Iterative Matrix Factorization Method For Social Media Data Location Prediction, 2018 Harvey Mudd College
Iterative Matrix Factorization Method For Social Media Data Location Prediction, Natchanon Suaysom
HMC Senior Theses
Since some of the location of where the users posted their tweets collected by social media company have varied accuracy, and some are missing. We want to use those tweets with highest accuracy to help fill in the data of those tweets with incomplete information. To test our algorithm, we used the sets of social media data from a city, we separated them into training sets, where we know all the information, and the testing sets, where we intentionally pretend to not know the location. One prediction method that was used in (Dukler, Han and Wang, 2016) requires appending one-hot ...
Quantifying Certainty: The P-Value, 2017 Central Washington University
Quantifying Certainty: The P-Value, Dominic Klyve
Statistics and Probability
No abstract provided.
Optimized Adaptive Enrichment Designs For Multi-Arm Trials: Learning Which Subpopulations Benefit From Different Treatments, 2017 Department of Biostatistics, Brown School of Public Health
Optimized Adaptive Enrichment Designs For Multi-Arm Trials: Learning Which Subpopulations Benefit From Different Treatments, Jon Arni Steingrimsson, Joshua Betz, Tiachen Qian, Michael Rosenblum
Johns Hopkins University, Dept. of Biostatistics Working Papers
We propose a class of adaptive randomized trial designs for comparing two treatments to a common control in two disjoint subpopulations. The type of adaptation, called adaptive enrichment, involves a preplanned rule for modifying enrollment and arm assignment based on accruing data in an ongoing trial. The motivation for this adaptive feature is that interim data may indicate that a subpopulation, such as those with lower disease severity at baseline, are unlikely to benefit from a particular treatment, while uncertainty remains for the other treatment and/or subpopulation. We developed a new multiple testing procedure tailored to this design problem ...
Comparison Of Adaptive Randomized Trial Designs For Time-To-Event Outcomes That Expand Versus Restrict Enrollment Criteria, To Test Non-Inferiority, 2017 Johns Hopkins Bloomberg School of Public Health, Department of Biostatistics
Comparison Of Adaptive Randomized Trial Designs For Time-To-Event Outcomes That Expand Versus Restrict Enrollment Criteria, To Test Non-Inferiority, Josh Betz, Jon Arni Steingrimsson, Tianchen Qian, Michael Rosenblum
Johns Hopkins University, Dept. of Biostatistics Working Papers
Adaptive enrichment designs involve preplanned rules for modifying patient enrollment criteria based on data accrued in an ongoing trial. These designs may be useful when it is suspected that a subpopulation, e.g., defined by a biomarker or risk score measured at baseline, may benefit more from treatment than the complementary subpopulation. We compare two types of such designs, for the case of two subpopulations that partition the overall population. The first type starts by enrolling the subpopulation where it is suspected the new treatment is most likely to work, and then may expand inclusion criteria if there is early ...
Using Ranked Auxiliary Covariate As A More Efficient Sampling Design For Ancova Model: Analysis Of A Psychological Intervention To Buttress Resilience, Rajai Jabrah, Hani Samawi, Robert Vogel, Haresh Rochani, Daniel Linder
Hani M. Samawi
Drawing a sample can be costly or time consuming in some studies. However, it may be possible to rank the sampling units according to some baseline auxiliary covariates, which are easily obtainable, and/or cost efficient. Ranked set sampling (RSS) is a method to achieve this goal. In this paper, we propose a modified approach of the RSS method to allocate units into an experimental study that compares L groups. Computer simulation estimates the empirical nominal values and the empirical power values for the test procedure of comparing L different groups using modified RSS based on the regression approach in ...
Inference On Overlapping Coefficients In Two Exponential Populations, 2017 Yarmouk University
Inference On Overlapping Coefficients In Two Exponential Populations, Mohammad F. Al-Saleh, Hani M. Samawi
Hani M. Samawi
Three measures of overlap, namely Matusita’s measureρ , Morisita’s measure λ and Weitzman’s measure Δ are investigated in this article for two exponential populations with different means. It is well that the estimators of those measures of overlap are biased. The bias is of these estimators depends on the unknown overlap parameters. There are no closed-form, exact formulas, for those estimators variances or their exact sampling distributions. Monte Carlo evaluations are used to study the bias and precision of the proposed overlap measures. Bootstrap method and Taylor series approximation are used to construct confidence intervals for the overlap ...
Evaluating The Efficiency Of Treatment Comparison In Crossover Design By Allocating Subjects Based On Ranked Auxiliary Variable, 2017 Georgia Southern University
Evaluating The Efficiency Of Treatment Comparison In Crossover Design By Allocating Subjects Based On Ranked Auxiliary Variable, Yisong Huang, Hani Samawi, Robert Vogel, Jingjing Yin, Worlanyo E. Gato, Daniel Linder
Hani M. Samawi
The validity of statistical inference depends on proper randomization methods. However, even with proper randomization, we can have imbalanced with respect to important characteristics. In this paper, we introduce a method based on ranked auxiliary variables for treatment allocation in crossover designs using Latin squares models. We evaluate the improvement of the efficiency in treatment comparisons using the proposed method. Our simulation study reveals that our proposed method provides a more powerful test compared to simple randomization with the same sample size. The proposed method is illustrated by conducting an experiment to compare two different concentrations of titanium dioxide nanofiber ...
Estimation Of P(X > Y) When X And Y Are Dependent Random Variables Using Different Bivariate Sampling Schemes, 2017 Georgia Southern University
Estimation Of P(X > Y) When X And Y Are Dependent Random Variables Using Different Bivariate Sampling Schemes, Hani M. Samawi, Amal Helu, Haresh Rochani, Jingjing Yin, Daniel Linder
Hani M. Samawi
The stress-strength models have been intensively investigated in the literature in regards of estimating the reliability θ = P (X > Y) using parametric and nonparametric approaches under different sampling schemes when X and Y are independent random variables. In this paper, we consider the problem of estimating θ when (X, Y) are dependent random variables with a bivariate underlying distribution. The empirical and kernel estimates of θ = P (X > Y), based on bivariate ranked set sampling (BVRSS) are considered, when (X, Y) are paired dependent continuous random variables. The estimators obtained are compared to their counterpart, bivariate simple random sampling (BVSRS ...
Correction Of Verication Bias Using Log-Linear Models For A Single Binaryscale Diagnostic Tests, 2017 Georgia Southern University
Correction Of Verication Bias Using Log-Linear Models For A Single Binaryscale Diagnostic Tests, Haresh Rochani, Hani M. Samawi, Robert L. Vogel, Jingjing Yin
Hani M. Samawi
In diagnostic medicine, the test that determines the true disease status without an error is referred to as the gold standard. Even when a gold standard exists, it is extremely difficult to verify each patient due to the issues of costeffectiveness and invasive nature of the procedures. In practice some of the patients with test results are not selected for verification of the disease status which results in verification bias for diagnostic tests. The ability of the diagnostic test to correctly identify the patients with and without the disease can be evaluated by measures such as sensitivity, specificity and predictive ...
Prevalence And Trends In Transmitted And Acquired Antiretroviral Drug Resistance, Washington, Dc, 1999-2014., 2017 George Washington University
Prevalence And Trends In Transmitted And Acquired Antiretroviral Drug Resistance, Washington, Dc, 1999-2014., Annette M Aldous, Amanda D Castel, David M Parenti
Epidemiology and Biostatistics Faculty Publications
Drug resistance limits options for antiretroviral therapy (ART) and results in poorer health outcomes among HIV-infected persons. We sought to characterize resistance patterns and to identify predictors of resistance in Washington, DC.
We analyzed resistance in the DC Cohort, a longitudinal study of HIV-infected persons in care in Washington, DC. We measured cumulative drug resistance (CDR) among participants with any genotype between 1999 and 2014 (n = 3411), transmitted drug resistance (TDR) in ART-naïve persons (n = 1503), and acquired drug resistance (ADR) in persons with genotypes before and after ART initiation (n = 309). Using logistic regression, we assessed associations ...
The University Of Iowa Biomass Energy Sustainability Index: A Decision-Making Tool For The University Of Iowa Biomass Partnership Project, Liz Christiansen, Ingrid Gronstal Anderson, Ferman Milster, Sara Maples, Aaron Strong, Adam Ward, Eric Tate, Tyler Priest, Emily A. Heaton, Lisa A. Schulte Moore, Richard B. Hall, John Tyndall, Maeraj Hafiz Sheikh, Daryl Smith
Work continued on a plan to increase the renewable, sustainable fuel sources available to power operations at the University of Iowa in Iowa City. A team of researchers from multiple institutions collaborated to create a tool that would allow the UI to evaluate its alternative energy options more effectively.
A Hierarchical Bayesian Approach To Distinguishing Serial And Parallel Processing, 2017 Wright State University - Main Campus
A Hierarchical Bayesian Approach To Distinguishing Serial And Parallel Processing, Joseph W. Houpt, Mario Fifić
Joseph W. Houpt
Nonparametric Variable Importance Assessment Using Machine Learning Techniques, 2017 Department of Biostatistics, University of Washington
Nonparametric Variable Importance Assessment Using Machine Learning Techniques, Brian D. Williamson, Peter B. Gilbert, Noah Simon, Marco Carone
UW Biostatistics Working Paper Series
In a regression setting, it is often of interest to quantify the importance of various features in predicting the response. Commonly, the variable importance measure used is determined by the regression technique employed. For this reason, practitioners often only resort to one of a few regression techniques for which a variable importance measure is naturally defined. Unfortunately, these regression techniques are often sub-optimal for predicting response. Additionally, because the variable importance measures native to different regression techniques generally have a different interpretation, comparisons across techniques can be difficult. In this work, we study a novel variable importance measure that can ...
Arca Controls Metabolism, Chemotaxis, And Motility Contributing To The Pathogenicity Of Avian Pathogenic Escherichia Coli, 2017 Nanjing Agricultural University
Arca Controls Metabolism, Chemotaxis, And Motility Contributing To The Pathogenicity Of Avian Pathogenic Escherichia Coli, Fengwei Jiang, Chunxia An, Yinli Bao, Xuefeng Zhao, Robert L. Jernigan, Andrew Lithio, Dan Nettleton, Ling Li, Eve S. Wurtele, Lisa K. Nolan, Chengping Lu, Ganwu Li
Avian pathogenic Escherichia coli (APEC) strains cause one of the three most significant infectious diseases in the poultry industry and are also potential food-borne pathogens threating human health. In this study, we showed that ArcA (aerobic respiratory control), a global regulator important for E. coli's adaptation from anaerobic to aerobic conditions and control of that bacterium's enzymatic defenses against reactive oxygen species (ROS), is involved in the virulence of APEC. Deletion of arcA significantly attenuates the virulence of APEC in the duck model. Transcriptome sequencing (RNA-Seq) analyses comparing the APEC wild type and the arcA mutant indicate that ...
Time Series Copulas For Heteroskedastic Data, 2017 Melbourne Business School
Time Series Copulas For Heteroskedastic Data, Ruben Loaiza-Maya, Michael S. Smith, Worapree Maneesoonthorn
Michael Stanley Smith
Index Number Of Iowa Farm Products Prices, 2017 Iowa State College
Index Number Of Iowa Farm Products Prices, Gertrude M. Cox
Bulletin (Iowa Agricultural Experiment Station)
The present Iowa farm price index has been in use since 1926. It is widely employed as a measure of the general level of Iowa farm prices and appears each month in the price barometer published in Agricultural Economic Facts2. A few years ago Peck3 developed a farm lease, known as the sliding scale lease, in which the rental payments are based on and vary with the changes in the index number. More recently, contracts covering land sales have been devised in which the interest payments and in some cases also the principal payments are based on this ...
Annuity Product Valuation And Risk Measurement Under Correlated Financial And Longevity Risks, 2017 The University of Western Ontario
Annuity Product Valuation And Risk Measurement Under Correlated Financial And Longevity Risks, Soohong Park
Electronic Thesis and Dissertation Repository
Longevity risk is a non-diversifiable risk and regarded as a pressing socio-economic challenge of the century. Its accurate assessment and quantification is therefore critical to enable pension-fund companies provide sustainable old-age security and maintain a resilient global insurance market. Fluctuations and a decreasing trend in mortality rates, which give rise to longevity risk, as well as the uncertainty in interest-rate dynamics constitute the two fundamental determinants in pricing and risk management of longevity-dependent products. We also note that historical data reveal some evidence of strong correlation between mortality and interest rates and must be taken into account when modelling their ...
Examination And Comparison Of The Performance Of Common Non-Parametric And Robust Regression Models, 2017 Stephen F Austin State University
Examination And Comparison Of The Performance Of Common Non-Parametric And Robust Regression Models, Gregory F. Malek
Electronic Theses and Dissertations
Examination and Comparison of the Performance of Common Non-Parametric and Robust Regression Models
Gregory Frank Malek
Stephen F. Austin State University, Masters in Statistics Program,
Nacogdoches, Texas, U.S.A.
This work investigated common alternatives to the least-squares regression method in the presence of non-normally distributed errors. An initial literature review identified a variety of alternative methods, including Theil Regression, Wilcoxon Regression, Iteratively Re-Weighted Least Squares, Bounded-Influence Regression, and Bootstrapping methods. These methods were evaluated using a simple simulated example data set, as well as various real data sets, including math proficiency data, Belgian telephone ...
The Soybean Rhg1 Locus For Resistance To The Soybean Cyst Nematode Heterodera Glycines Regulates The Expression Of A Large Number Of Stress- And Defense-Related Genes In Degenerating Feeding Cells, 2017 University of Missouri
The Soybean Rhg1 Locus For Resistance To The Soybean Cyst Nematode Heterodera Glycines Regulates The Expression Of A Large Number Of Stress- And Defense-Related Genes In Degenerating Feeding Cells, Pramod Kaitheri Kandoth, Nagabhushana Ithal, Justin Recknor, Tom Maier, Dan Nettleton, Thomas J. Baum, Melissa G. Mitchum
To gain new insights into the mechanism of soybean (Glycine max) resistance to the soybean cyst nematode (Heterodera glycines), we compared gene expression profiles of developing syncytia in soybean near-isogenic lines differing at Rhg1 (for resistance to Heterodera glycines), a major quantitative trait locus for resistance, by coupling laser capture microdissection with microarray analysis. Gene expression profiling revealed that 1,447 genes were differentially expressed between the two lines. Of these, 241 (16.8%) were stress- and defense-related genes. Several stress-related genes were up-regulated in the resistant line, including those encoding homologs of enzymes that lead to increased levels of ...
Improving The Accuracy For The Long-Term Hydrologic Impact Assessment (L-Thia) Model, 2017 Purdue University
Improving The Accuracy For The Long-Term Hydrologic Impact Assessment (L-Thia) Model, Anqi Zhang, Lawrence Theller, Bernard A. Engel
The Summer Undergraduate Research Fellowship (SURF) Symposium
Urbanization increases runoff by changing land use types from less impervious to impervious covers. Improving the accuracy of a runoff assessment model, the Long-Term Hydrologic Impact Assessment (L-THIA) Model, can help us to better evaluate the potential uses of Low Impact Development (LID) practices aimed at reducing runoff, as well as to identify appropriate runoff and water quality mitigation methods. Several versions of the model have been built over time, and inconsistencies have been introduced between the models. To improve the accuracy and consistency of the model, the equations and parameters (primarily curve numbers in the case of this model ...