Estimation Problems For Pooled Data,
2019
University of South Carolina
Estimation Problems For Pooled Data, Xichen Mou
Theses and Dissertations
In epidemiological applications, individual specimens (e.g., blood, urine, etc.) are often pooled together to detect the presence of disease or to measure the concentration level of a specific biomarker. Due to the advantage of cost efficiency, pooled data are also seen in diverse areas such as genetics, animal ecology, and environmental science. With pooled data, individual observations are masked and new statistical methods are needed to estimate characteristics such as disease prevalence, the underlying density function of a biomarker, etc. We focus on three estimation problems for pooled data. Chapters 2 and 3 propose nonparametric estimators for the density function …
Investigations On Multiple Interval Estimators,
2019
University of South Carolina
Investigations On Multiple Interval Estimators, Taeho Kim
Theses and Dissertations
Multiple interval estimation for a set of parameters is investigated. To begin, a strategy of optimization for a multiple interval estimator (MIE) is introduced. This approach allocates distinct optimized levels to individual interval estimators so that the global expected content can be minimized while the global coverage probability is still maintained at a global level. This optimal allocation is achieved by a decision theoretic procedure which consists of two global risk functions. The major part of this manuscript is devoted to two multiple interval estimation procedures. Both procedures adopt prior information added to the classical setting, but these procedures do …
Multivariate Probit Models For Interval-Censored Failure Time Data,
2019
University of South Carolina
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 …
Copula-Based Zero-Inflated Count Time Series Models,
2019
Old Dominion University
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 …
Interpreting Patient Reported Outcomes In Orthopaedic Surgery: A Systematic Review,
2019
Western University
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,
2019
National Chiao Tung University
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,
2019
Western University
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,
2019
University of Kentucky
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,
2019
University of Liverpool
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),
2019
University of South Carolina
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),
2019
University of South Carolina
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,
2019
Technological University Dublin
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,
2019
Brigham Young University
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,
2019
Brigham Young University
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,
2019
Embry-Riddle Aeronautical University, Daytona Beach
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,
2019
Children's Cancer Therapy Development Institut
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,
2019
Air Force Institute of Technology
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,
2019
University of South Carolina
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,
2019
Tokyo University of Science
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,
2019
University of Alabama
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.
