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Articles 5131 - 5160 of 12832
Full-Text Articles in Statistics and Probability
Colloidal And Truly Dissolved Metal(Loid)S In Wastewater Lagoons And Their Removal With Floating Treatment Wetlands, Lauren Sullivan
Colloidal And Truly Dissolved Metal(Loid)S In Wastewater Lagoons And Their Removal With Floating Treatment Wetlands, Lauren Sullivan
Graduate Student Theses, Dissertations, & Professional Papers
Climate change is predicted to cause continuing declines in late-season streamflow, thus increasing the relative contribution of wastewater effluent to surface water flows. Wastewater effluent represents a critical point source of metal and metalloid contamination to aquatic ecosystems and wastewater lagoons are the most common wastewater treatment system in the rural United States. Although the fraction of total wastewater metals and metalloids in "dissolved" forms (defined here asnm) likely drives the potential for negative effects on receiving waters, this broad operational definition lumps truly dissolved solutes (nm) with small colloids and nanomaterials (1-450 nm; hereafter colloids). This size distinction may …
Examining Partisan Advantage In Congressional Maps Using Simulations Based On Election Data, Zachary James Morgan
Examining Partisan Advantage In Congressional Maps Using Simulations Based On Election Data, Zachary James Morgan
Online Theses and Dissertations
Partisan gerrymandering has been and will continue to be a topic of interest in the coming years. States will soon begin their redistricting process following the 2020 Census. We introduce a method of simulating Congressional elections which provides a new way of examining and visualizing the votes-to-seats relationship for a state Congressional map using past election data. We are able to build upon Mira Bernstein's method of uniformly simulating elections by injecting a data-driven component of variation into the simulations. Additionally, we are able to directly evaluate the accuracy of our simulations using a type of cross-validation. We compare our …
Saturated Fat Intake Is Associated With Lung Function In Individuals With Airflow Obstruction: Results From Nhanes 2007⁻2012, Kasey Cornell, Morshed Alam, Elizabeth Lyden, Lisa Wood, Tricia D. Levan, Tara M. Nordgren, Kristina L. Bailey, Corrine K. Hanson
Saturated Fat Intake Is Associated With Lung Function In Individuals With Airflow Obstruction: Results From Nhanes 2007⁻2012, Kasey Cornell, Morshed Alam, Elizabeth Lyden, Lisa Wood, Tricia D. Levan, Tara M. Nordgren, Kristina L. Bailey, Corrine K. Hanson
Journal Articles: Biostatistics
Nutritional status is a well-recognized prognostic indicator in chronic obstructive pulmonary disease (COPD); however, very little is known about the relationship between lung function and saturated fat intake. We used data from the cross-sectional National Health and Nutrition Examination Surveys (NHANES) to assess the relationship between saturated fatty acid (SFA) intake and lung function in the general US adult population. Adults in NHANES (2007⁻2012) with pre-bronchodilator spirometry measurements and dietary SFA intake were included. Primary outcomes were lung function including forced expiratory volume in one second (FEV₁)
Stretching Hiv Treatment: A Replication Study Of Task Shifting In South Africa, Baojiang Chen, Morshed Alam
Stretching Hiv Treatment: A Replication Study Of Task Shifting In South Africa, Baojiang Chen, Morshed Alam
Journal Articles: Biostatistics
The Streamlining Tasks & Roles to Expand Treatment and Care for HIV (STRETCH) program was developed to increase the reach of antiretroviral therapy (ART) for HIV/AIDS patients in Sub-Saharan Africa by training nurses to prescribe, initiate, and maintain ART. Fairall and colleagues conducted a cluster-randomized trial to determine the effects/impact of STRETCH on patient health outcomes in South Africa between 2008 and 2010. The purpose of our replication study is to evaluate Fairall and colleagues' findings. We conducted push button and pure replication studies and measurement and estimation analyses (MEA). Our MEA validates the original findings: (1) overall, time to …
Compound-Specific Isotope Analysis Of Amino Acids In Biological Tissues: Applications In Forensic Entomology, Food Authentication And Soft-Biometrics In Humans, Mayara Patricia Viana De Matos
Compound-Specific Isotope Analysis Of Amino Acids In Biological Tissues: Applications In Forensic Entomology, Food Authentication And Soft-Biometrics In Humans, Mayara Patricia Viana De Matos
Graduate Theses, Dissertations, and Problem Reports (ETD)
In this work we demonstrate the power of compound-specific isotope analysis (CSIA) to analyze proteinaceous biological materials in three distinct forensic applications, including: 1) linking necrophagous blow flies in different life stages to their primary carrion diet; 2) identifying the harvesting area of oysters for food authentication purposes; and 3) the ability to predict biometric traits about humans from their hair.
In the first application, we measured the amino-acid-level fractionation that occurs at each major life stage of Calliphora vicina (Robineau-Desvoidy) (Diptera: Calliphoridae) blow flies. Adult blow flies oviposited on raw pork muscle, beef muscle, or chicken liver. Larvae, pupae …
Quantifying Human Biological Age: A Machine Learning Approach, Syed Ashiqur Rahman
Quantifying Human Biological Age: A Machine Learning Approach, Syed Ashiqur Rahman
Graduate Theses, Dissertations, and Problem Reports (ETD)
Quantifying human biological age is an important and difficult challenge. Different biomarkers and numerous approaches have been studied for biological age prediction, each with its advantages and limitations. In this work, we first introduce a new anthropometric measure (called Surface-based Body Shape Index, SBSI) that accounts for both body shape and body size, and evaluate its performance as a predictor of all-cause mortality. We analyzed data from the National Health and Human Nutrition Examination Survey (NHANES). Based on the analysis, we introduce a new body shape index constructed from four important anthropometric determinants of body shape and body size: body …
Numeracy And Social Justice: A Wide, Deep, And Longstanding Intersection, Kira Hamman, Victor Piercey, Samuel L. Tunstall
Numeracy And Social Justice: A Wide, Deep, And Longstanding Intersection, Kira Hamman, Victor Piercey, Samuel L. Tunstall
Numeracy
We discuss the connection between the numeracy and social justice movements both in historical context and in its modern incarnation. The intersection between numeracy and social justice encompasses a wide variety of disciplines and quantitative topics, but within that variety there are important commonalities. We examine the importance of sound quantitative measures for understanding social issues and the necessity of interdisciplinary collaboration in this work. Particular reference is made to the papers in the first part of the Numeracy special collection on social justice, which appear in this issue.
Snap Scholar: The User Experience Of Engaging With Academic Research Through A Tappable Stories Medium, Ieva Burk
CMC Senior Theses
With the shift to learn and consume information through our mobile devices, most academic research is still only presented in long-form text. The Stanford Scholar Initiative has explored the segment of content creation and consumption of academic research through video. However, there has been another popular shift in presenting information from various social media platforms and media outlets in the past few years. Snapchat and Instagram have introduced the concept of tappable “Stories” that have gained popularity in the realm of content consumption.
To accelerate the growth of the creation of these research talks, I propose an alternative to video: …
Confidence Intervals For The Expected P-Value, Emmanuel Kofi Abrefa
Confidence Intervals For The Expected P-Value, Emmanuel Kofi Abrefa
Open Access Theses & Dissertations
The p-value is widely used in many application fields. In common practice, a scientific finding is deemed statistically significant if its resultant p-value is less than a pre-specified significance level, for example α = 0.05, albeit many statistically significant results are not reproducible in new studies. Mixed reasons including misuses, abuses, misunderstanding and misinterpretation arouse intensive debates and conservatives around the p-value from time to time over the years. Yet no reasonable solutions have been proposed. In this research, we make efforts to close the gap by advocating the use of confidence level for the expected p-value p0. This allows …
Robust Statistical Inference For The Gaussian Distribution, Andrews Tawiah Anum
Robust Statistical Inference For The Gaussian Distribution, Andrews Tawiah Anum
Open Access Theses & Dissertations
The aim of robust statistics is to develop statistical procedures which are not unduly influenced by outliers or observations that are not representative of the underlying "true" data generating process. This thesis focuses on an estimator with this characteristic. The divergence function is introduced in Chapter 2 with the sole aim of taking the function f to be the univariate normal distribution and α - [0, 1]. The estimator fails when we rely on the classic Newton's method to converge to the minimum of the density power divergence (MDPD) function. There is a tendency of such estimator never to approach …
Forecasting Crashes, Credit Card Default, And Imputation Analysis On Missing Values By The Use Of Neural Networks, Jazmin Quezada
Forecasting Crashes, Credit Card Default, And Imputation Analysis On Missing Values By The Use Of Neural Networks, Jazmin Quezada
Open Access Theses & Dissertations
A neural network is a system of hardware and/or software patterned after the operation of neurons in the human brain. Neural networks,- also called Artificial Neural Networks - are a variety of deep learning technology, which also falls under the umbrella of artificial intelligence, or AI. Recent studies shows that Artificial Neural Network has the highest coefficient of determination (i.e. measure to assess how well a model explains and predicts future outcomes.) in comparison to the K-nearest neighbor classifiers, logistic regression, discriminant analysis, naive Bayesian classifier, and classification trees. In this work, the theoretical description of the neural network methodology …
On The Performance Of Variable Selection And Classification Via Rank-Based Classifier, Md Showaib Rahman None Sarker
On The Performance Of Variable Selection And Classification Via Rank-Based Classifier, Md Showaib Rahman None Sarker
Open Access Theses & Dissertations
In high-dimensional gene expression data analysis, the accuracy and reliability of cancer classification and selection of important genes play a very crucial role. To identify these important genes and predict future outcomes (tumor vs. non-tumor), various methods have been proposed in the literature. But only few of them take into account correlation patterns and grouping effects among the genes. In this article, we propose a rank-based modification of the popular penalized logistic regression procedure based on a combination of l1 and l2 penalties capable of handling possible correlation among genes in different groups. While the l1 penalty maintains sparsity, the …
Modeling Correlated Data Via Copulas, Panfeng Liang
Modeling Correlated Data Via Copulas, Panfeng Liang
Open Access Theses & Dissertations
Copulas are widely used to model the dependency structure among components of multi- variate data sets. Elliptical copulas, such as Gaussian copula, are most popular copulas being used since many data sets follow elliptical distributions or meta-elliptical distribu- tions (Fang et al. (2002)). However, today's approaches and software packages require us to assume the specific category, such as Gaussian or Student's T, of the elliptical cop- ula before estimating it. In this Thesis, we will propose a Bayesian method using Markov chain Monte Carlo (MCMC) methods to estimate the density function of elliptical copulas without specifying it is the copula …
Bayesian Analysis Of Variable-Stress Accelerated Life Testing, Richard Okine
Bayesian Analysis Of Variable-Stress Accelerated Life Testing, Richard Okine
Open Access Theses & Dissertations
Several authors have over the years studied the art of modeling data from accelerated life testing and making inferences from such data. In this study, we consider a continuously varying stress accelerated life testing procedure which is the limiting case of the multiple stress-level discussed by Doksum and H´oyland [1]. We derive the likelihood function for the life distribution of the continuously increasing stress accelerated life testing model and consequently the Fisher's Information Matrix. We propose a Bayesian analysis for this distribution using the Gibbs Sampling Procedure. We conduct simulation studies and real data analysis to demonstrate the efficiency of …
Application Of Urinary Metabolites For Cancer Detection, Qin Gao
Application Of Urinary Metabolites For Cancer Detection, Qin Gao
Open Access Theses & Dissertations
Prostate cancer (PCa) is the 3rd most common cause of male cancer mortality in the US. Early diagnosis and treatment of PCa will improve the quality of care and reduce mortality. The prostate specific antigen (PSA) is commonly used in the current PCa screening, but its limitation has resulted in an intense search for more reliable biomarkers. Studies showed that dogs could differentiate PCa patients from negative control by sniffing their urine. As the odor profiles are generated by volatile organic compounds (VOCs), the finding suggests that particular VOCs could be linked to PCa, PCa risk levels and other cancers. …
Nonparametric Collective Spectral Density Estimation With An Application To Clustering The Brain Signals, Mehdi Maadooliat, Ying Sun, Tianbo Chen
Nonparametric Collective Spectral Density Estimation With An Application To Clustering The Brain Signals, Mehdi Maadooliat, Ying Sun, Tianbo Chen
Mathematics, Statistics and Computer Science Faculty Research and Publications
In this paper, we develop a method for the simultaneous estimation of spectral density functions (SDFs) for a collection of stationary time series that share some common features. Due to the similarities among the SDFs, the log‐SDF can be represented using a common set of basis functions. The basis shared by the collection of the log‐SDFs is estimated as a low‐dimensional manifold of a large space spanned by a prespecified rich basis. A collective estimation approach pools information and borrows strength across the SDFs to achieve better estimation efficiency. Moreover, each estimated spectral density has a concise representation using the …
A Tree-Based Multiscale Regression Method, Haiyan Cai, Qingtang Jiang
A Tree-Based Multiscale Regression Method, Haiyan Cai, Qingtang Jiang
Educator Preparation & Leadership Faculty Works
A tree-based method for regression is proposed. In a high dimensional feature space, the method has the ability to adapt to the lower intrinsic dimension of data if the data possess such a property so that reliable statistical estimates can be performed without being hindered by the “curse of dimensionality.” The method is also capable of producing a smoother estimate for a regression function than those from standard tree methods in the region where the function is smooth and also being more sensitive to discontinuities of the function than smoothing splines or other kernel methods. The estimation process in this …
Earthquake Exposures And Mental Health Outcomes In Children And Adolescents From Phulpingdanda Village, Nepal: A Cross-Sectional Study, Jessica S. Schwind, Clara B. Formby, Susan L. Santangelo, Stephanie A. Norman, Rebecca Brown, Rebecca Hoffman Frances, Elisabeth Koss, Dibesh Karmacharya
Earthquake Exposures And Mental Health Outcomes In Children And Adolescents From Phulpingdanda Village, Nepal: A Cross-Sectional Study, Jessica S. Schwind, Clara B. Formby, Susan L. Santangelo, Stephanie A. Norman, Rebecca Brown, Rebecca Hoffman Frances, Elisabeth Koss, Dibesh Karmacharya
Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications
Background
Mental health issues can reach epidemic proportions in developed countries after natural disasters, but research is needed to better understand the impact on children and adolescents in developing nations.
Methods
A cross-sectional study was performed to examine the relationship between earthquake exposures and depression, PTSD, and resilience among children and adolescents in Phulpingdanda village in Nepal, 1 year after the 2015 earthquakes, using the Depression Self-Rating Scale for Children, Child PTSD Symptom Scale, and the Child and Youth Resilience Measure, respectively. To quantify exposure, a basic demographic and household questionnaire, including an earthquake exposure assessment tool for children and …
Power In Pairs: Assessing The Statistical Value Of Paired Samples In Tests For Differential Expression, John R. Stevens, Jennifer S. Herrick, Roger K. Wolff, Martha L. Slattery
Power In Pairs: Assessing The Statistical Value Of Paired Samples In Tests For Differential Expression, John R. Stevens, Jennifer S. Herrick, Roger K. Wolff, Martha L. Slattery
Mathematics and Statistics Faculty Publications
Background: When genomics researchers design a high-throughput study to test for differential expression, some biological systems and research questions provide opportunities to use paired samples from subjects, and researchers can plan for a certain proportion of subjects to have paired samples. We consider the effect of this paired samples proportion on the statistical power of the study, using characteristics of both count (RNA-Seq) and continuous (microarray) expression data from a colorectal cancer study.
Results: We demonstrate that a higher proportion of subjects with paired samples yields higher statistical power, for various total numbers of samples, and for various strengths of …
Large-Scale Genome-Wide Meta-Analysis Of Polycystic Ovary Syndrome Suggests Shared Genetic Architecture For Different Diagnosis Criteria, Felix Day, Tugce Karaderi, Michelle R. Jones, Cindy Meun, Chunyan He, Alex Drong, Peter Kraft, Nan Lin, Hongyan Huang, Linda Broer, Reedik Magi, Richa Saxena, Triin Laisk, Margrit Urbanek, M. Geoffrey Hayes, Gudmar Thorleifsson, Juan Fernandez-Tajes, Anubha Mahajan, Benjamin H. Mullin, Bronwyn G. A. Stuckey, Timothy D. Spector, Scott G. Wilson, Mark O. Goodarzi, Lea Davis, Barbara Obermayer-Pietsch, André G. Uitterlinden, Verneri Anttila, Benjamin M. Neale, Marjo-Riitta Jarvelin, Bart Fauser
Large-Scale Genome-Wide Meta-Analysis Of Polycystic Ovary Syndrome Suggests Shared Genetic Architecture For Different Diagnosis Criteria, Felix Day, Tugce Karaderi, Michelle R. Jones, Cindy Meun, Chunyan He, Alex Drong, Peter Kraft, Nan Lin, Hongyan Huang, Linda Broer, Reedik Magi, Richa Saxena, Triin Laisk, Margrit Urbanek, M. Geoffrey Hayes, Gudmar Thorleifsson, Juan Fernandez-Tajes, Anubha Mahajan, Benjamin H. Mullin, Bronwyn G. A. Stuckey, Timothy D. Spector, Scott G. Wilson, Mark O. Goodarzi, Lea Davis, Barbara Obermayer-Pietsch, André G. Uitterlinden, Verneri Anttila, Benjamin M. Neale, Marjo-Riitta Jarvelin, Bart Fauser
Internal Medicine Faculty Publications
Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed based on the two criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a fixed-effect, inverse-weighted-variance meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related …
Dichotomous Scoring Of Tdp-43 Proteinopathy From Specific Brain Regions In 27 Academic Research Centers: Associations With Alzheimer's Disease And Cerebrovascular Disease Pathologies, Yuriko Katsumata, David W. Fardo, Walter A. Kukull, Peter T. Nelson
Dichotomous Scoring Of Tdp-43 Proteinopathy From Specific Brain Regions In 27 Academic Research Centers: Associations With Alzheimer's Disease And Cerebrovascular Disease Pathologies, Yuriko Katsumata, David W. Fardo, Walter A. Kukull, Peter T. Nelson
Biostatistics Faculty Publications
TAR-DNA binding protein 43 (TDP-43) proteinopathy is a common brain pathology in elderly persons, but much remains to be learned about this high-morbidity condition. Published stage-based systems for operationalizing disease severity rely on the involvement (presence/absence) of pathology in specific anatomic regions. To examine the comorbidities associated with TDP-43 pathology in aged individuals, we studied data from the National Alzheimer’s Coordinating Center (NACC) Neuropathology Data Set. Data were analyzed from 929 included subjects with available TDP-43 pathology information, sourced from 27 different American Alzheimer’s Disease Centers (ADCs). Cases with relatively unusual diseases including autopsy-proven frontotemporal lobar degeneration (FTLD-TDP or FTLD-tau) …
Positive Association Between Dietary Inflammatory Index And The Risk Of Osteoporosis: Results From The Koges_Health Examinee (Hexa) Cohort Study, Hye Sun Kim, Cheongmin Sohn, Minji Kwon, Woori Na, Nitin Shivappa, James R. Hébert, Mi Kyung Kim
Positive Association Between Dietary Inflammatory Index And The Risk Of Osteoporosis: Results From The Koges_Health Examinee (Hexa) Cohort Study, Hye Sun Kim, Cheongmin Sohn, Minji Kwon, Woori Na, Nitin Shivappa, James R. Hébert, Mi Kyung Kim
Faculty Publications
Previous studies have found that diet’s inflammatory potential is related to various diseases. However, little is known about its relationship with osteoporosis. The aim of this study was to investigate the association between the dietary inflammatory index (DII®) and osteoporosis risk in a large-scale prospective cohort study in Korea. This prospective cohort study included 159,846 participants (men 57,740; women 102,106) from South Korea with a mean follow-up of 7.9 years. The DII was calculated through a validated semi-quantitative FFQ (SQFFQ), and information on osteoporosis was self-reported by the participants. Analyses were performed by using a multivariable Cox proportional hazard model. …
Estimation Of The Parameters In A Spatial Regressive-Autoregressive Model Using Ord's Eigenvalue Method, Sajib Mahmud Mahmud Tonmoy
Estimation Of The Parameters In A Spatial Regressive-Autoregressive Model Using Ord's Eigenvalue Method, Sajib Mahmud Mahmud Tonmoy
UNLV Theses, Dissertations, Professional Papers, and Capstones
In this thesis, we study one of Ord's (1975) global spatial regression models.
Ord considered spatial regressive-autoregressive models to describe the interaction
between location and a response variable in the presence of several covariates. He also
developed a practical estimation method for the parameters of this regression model
using the eigenvalues of a weight matrix that captures the contiguity of locations.
We review the theoretical aspects of his estimation method and implement it in the
statistical package R.
We also implement Ord's methods on the Columbus, Ohio, crime data set from the
year 1980, which involves the crime rate of …
Serum Nutrient Levels And Aging Effects On Periodontitis, Jeffrey L Ebersole, Joshua Lambert, Heather Bush, Pinar Emecen Huja, Arpita Basu
Serum Nutrient Levels And Aging Effects On Periodontitis, Jeffrey L Ebersole, Joshua Lambert, Heather Bush, Pinar Emecen Huja, Arpita Basu
Biostatistics Faculty Publications
Periodontal disease damages tissues as a result of dysregulated host responses against the chronic bacterial biofilm insult and approximately 50% of US adults > 30 years old exhibit periodontitis. The association of five blood nutrients and periodontitis were evaluated due to our previous findings regarding a potential protective effect for these nutrients in periodontal disease derived from the US population sampled as part of the National Health and Nutrition Examination Survey (1999–2004). Data from over 15,000 subjects was analyzed for blood levels of cis-β-carotene, β-cryptoxanthin, folate, vitamin D, and vitamin E, linked with analysis of the presence and severity of periodontitis. …
Evaluating Rater Effects In The Context Of Ethical Reasoning Essay Assessment: An Application Of The Many-Facets Rasch Measurement Model, Madison A. Holzman
Evaluating Rater Effects In The Context Of Ethical Reasoning Essay Assessment: An Application Of The Many-Facets Rasch Measurement Model, Madison A. Holzman
Dissertations, 2014-2019
Performance assessments are an often desired type of assessment due to their potential for alignment between the assessment and reality. However, due to the rater-mediated nature of scoring (Eckes, 2015), performance assessments have psychometric challenges that cannot be ignored in testing and assessment work. Specifically, performance assessment scores are prone to rater effects, or systematic differences in how raters evaluate performance assessment products (Myford & Wolfe, 2003). The purpose of this project was to evaluate ethical reasoning essay scores for rater effects. The Many-Facets Rasch Measurement (MFRM) model was used to evaluate ethical reasoning essay scores for rater leniency/severity effects, …
The Principal Problem With Principal Components Regression, Heidi Margaret Artigue, Gary Smith
The Principal Problem With Principal Components Regression, Heidi Margaret Artigue, Gary Smith
Pomona Faculty Publications and Research
Principal components regression (PCR) reduces a large number of explanatory variables down to a small number of principal components. PCR is thought to be more useful, the more numerous the potential explanatory variables. The reality is that a large number of candidate explanatory variables does not make PCR more valuable; instead, it magnifies the failings of PCR.
Subject Level Clustering Using A Negative Binomial Model For Small Transcriptomic Studies., Qian Li, Janelle R. Noel-Macdonnell, Devin C. Koestler, Ellen L. Goode, Brooke L. Fridley
Subject Level Clustering Using A Negative Binomial Model For Small Transcriptomic Studies., Qian Li, Janelle R. Noel-Macdonnell, Devin C. Koestler, Ellen L. Goode, Brooke L. Fridley
Manuscripts, Articles, Book Chapters and Other Papers
BACKGROUND: Unsupervised clustering represents one of the most widely applied methods in analysis of high-throughput 'omics data. A variety of unsupervised model-based or parametric clustering methods and non-parametric clustering methods have been proposed for RNA-seq count data, most of which perform well for large samples, e.g. N ≥ 500. A common issue when analyzing limited samples of RNA-seq count data is that the data follows an over-dispersed distribution, and thus a Negative Binomial likelihood model is often used. Thus, we have developed a Negative Binomial model-based (NBMB) clustering approach for application to RNA-seq studies.
RESULTS: We have developed a Negative …
Application Of Bradford’S Law Of Scattering On Research Publication In Astronomy & Astrophysics Of India, Satish Kumar, Senthilkumar R.
Application Of Bradford’S Law Of Scattering On Research Publication In Astronomy & Astrophysics Of India, Satish Kumar, Senthilkumar R.
Library Philosophy and Practice (e-journal)
The present study is focused on examining the application of Bradford’s law of scattering on research articles published in the field of Astronomy & Astrophysics by Indian scientist during 1988-2017. The bibliographic data was retrieved from Web of Science (WoS) bibliographic data base for different period of time. Total 18,877 journal’s article have been published by Indian scientist in the field of Astronomy & Astrophysics during 1988-2017 which was further retrieved and analyzed separately for different blocks of 10 years as well as for 30 years consolidated too. The core journal of the field was identified. The Bradford law of …
A Proficient Two-Stage Stratified Randomized Response Strategy, Tanveer A. Tarray, Housila P. Singh
A Proficient Two-Stage Stratified Randomized Response Strategy, Tanveer A. Tarray, Housila P. Singh
Journal of Modern Applied Statistical Methods
A stratified randomized response model based on R. Singh, Singh, Mangat, and Tracy (1995) improved two-stage randomized response strategy is proposed. It has an optimal allocation and large gain in precision. Conditions are obtained under which the proposed model is more efficient than R. Singh et al. (1995) and H. P. Singh and Tarray (2015) models. Numerical illustrations are also given in support of the present study.
A Logitudinal Feature Selection Method Identifies Relevant Genes To Distinguish Complicated Injury And Uncomplicated Injury Over Time, Suyan Tian, Chi Wang, Howard H. Chang
A Logitudinal Feature Selection Method Identifies Relevant Genes To Distinguish Complicated Injury And Uncomplicated Injury Over Time, Suyan Tian, Chi Wang, Howard H. Chang
Biostatistics Faculty Publications
Background: Feature selection and gene set analysis are of increasing interest in the field of bioinformatics. While these two approaches have been developed for different purposes, we describe how some gene set analysis methods can be utilized to conduct feature selection.
Methods: We adopted a gene set analysis method, the significance analysis of microarray gene set reduction (SAMGSR) algorithm, to carry out feature selection for longitudinal gene expression data.
Results: Using a real-world application and simulated data, it is demonstrated that the proposed SAMGSR extension outperforms other relevant methods. In this study, we illustrate that a gene’s expression profiles over …