Statistics and Probability Commons^™

Multivariate Probit Models For Interval-Censored Failure Time Data, Yifan Zhang

Theses and Dissertations

Survival analysis is an important branch of statistics that analyzes the time to event data. The events of interest can be death, disease occurrence, the failure of a machine part, etc.. One important feature of this type of data is censoring: information on time to event is not observed exactly due to loss to follow-up or non-occurrence of interested event before the trial ends. Censored data are commonly observed in clinical trials and epidemiological studies, since monitoring a person’s health over time after treatment is often required in medical or health studies. In this dissertation we focus on studying multivariate …

Statin Prescription For Patients With Atherosclerotic Cardiovascular Disease From National Survey Data, Kristina Vatcheva, Vicente Aparicio, Ayesha Araya, Eduardo Gonzalez, Susan T. Laing

School of Mathematical & Statistical Sciences Faculty Publications

Despite strong evidence for the use of statins for patients with atherosclerotic cardiovascular disease (ASCVD), statin prescription is still suboptimal. We aimed to determine the rates and factors that influence statin prescription using national survey data. This is a cross-sectional retrospective study on 8,468 patients with clinical ASCVD who were drawn from the National Ambulatory Medical Care Survey and the National Hospital Ambulatory Medical Care Survey from years 2011 to 2015. Survey-weighted analysis was conducted to estimate weighted prevalence and odds ratios for statin prescription. There was a significant increase in statin prescription from the years 2011 to 2015. Nevertheless, …

Copula-Based Zero-Inflated Count Time Series Models, Mohammed Sulaiman Alqawba

Mathematics & Statistics Theses & Dissertations

Count time series data are observed in several applied disciplines such as in environmental science, biostatistics, economics, public health, and finance. In some cases, a specific count, say zero, may occur more often than usual. Additionally, serial dependence might be found among these counts if they are recorded over time. Overlooking the frequent occurrence of zeros and the serial dependence could lead to false inference. In this dissertation, we propose two classes of copula-based time series models for zero-inflated counts with the presence of covariates. Zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), and zero-inflated Conway-Maxwell-Poisson (ZICMP) distributed marginals of the …

The Odd Nadarajah-Haghighi Family Of Distributions: Properties And Applications, Abraão D.C. Nascimento, Kássio F. Silva, Gauss M. Cordeiro, Morad Alizadeh, Haitham M. Yousof, Gholamhossein G. Hamedani

Mathematical and Statistical Science Faculty Research and Publications

We study some mathematical properties of a new generator of continuous distributions called the Odd Nadarajah-Haghighi (ONH) family. In particular, three special models in this family are investigated, namely the ONH gamma, beta and Weibull distributions. The family density function is given as a linear combination of exponentiated densities. Further, we propose a bivariate extension and various characterization results of the new family. We determine the maximum likelihood estimates of ONH parameters for complete and censored data. We provide a simulation study to verify the precision of these estimates. We illustrate the performance of the new family by means of …

Interpreting Patient Reported Outcomes In Orthopaedic Surgery: A Systematic Review, Shgufta Docter, Zina Fathalla, Michael Lukacs, Michaela Khan, Morgan Jennings, Shu-Hsuan Liu, Dong Zi, Dianne Bryant

Western Research Forum

Background: Reporting methods of patient reported outcome measures (PROMs) vary in orthopaedic surgery literature. While most studies report statistical significance, the interpretation of results would be improved if authors reported confidence intervals (CIs), the minimally clinically important difference (MCID), and number needed to treat (NNT).

Objective: To assess the quality and interpretability of reporting the results of PROMs. To evaluate reporting, we will assess the proportion of studies that reported (1) 95% CIs, (2) MCID, and (3) NNT. To evaluate interpretation, we will assess the proportion of studies that discussed results using the MCID or the effect sizes and how …

Generalized Interventional Approach For Causal Mediation Analysis With Causally Ordered Multiple Mediators, Sheng-Hsuan Lin

Harvard University Biostatistics Working Paper Series

Causal mediation analysis has demonstrated the advantage of mechanism investigation. In conditions with causally ordered mediators, path-specific effects (PSEs) are introduced for specifying the effect subject to a certain combination of mediators. However, most PSEs are unidentifiable. To address this, an alternative approach termed interventional analogue of PSE (iPSE), is widely applied to effect decomposition. Previous studies that have considered multiple mediators have mainly focused on two-mediator cases due to the complexity of the mediation formula. This study proposes a generalized interventional approach for the settings, with the arbitrary number of ordered multiple mediators to study the causal parameter identification …

Where On Ice? Algorithmically Deconstructing Nhl Shot Locations As A Method For Player Classification, Devan Becker, Douglas G. Woolford, Charmaine B. Dean

Western Research Forum

Where do hockey players shoot from? How does this vary from player to player? We present the results of a study that uses data-driven statistical methods to investigate these questions. The locations of shots by National Hockey League (NHL) players from 2011 to 2017 are analyzed using a combination of an image recognition algorithm and spatial statistical methodology. An unsupervised classifier is applied to output from a spatial point process model in order to determine which shot locations best characterize a given player. We define the number of regions a priori, but the image recognition algorithm chooses the shape …

Incidence And Cost Of Acute Kidney Injury In Hospitalized Patients With Infective Endocarditis, Victor M. Ortiz-Soriano, Katherine Donaldson, Gaixin Du, Ye Li, Joshua Lambert, Dan Cleland, Alice C. Thornton, Laura C. Fanucchi, Moises A. Huaman, Javier A. Neyra

Internal Medicine Faculty Publications

Acute kidney injury (AKI) is a frequent complication of hospitalized patients with infective endocarditis (IE). Further, AKI in the setting of IE is associated with high morbidity and mortality. We aimed to examine the incidence, clinical parameters, and hospital costs associated with AKI in hospitalized patients with IE in an endemic area with an increasing prevalence of opioid use. This retrospective cohort study included 269 patients admitted to a major referral center in Kentucky with a primary diagnosis of IE from January 2013 to December 2015. Of these, 178 (66.2%) patients had AKI by Kidney Disease Improving Global Outcomes (KDIGO) …

Automated Monitoring Of Behaviour In Zebrafish After Invasive Procedures, Anthony G. Deakin, Jonathan Buckley, Hamzah S. Alzu'bi, Andrew R. Cossins, Joseph W. Spencer, Waleed Al'nuaimy, Iain S. Young, Jack S. Thomson, Lynne U. Sneddon

Validation of Animal Experimentation Collection

Fish are used in a variety of experimental contexts often in high numbers. To maintain their welfare and ensure valid results during invasive procedures it is vital that we can detect subtle changes in behaviour that may allow us to intervene to provide pain-relief. Therefore, an automated method, the Fish Behaviour Index (FBI), was devised and used for testing the impact of laboratory procedures and efficacy of analgesic drugs in the model species, the zebrafish. Cameras with tracking software were used to visually track and quantify female zebrafish behaviour in real time after a number of laboratory procedures including fin …

Dietary Inflammatory Index, Dietary Non-Enzymatic Antioxidant Capacity, And Colorectal And Breast Cancer Risk(Mcc-Spain Study), Mireia Obón-Santacana, Dora Romaguera, Esther Gracia-Lavedan, Amaia Molinuevo, Esther Molina-Montes, Nitin Shivappa, James R. Hébert, Adonia Tardón, Gemma Castaño-Vinyals, Ferran Moratalla, Elisabet Guinó, Rafael Marcos-Gragera, Mikel Azpiri Leire Gil, Rocío Olmedo-Requena, Macarena Lozano-Lorca, Juan Alguacil, Tania Fernández-Villa, Vicente Martín, Antonio J. Molina, María Ederra, Beatriz Perez, Nuria Aragonés, Adela Castello, José Mª Huerta, Trinidad Dierssen-Sotos, Ana Molina-Barceló, Marina Pollán, Manolis Kogevinas, Victor Moreno, Pilar Amiano

Faculty Publications

Inflammation and antioxidant capacity have been associated with colorectal and breast cancer. We computed the dietary inflammatory index (DII®), and the total dietary non-enzymatic antioxidant capacity (NEAC) and associated them with colorectal and breast cancer risk in the population-based multi case-control study in Spain (MCC-Spain). We included 1852 colorectal cancer and 1567 breast cancer cases, and 3447 and 1486 population controls, respectively. DII score and NEAC were derived using data from a semi-quantitative validated food frequency questionnaire. Unconditional logistic regression models were used to estimate odds ratios (OR) and 95% confidence intervals (95%CI) for energy-adjusted DII (E-DII), and a score …

Dietary Inflammatory Index, Dietary Non-Enzymatic Antioxidant Capacity, And Colorectal And Breast Cancer Risk (Mcc-Spain Study), Mireia Obon-Santacana, Dora Romaguera, Esther Gracia-Lavedan, Amaia Molinuevo, Esther Molina-Montes, Nitin Shivappa, James R. Hébert, Adonina Tardon, Gemma Castano-Vinyals, Ferran Moratalla, Elisabet Guino, Rafael Marcos-Gragera, Mikel Azpiri, Leire Gil, Rocio Olmedo-Requena, Macarena Lozano-Lorca, Juan Alguacil, Tania Fernandez-Villa, Vicente Martin, Antonio J. Molina, Maria Ederra, Conchi Moreno-Iribas, Beatriz Perez, Nuria Aragones

Faculty Publications

Inflammation and antioxidant capacity have been associated with colorectal and breast cancer. We computed the dietary inflammatory index (DII^®), and the total dietary non-enzymatic antioxidant capacity (NEAC) and associated them with colorectal and breast cancer risk in the population-based multi case-control study in Spain (MCC-Spain). We included 1852 colorectal cancer and 1567 breast cancer cases, and 3447 and 1486 population controls, respectively. DII score and NEAC were derived using data from a semi-quantitative validated food frequency questionnaire. Unconditional logistic regression models were used to estimate odds ratios (OR) and 95% confidence intervals (95%CI) for energy-adjusted DII (E-DII), and …

Modelling Weighted Signed Networks, Alberto Caimo, Isabella Gollini

Conference papers

In this paper we introduce a new modelling approach to analyse weighted signed networks by assuming that their generative process consists of two models: the interaction model which describes the overall connectivity structure of the relations in the network without taking into account neither the weight nor the sign of the dyadic relations; and the conditional weighted signed network model describes how the edge signed weights form given the interaction structure. We then show how this modelling approach can facilitate the interpretation of the overall network process. Finally, we adopt a Bayesian inferential approach to illustrate the new methodology by …

Cancerous Male And Female Gene Expression, Clarissa Farmer, E. Shannon Tass

Journal of Undergraduate Research

Genetic diagnosing is becoming more popular, as well as more and more accurate. However, many genetic diseases have complex genetic effects and are still not fully understood. Transthyretin Amyloidosis (ATTR; also known as familial or hereditary amyloidosis) is a terminal genetic disease. It is caused by unstable transthyretin proteins that fold improperly, and then deteriorate. The fragmented proteins are deposited outside of the cell and build up in the tissues over time, forming insoluble oligomers. The oligomers continue to grow into Amyloid fibrils, which adversely affect many organs in the body, eventually causing their failure. In order to accurately diagnose, …

Cluster Analysis Via Random Partition Distributions, Brandon Carter, Dr. David B. Dahl

Journal of Undergraduate Research

Cluster analysis is an important exploratory data analysis technique used in a wide variety of fields. Cluster analysis seeks to discover a natural grouping of the data, where items in the same cluster or group are more similar than items from different clusters. Through our research, we developed a novel method for cluster analysis which takes pairwise distance information as input. Our new method improves upon traditional cluster analysis methods which also take pairwise distance information as input, such as hierarchical clustering. Our method, cluster analysis via random partition distributions (CaviarPD) is based on probability distributions and therefore allows the …

Data Mining And Machine Learning To Improve Northern Florida’S Foster Care System, Daniel Oldham, Nathan Foster, Mihhail Berezovski

Beyond: Undergraduate Research Journal

The purpose of this research project is to use statistical analysis, data mining, and machine learning techniques to determine identifiable factors in child welfare service records that could lead to a child entering the foster care system multiple times. This would allow us the capability of accurately predicting a case’s outcome based on these factors. We were provided with eight years of data in the form of multiple spreadsheets from Partnership for Strong Families (PSF), a child welfare services organization based in Gainesville, Florida, who is contracted by the Florida Department for Children and Families (DCF). This data contained a …

Probabilistic Modeling Of Personalized Drug Combinations From Integrated Chemical Screen And Molecular Data In Sarcoma, Noah E. Berlow, Rishi Rikhi, Mathew Geltzeiler, Jinu Abraham, Matthew N. Svalina, Lara E. Davis, Erin Wise, Maria Mancini, Jonathan Noujaim, Atiya Mansoor, Michael J. Quist, Kevin L. Matlock, Martin W. Goros, Brian S. Hernandez, Yee C. Doung, Khin Thway, Tomohide Tsukahara, Jun Nishio, Elaine T. Huang, Susan Airhart, Carol J. Bult, Regina Gandour-Edwards, Robert G. Maki, Robin L. Jones, Joel E. Michalek, Milan Milovancev, Souparno Ghosh, Ranadip Pal, Charles Keller

Department of Statistics: Faculty Publications

Background: Cancer patients with advanced disease routinely exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates molecular sequencing data with functional assay data to develop patient-specific combination cancer treatments. Methods: Tissue taken from a murine model of alveolar rhabdomyosarcoma was used to perform single agent drug screening and DNA/RNA sequencing experiments; results integrated via our computational modeling approach identified …

Cocyclic Hadamard Matrices: An Efficient Search Based Algorithm, Jonathan S. Turner

Theses and Dissertations

This dissertation serves as the culmination of three papers. “Counting the decimation classes of binary vectors with relatively prime fixed-density" presents the first non-exhaustive decimation class counting algorithm. “A Novel Approach to Relatively Prime Fixed Density Bracelet Generation in Constant Amortized Time" presents a novel lexicon for binary vectors based upon the Discrete Fourier Transform, and develops a bracelet generation method based upon the same. “A Novel Legendre Pair Generation Algorithm" expands upon the bracelet generation algorithm and includes additional constraints imposed by Legendre Pairs. It further presents an efficient sorting and comparison algorithm based upon symmetric functions, as well …

Dietary Inflammatory Index And Sleep Quality In Southern Italian Adults, Justyna Godos, Raffaele Ferri, Filippo Caraci, Filomena I. I. Cosentino, Sabrina Castellano, Nitin Shivappa, James R. Hébert, Fabio Galvano, Giuseppe Grosso

Faculty Publications

Background: Current evidence supports the central role of a subclinical, low-grade inflammation in a number of chronic illnesses and mental disorders; however, studies on sleep quality are scarce. The aim of this study was to test the association between the inflammatory potential of the diet and sleep quality in a cohort of Italian adults. Methods: A cross-sectional analysis of baseline data of the Mediterranean healthy Eating, Aging, and Lifestyle (MEAL) study was conducted on 1936 individuals recruited in the urban area of Catania during 2014-2015 through random sampling. A food frequency questionnaire and other validated instruments were used to calculate …

Measure Of Departure From Marginal Average Point-Symmetry For Two-Way Contingency Tables, Kiyotaka Iki, Sadao Tomizawa

Journal of Modern Applied Statistical Methods

For the analysis of two-way contingency tables with ordered categories, Yamamoto, Tahata, Suzuki, and Tomizawa (2011) considered a measure to represent the degree of departure from marginal point-symmetry. The maximum value of the measure cannot distinguish two kinds of marginal complete asymmetry with respect to the midpoint. A measure is proposed which can distinguish two kinds of marginal asymmetry with respect to the midpoint. It also gives large-sample confidence interval for the proposed measure.

The Impact Of Equating On Detection Of Treatment Effects, Youn-Jeng Choi, Seohyun Kim, Allan S. Cohen, Zhenqiu Lu

Journal of Modern Applied Statistical Methods

Equating makes it possible to compare performances on different forms of a test. Three different equating methods (baseline selection, subgroup, and subscore equating) using common-item item response theory equating were examined for their impact on detection of treatment effects in multilevel models.

Field Drilling Data Cleaning And Preparation For Data Analytics Applications, Daniel Cardoso Braga

LSU Master's Theses

Throughout the history of oil well drilling, service providers have been continuously striving to improve performance and reduce total drilling costs to operating companies. Despite constant improvement in tools, products, and processes, data science has not played a large part in oil well drilling. With the implementation of data science in the energy sector, companies have come to see significant value in efficiently processing the massive amounts of data produced by the multitude of internet of thing (IOT) sensors at the rig. The scope of this project is to combine academia and industry experience to analyze data from 13 different …

Epidemiologic Evaluation Of Nhanes For Environmental Factors And Periodontal Disease, P. Emecen-Huja, H. -F. Li, J. L. Ebersole, J. Lambert, Heather M. Bush

Biostatistics Faculty Publications

Periodontitis is a chronic inflammation that destroys periodontal tissues caused by the accumulation of bacterial biofilms that can be affected by environmental factors. This report describes an association study to evaluate the relationship of environmental factors to the expression of periodontitis using the National Health and Nutrition Examination Study (NHANES) from 1999–2004. A wide range of environmental variables (156) were assessed in patients categorized for periodontitis (n = 8884). Multiple statistical approaches were used to explore this dataset and identify environmental variable patterns that enhanced or lowered the prevalence of periodontitis. Our findings indicate an array of environmental variables were …

An Interdisciplinary Weight Loss Program Improves Body Composition And Metabolic Profile In Adolescents With Obesity: Associations With The Dietary Inflammatory Index, Yasmin Alaby Martins Ferreira, Ana Claudia Pelissari Kravchychyn, Sofia De Castro Ferreira Vicente, Raquel Munhoz Da Silveira Campos, Lian Tock, Lila Missae Oyama, Valter Tadeu Boldarine, Deborah Cristina Landi Masquio, David Thivel, Nitin Shivappa, James R. Hébert, Ana R. Dâmaso

Faculty Publications

Background and Aims: The prevalence of overweight and obesity consitutes a global epidemic and it is growing around the world. Food and nutrition are essential requirements for promoting health and protecting against non-communicable chronic diseases, such as obesity and cardiovascular disease. Specific dietary components may modulate inflammation and oxidative stress in obese individuals. The Dietary Inflammatory Index (DII®) was developed to characterize the anti- and pro-inflammatory effects of individuals' diet. Few studies have investigated the role of diet-associated inflammation in adolescents with obesity. The present study aims to investigate the effects of an interdisciplinary weight loss therapy on DII scores …

Implementation Of Multivariate Artificial Neural Networks Coupled With Genetic Algorithms For The Multi-Objective Property Prediction And Optimization Of Emulsion Polymers, David Chisholm

Master's Theses

Machine learning has been gaining popularity over the past few decades as computers have become more advanced. On a fundamental level, machine learning consists of the use of computerized statistical methods to analyze data and discover trends that may not have been obvious or otherwise observable previously. These trends can then be used to make predictions on new data and explore entirely new design spaces. Methods vary from simple linear regression to highly complex neural networks, but the end goal is similar. The application of these methods to material property prediction and new material discovery has been of high interest …

Positivity-Preserving, Energy Stable Numerical Schemes For The Cahn-Hilliard Equation With Logarithmic Potential, Wenbin Chen, Cheng Wang, Xiaoming Wang, Steven M. Wise

Mathematics and Statistics Faculty Research & Creative Works

In this paper we present and analyze finite difference numerical schemes for the Cahn-Hilliard equation with a logarithmic Flory Huggins energy potential. Both first and second order accurate temporal algorithms are considered. in the first order scheme, we treat the nonlinear logarithmic terms and the surface diffusion term implicitly and update the linear expansive term and the mobility explicitly. We provide a theoretical justification that this numerical algorithm has a unique solution, such that the positivity is always preserved for the logarithmic arguments, i.e., the phase variable is always between −1 and 1, at a point-wise level. in particular, our …

Involuntary Hospitalization Among Young People With Early Psychosis: A Population-Based Study Using Health Administrative Data., Rebecca Rodrigues, Arlene G Macdougall, Guangyong Zou, Michael Lebenbaum, Paul Kurdyak, Lihua Li, Salimah Z Shariff, Kelly K Anderson

Epidemiology and Biostatistics Publications

OBJECTIVE: Early psychosis is an important window for establishing long-term trajectories. Involuntary hospitalization during this period may impact subsequent service engagement in people with newly diagnosed psychotic disorder. However, population-based studies of involuntary hospitalization in early psychosis are lacking. We sought to estimate the proportion of people aged 16 to 35 years with early psychosis in Ontario who are hospitalized involuntarily at first admission, and to identify the associated risk factors and outcomes.

METHODS: Using linked population-based health administrative data, we identified incident cases of non-affective psychosis over a five-year period (2009-2013) and followed cases for two years to ascertain …

Image-Based Modeling Of Blood Flow In Cerebral Aneurysms Treated With Intrasaccular Flow Diverting Devices, Fernando Mut, Bong Jae Chung, Jorge Chudyk, Pedro Lylyk, Ramanathan Kadirvel, David F. Kallmes, Juan R. Cebral

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

Modeling the flow dynamics in cerebral aneurysms after the implantation of intrasaccular devices is important for understanding the relationship between flow conditions created immediately posttreatment and the subsequent outcomes. This information, ideally available a priori based on computational modeling prior to implantation, is valuable to identify which aneurysms will occlude immediately and which aneurysms will likely remain patent and would benefit from a different procedure or device. In this report, a methodology for modeling the hemodynamics in intracranial aneurysms treated with intrasaccular flow diverting devices is described. This approach combines an image-guided, virtual device deployment within patient-specific vascular models with …

Tumor Heterogeneity As A Predictor Of Response To Neoadjuvant Chemotherapy In Locally Advanced Rectal Cancer, Alissa Greenbaum, David R. Martin, Therese J. Bocklage, Ji-Hyun Lee, Scott A. Ness, Ashwani Rajput

Pathology and Laboratory Medicine Faculty Publications

BACKGROUND: Neoadjuvant chemoradiotherapy (nCRT) is the standard of care for locally advanced adenocarcinoma of the rectum, but it is currently unknown which patients have disease that will respond. This study tested the correlation between response to nCRT and intratumoral heterogeneity using next-generation sequencing assays.

PATIENTS AND METHODS: DNA was extracted from formalin-fixed, paraffin-embedded biopsy samples from a cohort of patients with locally advanced rectal adenocarcinoma (T3/4 or N1/2 disease) who received nCRT. High read-depth sequencing of > 400 cancer-relevant genes was performed. Tumor mutations and variant allele frequencies were used to calculate mutant-allele tumor heterogeneity (MATH) scores as measures of intratumoral …

Analysis Of An M/M/1 Queue With Working Vacation And Vacation Interruption, Shakir Majid, P. Manoharan

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, an M/M/1 queue with working vacation and vacation interruption is investigated. The server is supposed to interrupt the vacation and return back to the normal working period, if there are at least N customers waiting in the system at a service completion instant during the working vacation period. Otherwise, the server continues the vacation until the system is nonempty after a vacation ends or there are at least N customers after a service ends. In terms of the quasi birth and death process and matrix-geometric solution method, we obtain the distributions for the stationary queue length. Moreover, …

Performance And Economic Evaluation Of Differentiated Multiple Vacation Queueing System With Feedback And Balked Customers, Amina A. Bouchentouf, Latifa Medjahri

Applications and Applied Mathematics: An International Journal (AAM)

The present paper deals with a single server feedback queueing system under two differentiated multiple vacations and balked customers. It is assumed that the service times of the two vacation types are exponentially distributed with different means. The steady-state probabilities of the model are obtained. Some important performance measures of the system are derived. Then, a cost model is developed. Further, a numerical study is presented.