more than 25 species of stream frogs from Southeast Asia. Traditionally, morphometrics (particularly linear measures) has been the …

Biological And Practical Implications Of Genome-Wide Association Study Of Schizophrenia Using Bayesian Variable Selection, Benazir Rowe, Xiangning Chen, Zuoheng Wang, Jingchun Chen, Amei Amei

School of Medicine Faculty Research

Genome-wide association studies (GWAS) have identified over 100 loci associated with schizophrenia. Most of these studies test genetic variants for association one at a time. In this study, we performed GWAS of the molecular genetics of schizophrenia (MGS) dataset with 5334 subjects using multivariate Bayesian variable selection (BVS) method Posterior Inference via Model Averaging and Subset Selection (piMASS) and compared our results with the previous univariate analysis of the MGS dataset. We showed that piMASS can improve the power of detecting schizophrenia-associated SNPs, potentially leading to new discoveries from existing data without increasing the sample size. We tested SNPs in …

Unified Methods For Feature Selection In Large-Scale Genomic Studies With Censored Survival Outcomes, Lauren Spirko-Burns, Karthik Devarajan

COBRA Preprint Series

One of the major goals in large-scale genomic studies is to identify genes with a prognostic impact on time-to-event outcomes which provide insight into the disease's process. With rapid developments in high-throughput genomic technologies in the past two decades, the scientific community is able to monitor the expression levels of tens of thousands of genes and proteins resulting in enormous data sets where the number of genomic features is far greater than the number of subjects. Methods based on univariate Cox regression are often used to select genomic features related to survival outcome; however, the Cox model assumes proportional hazards …

Reassessment Of The Red Drum Stock In Mississippi Coastal Waters: The Role Of Ages 3-5 Year-Class Fish, Emily Satterfield

Master's Theses

Red Drum, Sciaenops ocellatus, are highly sought after by sport fishermen in Mississippi coastal waters. In 2016, Mississippi anglers made over 180,000 fishing trips targeting Red Drum, making it the second most targeted marine species. The current Fishery Management Plan of the Gulf of Mexico Fishery Management Council, prohibits harvest of Red Drum in federal waters. Monitoring of the stock in Mississippi state waters occurs at sites that are almost exclusively estuarine, using gear types selective for juvenile fish. Additional samples come from the for-hire-industry that typically targets larger Red Drum. This project’s goal was to target age three …

A Statistical Method For The Conservative Adjustment Of False Discovery Rate (Q-Value), Yinglei Lai

Epidemiology Faculty Publications

Background

q-value is a widely used statistical method for estimating false discovery rate (FDR), which is a conventional significance measure in the analysis of genome-wide expression data. q-value is a random variable and it may underestimate FDR in practice. An underestimated FDR can lead to unexpected false discoveries in the follow-up validation experiments. This issue has not been well addressed in literature, especially in the situation when the permutation procedure is necessary for p-value calculation.

Results

We proposed a statistical method for the conservative adjustment of q-value. In practice, it is usually necessary to calculate p …

Juvenile Remains: Predicting Body Mass And Stature In Modern American Populations, Erin F E Pinkston

Cal Poly Humboldt theses and projects

There are increasing numbers of unidentified persons in the U.S. and abroad. To generate positive identifications, forensic anthropologists and others working in the medicolegal field employ a variety of methods to produce biological profiles to match to case files and missing persons databases. Body mass, and stature are two important components of a biological profile, and both can be estimated using regression formulae derived from skeletal metrics. In cases of unidentified juvenile remains, these are particularly important metrics, as it is difficult or impossible to determine sex in prepubescent remains, and the quality of ancestry estimation is currently under debate …

Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang

COBRA Preprint Series

Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …

Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret

UW Biostatistics Working Paper Series

We have frequently implemented crossover studies to evaluate new therapeutic interventions for genital herpes simplex virus infection. The outcome measured to assess the efficacy of interventions on herpes disease severity is the viral shedding rate, defined as the frequency of detection of HSV on the genital skin and mucosa. We performed a simulation study to ascertain whether our standard model, which we have used previously, was appropriately considering all the necessary features of the shedding data to provide correct inference. We simulated shedding data under our standard, validated assumptions and assessed the ability of 5 different models to reproduce the …

Meta-Analysis Of Gene Expression Studies, Umaporn Siangphoe

Theses and Dissertations

Combining effect sizes from individual studies using random-effects models are commonly applied in high-dimensional gene expression data. However, unknown study heterogeneity can arise from inconsistency of sample qualities and experimental conditions. High heterogeneity of effect sizes can reduce statistical power of the models. We proposed two new methods for random effects estimation and measurements for model variation and strength of the study heterogeneity. We then developed a statistical technique to test for significance of random effects and identify heterogeneous genes. We also proposed another meta-analytic approach that incorporates informative weights in the random effects meta-analysis models. We compared the proposed …

Mixtures Of Self-Modelling Regressions, Rhonda D. Szczesniak, Kert Viele, Robin L. Cooper

Statistics Faculty Publications

A shape invariant model for functions f₁,...,f_n specifies that each individual function f_i can be related to a common shape function g through the relation f_i(x) = a_ig(c_ix + d_i) + b_i. We consider a flexible mixture model that allows multiple shape functions g₁,...,g_K, where each f_i is a shape invariant transformation of one of those g_K. We derive an MCMC algorithm for fitting the model using Bayesian Adaptive Regression Splines (BARS), propose …

Missing At Random And Ignorability For Inferences About Subsets Of Parameters With Missing Data, Roderick J. Little, Sahar Zanganeh

The University of Michigan Department of Biostatistics Working Paper Series

For likelihood-based inferences from data with missing values, Rubin (1976) showed that the missing data mechanism can be ignored when (a) the missing data are missing at random (MAR), in the sense that missingness does not depend on the missing values after conditioning on the observed data, and (b) the parameters of the data model and the missing-data mechanism are distinct; that is, there are no a priori ties, via parameter space restrictions or prior distributions, between the parameters of the data model and the parameters of the model for the mechanism. Rubin described (a) and (b) as the "weakest …

A Bayesian Approach To Dose-Response Assessment And Drug-Drug Interaction Analysis: Application To In Vitro Studies, Violeta G. Hennessey

Dissertations and Theses (Open Access)

The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis.

The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method …