Statistics and Probability Commons^™

Allocating Interventions Based On Counterfactual Predictions: A Case Study On Homelessness Services, Amanda R. Kube

Engineering and Applied Science Theses & Dissertations

Modern statistical and machine learning methods are increasingly capable of modeling individual or personalized treatment effects by predicting counterfactual outcomes. These counterfactual predictions could be used to allocate different interventions across populations based on individual characteristics. In many domains, like social services, the availability of possible interventions can be severely resource limited. This thesis considers possible improvements to the allocation of such services in the context of homelessness service provision in a major metropolitan area. Using data from the homeless system, I show potential for substantial predicted benefits in terms of reducing the number of families who experience repeat episodes ...

On Passing The Buck, Adam J. Hammett, Anna Joy Yang

Adam J. Hammett, Ph.D.

Imagine there are n>1 people seated around a table, and person S starts with a fair coin they will flip to decide whom to hand the coin next -- if "heads" they pass right, and if "tails" they pass left. This process continues until all people at the table have "touched" the coin. Curiously, it turns out that all people seated at the table other than S have the same probability 1/(n-1) of being last to touch the coin. In fact, Lovasz and Winkler ("A note on the last new vertex visited by a random walk," J. Graph Theory ...

Using Random Forests To Describe Equity In Higher Education: A Critical Quantitative Analysis Of Utah’S Postsecondary Pipelines, Tyler Mcdaniel

Butler Journal of Undergraduate Research

The following work examines the Random Forest (RF) algorithm as a tool for predicting student outcomes and interrogating the equity of postsecondary education pipelines. The RF model, created using longitudinal data of 41,303 students from Utah's 2008 high school graduation cohort, is compared to logistic and linear models, which are commonly used to predict college access and success. Substantially, this work finds High School GPA to be the best predictor of postsecondary GPA, whereas commonly used ACT and AP test scores are not nearly as important. Each model identified several demographic disparities in higher education access, most significantly ...

A Systems Modeling Approach To Forecast Corn Economic Optimum Nitrogen Rate, Laila A. Puntel, John E. Sawyer, Daniel W. Barker, Peter J. Thorburn, Michael J. Castellano, Kenneth J. Moore, Andy Vanloocke, Emily A. Heaton, Sotirios V. Archontoulis

Agronomy Publications

Historically crop models have been used to evaluate crop yield responses to nitrogen (N) rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM) calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation) combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1) evaluate the ...

On Passing The Buck, Adam J. Hammett, Anna Joy Yang

The Research and Scholarship Symposium

Imagine there are n>1 people seated around a table, and person S starts with a fair coin they will flip to decide whom to hand the coin next -- if "heads" they pass right, and if "tails" they pass left. This process continues until all people at the table have "touched" the coin. Curiously, it turns out that all people seated at the table other than S have the same probability 1/(n-1) of being last to touch the coin. In fact, Lovasz and Winkler ("A note on the last new vertex visited by a random walk," J. Graph Theory ...

The Subject Librarian Newsletter, Statistics, Fall 2016, Sandy Avila

Sandy Avila

No abstract provided.

The Devil You Don’T Know: A Spatial Analysis Of Crime At Newark’S Prudential Center On Hockey Game Days, Justin Kurland, Eric Piza

Journal of Sport Safety and Security

Inspired by empirical research on spatial crime patterns in and around sports venues in the United Kingdom, this paper sought to measure the criminogenic extent of 216 hockey games that took place at the Prudential Center in Newark, NJ between 2007-2016. Do games generate patterns of crime in the areas beyond the arena, and if so, for what type of crime and how far? Police-recorded data for Newark are examined using a variety of exploratory methods and non-parametric permutation tests to visualize differences in crime patterns between game and non-game days across all of Newark and the downtown area. Change ...

A Comparison Of Unsupervised Methods For Dna Microarray Leukemia Data, Denise Harness

Appalachian Student Research Forum

Advancements in DNA microarray data sequencing have created the need for sophisticated machine learning algorithms and feature selection methods. Probabilistic graphical models, in particular, have been used to identify whether microarrays or genes cluster together in groups of individuals having a similar diagnosis. These clusters of genes are informative, but can be misleading when every gene is used in the calculation. First feature reduction techniques are explored, however the size and nature of the data prevents traditional techniques from working efficiently. Our method is to use the partial correlations between the features to create a precision matrix and predict which ...

Introduction To Statistics (Ga Southern), Scott Kersey, Stephen Carden

Mathematics Grants Collections

This Grants Collection for Introduction to Statistics was created under a Round Eight ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

• Linked Syllabus
• Initial Proposal
• Final Report

Pricing Asian Options: Volatility Forecasting As A Source Of Downside Risk, Adam T. Diehl

Undergraduate Economic Review

Asian options are a class of derivative securities whose payoffs average movements in the underlying asset as a means of hedging exposure to unexpected market behavior. We find that despite their volatility smoothing properties, the price of an Asian option is sensitive to the choice of volatility model employed to price them from market data. We estimate the errors induced by two common schemes of forecasting volatility and their potential impact upon trading.

A Visual Tool For Interdisciplinary Investigations, James J. O'Keefe

Lesley University Community of Scholars Day

Interdisciplinary investigations using the Gapminder dynamic interactive software will be the focus of this seminar.

Robust Estimation Of The Average Treatment Effect In Alzheimer's Disease Clinical Trials, Michael Rosenblum, Aidan Mcdermont, Elizabeth Colantuoni

Johns Hopkins University, Dept. of Biostatistics Working Papers

The primary analysis of Alzheimer's disease clinical trials often involves a mixed-model repeated measure (MMRM) approach. We consider another estimator of the average treatment effect, called targeted minimum loss based estimation (TMLE). This estimator is more robust to violations of assumptions about missing data than MMRM.

We compare TMLE versus MMRM by analyzing data from a completed Alzheimer's disease trial data set and by simulation studies. The simulations involved different missing data distributions, where loss to followup at a given visit could depend on baseline variables, treatment assignment, and the outcome measured at previous visits. The TMLE generally ...

Therapy Dogs On Campus: An Exploration Of How Dog Therapy Services Affect Undergraduate Students’ Stress Levels, Tanna Lauriente, Drayden A.D. Kopp

Proceedings of the Annual Thompson Rivers University Undergraduate Research and Innovation Conference

University can be stressful for many undergraduates. Fortunately, there are various stress reduction strategies, including weekly dog therapy sessions, offered at Thompson Rivers University. This study investigated the effects of dog therapy on students via a self-reported stress survey. Students in a control group (n= 98), who did not visit the therapy dogs, and a test group (n= 108), who did, provided data on their stress level and various other factors. Students in the test group reported their stress levels before and after participating in a dog therapy session by circling a number on our stress scale, determining their stress ...

Default Priors For The Intercept Parameter In Logistic Regressions, Philip S. Boonstra, Ryan P. Barbaro, Ananda Sen

The University of Michigan Department of Biostatistics Working Paper Series

In logistic regression, separation refers to the situation in which a linear combination of predictors perfectly discriminates the binary outcome. Because finite-valued maximum likelihood parameter estimates do not exist under separation, Bayesian regressions with informative shrinkage of the regression coefficients offer a suitable alternative. Little focus has been given on whether and how to shrink the intercept parameter. Based upon classical studies of separation, we argue that efficiency in estimating regression coefficients may vary with the intercept prior. We adapt alternative prior distributions for the intercept that downweight implausibly extreme regions of the parameter space rendering less sensitivity to separation ...

Perceived Access And Barriers To Care Among Illicit Drug Users And Hazardous Drinkers: Findings From The Seek, Test, Treat, And Retain Data Harmonization Initiative (Sttr)., Mika Matsuzaki, Quan M Vu, Marya Gwadz, Joseph A C Delaney, Irene Kuo, Maria Esther Perez Trejo, William E Cunningham, Chinazo O Cunningham, Katerina Christopoulos

Epidemiology and Biostatistics Faculty Publications

BACKGROUND: Illicit drug use (DU) and hazardous drinking (HD) among marginalized populations may be associated with greater barriers to care.

METHODS: We used baseline data on the participants of the Seek, Test, Treat, and Retain data harmonization initiative. DU includes use of any illicit drugs within the past 6 months. HD was defined as scores ≥8 for men and ≥ 7 for women on Alcohol Use Disorders Identification Test within the past 12 months. Social support scores were assigned by summing scores from individual questions related to social support. Two outcomes for multivariable regression models and mediation analysis were perceived access ...

Multivariate Spectral Analysis Of Crism Data To Characterize The Composition Of Mawrth Vallis, Melissa Luna

Melissa Luna

No abstract provided.

Essentials Of Structural Equation Modeling, Mustafa Emre Civelek

Zea E-Books

Structural Equation Modeling is a statistical method increasingly used in scientific studies in the fields of Social Sciences. It is currently a preferred analysis method, especially in doctoral dissertations and academic researches. However, since many universities do not include this method in the curriculum of undergraduate and graduate courses, students and scholars try to solve the problems they encounter by using various books and internet resources.

This book aims to guide the researcher who wants to use this method in a way that is free from math expressions. It teaches the steps of a research program using structured equality modeling ...

Building A Better Risk Prevention Model, Steven Hornyak

National Youth-At-Risk Conference Savannah

This presentation chronicles the work of Houston County Schools in developing a risk prevention model built on more than ten years of longitudinal student data. In its second year of implementation, Houston At-Risk Profiles (HARP), has proven effective in identifying those students most in need of support and linking them to interventions and supports that lead to improved outcomes and significantly reduces the risk of failure.

Optimal Stratification And Allocation For The June Agricultural Survey, Cigna, Hejian Sang, Zhengyuan Zhu, Stephanie Zimmer

Statistics Publications

A computational approach to optimal multivariate designs with respect to stratification and allocation is investigated under the assumptions of fixed total allocation, known number of strata, and the availability of administrative data correlated with thevariables of interest under coefficient-of-variation constraints. This approach uses a penalized objective function that is optimized by simulated annealing through exchanging sampling units and sample allocations among strata. Computational speed is improved through the use of a computationally efficient machine learning method such as K-means to create an initial stratification close to the optimal stratification. The numeric stability of the algorithm has been investigated and parallel ...

A Spline-Assisted Semiparametric Approach To Nonparametric Measurement Error Models, Fei Jiang, Yanyuan Ma

COBRA Preprint Series

Nonparametric estimation of the probability density function of a random variable measured with error is considered to be a difficult problem, in the sense that depending on the measurement error prop- erty, the estimation rate can be as slow as the logarithm of the sample size. Likewise, nonparametric estimation of the regression function with errors in the covariate suffers the same possibly slow rate. The traditional methods for both problems are based on deconvolution, where the slow convergence rate is caused by the quick convergence to zero of the Fourier transform of the measurement error density, which, unfortunately, appears in ...