Statistics and Probability Commons^™

Collecting, Analyzing And Interpreting Bivariate Data From Leaky Buckets: A Project-Based Learning Unit, Florence Funmilayo Obielodan

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Despite the significance and the emphasis placed on mathematics as a subject and field of study, achieving the right attitude to improve students‟ understanding and performance is still a challenge. Previous studies have shown that the problem cuts across nations around the world, both developing countries and developed alike. Teachers and educators of the subject have responsibilities to continuously develop innovative pedagogical approaches that will enhance students‟ interests and performance. Teaching approaches that emphasize real life applications of the subject have become imperative. It is believed that this will stimulate learners‟ interest in the subject as they will be able …

Climate Change And Community Dynamics: A Hierarchical Bayesian Model Of Resource-Driven Changes In A Desert Rodent Community, Glenda M. Yenni

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Predicting effects of climate change on species persistence often assumes that those species are responding to abiotic effects alone. However, biotic interactions between community members may affect species’ ability to respond to abiotic changes. Latent Gaussian models of resource availability using precipitation and NDVI and accounting for spatial autocorrelation and rodent group-level uncertainty in the process are developed to detect differences in seasons, groups, and the experimental removal of one group. Precipitation and NDVI have overall positive effects on rodent energy use as expected, but meaningful differences were detected. Differences in the importance of seasonality when the dominant group was …

Controlling Error Rates With Multiple Positively-Dependent Tests, Abdullah Al Masud

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

It is a typical feature of high dimensional data analysis, for example a microarray study, that a researcher allows thousands of statistical tests at a time. All inferences for the tests are determined using the p-values; a smaller p-value than the α-level of the test signifies a statistically significant test. As the number of tests increases, the chance of observing some small p-values is very high even when all null hypotheses are true. Consequently, we make wrong conclusions on the hypotheses. This type of potential problem frequently happens when we test several hypotheses simultaneously, i.e., the multiple testing problem. …

Putting Artists On The Map: A Five Part Study Of Greater Cleveland Artists' Location Decisions - Part 4: Predictive Analysis - Regression Modeling, Mark Salling, Gregory Soltis, Charles Post, Sharon Bliss, Ellen Cyran

All Maxine Goodman Levin School of Urban Affairs Publications

A series of reports detailing the residential and work space location preferences of Cuyahoga county's artists.

Evaluation Of Flexible Regression For Non-Unimodal Hazard Functions, Marco Fornili, Patrizia Boracchi, Federico Ambrogi, Elia Biganzoli

COBRA Preprint Series

Longer follow-up for various kinds of cancer, particularly breast cancer, has made it possible the observation of complex forms of the hazard function of occurrence of metastasis and death. In several studies a bimodal hazard function was obtained, with a possible interpretation in the context of tumor dormancy. The shape of the hazard function is usually estimated by spline regression functions. In the case of breast cancer, no general agreement is obtained on the presence of a complex behavior. This may depend on the properties of the smoothing function adopted. We evaluate through simulations of a bimodal hazard function the …

Risk Auto Theft: Predicting Spatial Distributions Of Crime Events, Tana J. Gurule, Tamara D. Madensen

Graduate Research Symposium (2010 - 2017)

Police typically rely on retrospective hotspot maps to informe prevention strategies aimed at reducing future crime. The current study reviews environmental crime theories that help to identify casual factors associated with rish of auto theft. Map layers are created from data that operationalize these risk factors. These layers are combined using spatial analysis techniques to produce a "risk density" map. Analysis of crime data are used to determing wheter our "risk density" map better predicts subsequetnt theft events than a traditional retrospective hotspot map.

Putting Artists On The Map: A Five Part Study Of Greater Cleveland Artists' Location Decisions - Part 3: Attitudinal Analysis - Artist Housing And Space Survey, Mark Salling, Gregory Soltis, Charles Post, Sharon Bliss, Ellen Cyran

All Maxine Goodman Levin School of Urban Affairs Publications

A series of reports detailing the residential and work space location preferences of Cuyahoga county's artists.

Relationship Between Perceived And Actual Quality Of Data Checking, Hunter Speich, Sophia Karas, Dan Erosa, Kelly Grob, Kimberly A. Barchard

Festival of Communities: UG Symposium (Posters)

Data quality is critical to reaching correct research conclusions. Researchers attempt to ensure that they have accurate data by checking the data after it has been entered. Previous research has demonstrated that some methods of data checking are better than others, but not all researchers use the best methods. Perhaps researchers continue to use less optimal data checking methods because they mistakenly believe that they are highly accurate. The purpose of this study was to examine the relationship between perceived data quality and actual data quality. A total of 29 participants completed this study. Participants checked that letters and numbers …

Analysis Of Morris Water Maze Data With Bayesian Statistical Methods, Maxym V. Myroshnychenko, Anton Westveld, Jefferson Kinney

Festival of Communities: UG Symposium (Posters)

Neuroscientists commonly use a Morris Water Maze to assess learning in rodents. In his kind of a maze, the subjects learn to swim toward a platform hidden in opaque water as they orient themselves according to the cues on the walls. This protocol presents a challenge to statistical analysis, because an artificial cut-off must be set for those experimental subjects that do not reach the platform so as they do not drown from exhaustion. This fact leads to the data being right censored. In our experimental data, which compares learning in rodents that have chemically induced symptoms of schizophrenia to …

Unlv Enrollment Forecasting, Sabrina Beckman, Stefan Cline, Monika Neda

Festival of Communities: UG Symposium (Posters)

Our project investigates the future enrollment of undergraduates at UNLV in the entire university, the College of Science, and the Department of Mathematical Sciences. The method used for the forecast, is the well-known least-squares method, for which a mathematical description will be presented. Studies for the numerical error are pursued too. The study will include graphs that describe the past and future behavior for different parameter settings. Mathematical results obtained show that the university will continue to grow given the current trends of enrollment.

A New Perspective On Visual Word Processing Efficiency, Joseph W. Houpt, James T. Townsend

Psychology Faculty Publications

No abstract provided.

A General Implementation Of Tmle For Longitudinal Data Applied To Causal Inference In Survival Analysis, Ori M. Stitelman, Victor De Gruttola, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

In many randomized controlled trials the outcome of interest is a time to event, and one measures on each subject baseline covariates and time-dependent covariates until the subject either drops-out, the time to event is observed, or the end of study is reached. The goal of such a study is to assess the causal effect of the treatment on the survival curve. Standard methods (e.g., Kaplan-Meier estimator, Cox-proportional hazards) ignore the available baseline and time-dependent covariates, and are therefore biased if the drop-out is affected by these covariates, and are always inefficient. We present a targeted maximum likelihood estimator of …

A Rank-Based Estimate For Cell Lineage Data, Tamer M. Elbayoumi, Jeffrey Terpstra

Research and Creative Activities Poster Day

The presence of aberrant observations (i.e. outliers) in cell lineage data is quite common. As such, it is desirable to have an outlier-resistant estimation procedure as an alternative to least squares estimation (maximum likelihood estimation under normality). In this work, we consider rankbased estimates of the parameters of a first order bifurcating autoregressive [BAR(1)] model. The BAR(1) model was proposed by Cowan and Staudte (1986) for cell lineage data. In it, each line of descendents follows a first order autoregressive [AR(1)] model and allows sister cells from the same mother to be correlated. Real examples and a simulation study are …

Multiple Solutions For An Elliptic Problem Related To Vortex Pairs, Yi Li, Shuangjie Peng

Mathematics and Statistics Faculty Publications

Let Ω be a bounded domain in RN (N⩾2), φ a harmonic function in Ω¯. In this paper we study the existence of solutions to the following problem arising in the study of vortex pairs(Pλ){−Δu=λ(u−φ)+p−1,x∈Ω,u=0,x∈∂Ω. The set Ωp={x∈Ω,u(x)>φ} is called “vortex core”. Existence of solutions whose “vortex core” consists of one component and asymptotic behavior of “vortex core” were studied by many authors for large λ recently. Under the condition that φ has k strictly local minimum points on the boundary ∂Ω, we obtain in this paper that for λ large enough, (Pλ) has a solution with “vortex core” …

A Broad Symmetry Criterion For Nonparametric Validity Of Parametrically-Based Tests In Randomized Trials, Russell T. Shinohara, Constantine E. Frangakis, Constantine G.. Lyketos

Johns Hopkins University, Dept. of Biostatistics Working Papers

Summary. Pilot phases of a randomized clinical trial often suggest that a parametric model may be an accurate description of the trial's longitudinal trajectories. However, parametric models are often not used for fear that they may invalidate tests of null hypotheses of equality between the experimental groups. Existing work has shown that when, for some types of data, certain parametric models are used, the validity for testing the null is preserved even if the parametric models are incorrect. Here, we provide a broader and easier to check characterization of parametric models that can be used to (a) preserve nonparametric validity …

Prospective K-8 Teachers’ Knowledge Of Relational Thinking, Marta Magiera, Leigh A. Van Den Kieboom, John Moyer

Mathematics, Statistics and Computer Science Faculty Research and Publications

The goal of this study was to examine two issues: First, pre-service teachers’ ability and inclination to think relationally prior to instruction about the role relational thinking plays in the K-8 mathematics curriculum. Second, to examine task specific variables possibly associated with pre-service teachers’ inclination to engage in relational thinking. The results revealed that preservice teachers engage in relational thinking about equality, however, their inclination to do so is rather limited. Furthermore, they tend to engage in relational thinking more frequently in the context of arithmetic than algebra-related tasks. Pre-service teachers’ inclination to engage in relational thinking appeared to also …

Targeted Minimum Loss Based Estimator That Outperforms A Given Estimator, Susan Gruber, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Targeted minimum loss based estimation (TMLE) provides a template for the construction of semiparametric locally efficient double robust substitution estimators of the target parameter of the data generating distribution in a semiparametric censored data or causal inference model (van der Laan and Rubin (2006),van der Laan (2008), van der Laan and Rose (2011)). In this article we demonstrate how to construct a TMLE that also satisfies the property that it is at least as efficient as a user supplied asymptotically linear estimator. For the sake of illustration we focus on estimation of the additive average causal effect of a point …

Examining The Student Investment Roundtable's Funds, David Hernandez, Uriel Luna

Undergraduate Research Conference

To what extent are the factors of the Fama-French-Factor Asset Pricing Model related to rates of returns of the Stephen F. Austin State University Student Investment Roundtable Fund?

The Fama-French Model is believed to be a major improvement over the ever-popular Capital Asset Pricing Model, CAPM. The Capital Asset Pricing Model uses a single factor beta to compare the excess returns of a portfolio with the excess returns of the market as a whole, but is said to oversimplify the complex market. On the other hand, the Fama-French Model three-factor adds additional factors to the original CAPM equation. The Fama-French …

The Relative Performance Of Targeted Maximum Likelihood Estimators, Kristin E. Porter, Susan Gruber, Mark J. Van Der Laan, Jasjeet S. Sekhon

U.C. Berkeley Division of Biostatistics Working Paper Series

There is an active debate in the literature on censored data about the relative performance of model based maximum likelihood estimators, IPCW-estimators, and a variety of double robust semiparametric efficient estimators. Kang and Schafer (2007) demonstrate the fragility of double robust and IPCW-estimators in a simulation study with positivity violations. They focus on a simple missing data problem with covariates where one desires to estimate the mean of an outcome that is subject to missingness. Responses by Robins et al. (2007), Tsiatis and Davidian (2007), Tan (2007a) and Ridgeway and McCaffrey (2007) further explore the challenges faced by double robust …

Estimation And Testing In Targeted Group Sequential Covariate-Adjusted Randomized Clinical Trials, Antoine Chambaz, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

This article is devoted to the construction and asymptotic study of adaptive group sequential covariate-adjusted randomized clinical trials analyzed through the prism of the semiparametric methodology of targeted maximum likelihood estimation (TMLE). We show how to build, as the data accrue group-sequentially, a sampling design which targets a user-supplied optimal design. We also show how to carry out a sound TMLE statistical inference based on such an adaptive sampling scheme (therefore extending some results known in the i.i.d setting only so far), and how group-sequential testing applies on top of it. The procedure is robust (i.e., consistent even if the …