Statistics and Probability Commons^™

Session 1-3-E: Hitting The Sweet Spot: Lottery Promotion And Vulnerability, Elisabeth Papineau, Jean-François Biron, Fanny Lemetayer, Amadou Barry

International Conference on Gambling & Risk Taking

Literature about lottery marketing and vulnerability

Lottery advertising in Quebec

Project phases

Results

Conclusion

Session 1-3-F: The Victorian Gambling Study Identifying And Predicting Risks, Rosa Billi

International Conference on Gambling & Risk Taking

Overview

Background

Study design

• Incidence
• Transitions
• Risk & protective
• Co morbidities

Session 1-2-F: Sports As An Alternative Asset Class: Gambling As An Investment, Brendan Poots

International Conference on Gambling & Risk Taking

Genesis of the idea came in 2007 in NYC when studying at Columbia. The trading of sports utilising strategies and other traditional financial market practices was identified as a burgeoning opportunity.

Towards the end of 2007 a private Fund with owner’s capital was started.

Global Financial Crisis in 2008 – all asset classes lost value. Diversification did not work. The Olympics, the Superbowl, the World Series and all the Grand Slam tennis and golf tournaments went ahead unaffected.

Priomha Capital Sports Hedge Fund Founded in 2010

Global HQ – Melbourne

Trading office – London & Las Vegas (2014)

Priomha Capital …

Session 1-2-F: Rationality And Risk Intelligence In Binary Betting, Raph Di Guisto, Aaron C. Brown, Nick Maughan

International Conference on Gambling & Risk Taking

We analyze 1.6 million binary bets on financial markets totaling $600 million in stakes, placed by 21,000 bettors at a large Internet betting site. The data set is unusually large and complete, plus has one additional important advantage: we can obtain objective independent estimates of the ex ante probability of winning each bet, using data from financial markets. This allows us to distinguish bettor profit due to superior prediction of financial events from bettor profit due to exploiting ex ante favorable odds situations. We focus on the degree or type of skill possessed by bettors (if any), and the amount …

Session 1-2-A: A Comparison Of Outcome Efficacy Between Residential And Intensive Outpatient Treatment For Disordered Gambling As Measured By Gamtoms, Reece Middleton

International Conference on Gambling & Risk Taking

Conclusions

Whereas, it is apparent that each of the Programs is clearly efficacious, as evidenced by major improvements in all evaluated life areas for clients of both, it seems that Residential Treatment, for those able to accomplish it, would have the Advantage. It is further indicated that continued involvement in recovery-oriented activity, such as, Aftercare and 12-Step Programs produces sought-after results for all participants.

Session 1-2-A: Building, Maintaining And Evaluating A Statewide Treatment Program For Problem Gambling, Timothy W. Fong

International Conference on Gambling & Risk Taking

Shows how to build, maintain and evaluate programs for problem gambling

Program: The 15th International Conference On Gambling & Risk Taking, University Of Nevada, Las Vegas, University Of Nevada, Reno

International Conference on Gambling & Risk Taking

Listing of presentations, events, and sponsors

A Versatile Test For Equality Of Two Survival Functions Based On Weighted Differences Of Kaplan-Meier Curves, Hajime Uno, Lu Tian, Brian Claggett, L. J. Wei

Harvard University Biostatistics Working Paper Series

With censored event time observations, the logrank test is the most popular tool for testing the equality of two underlying survival distributions. Although this test is asymptotically distribution-free, it may not be powerful when the proportional hazards assumption is violated. Various other novel testing procedures have been proposed, which generally are derived by assuming a class of specific alternative hypotheses with respect to the hazard functions. The test considered by Pepe and Fleming (1989) is based on a linear combination of weighted differences of two Kaplan-Meier curves over time and is a natural tool to assess the difference of two …

Subsemble: An Ensemble Method For Combining Subset-Specific Algorithm Fits, Stephanie Sapp, Mark J. Van Der Laan, John Canny

U.C. Berkeley Division of Biostatistics Working Paper Series

Ensemble methods using the same underlying algorithm trained on different subsets of observations have recently received increased attention as practical prediction tools for massive datasets. We propose Subsemble: a general subset ensemble prediction method, which can be used for small, moderate, or large datasets. Subsemble partitions the full dataset into subsets of observations, fits a specified underlying algorithm on each subset, and uses a clever form of V-fold cross-validation to output a prediction function that combines the subset-specific fits. We give an oracle result that provides a theoretical performance guarantee for Subsemble. Through simulations, we demonstrate that Subsemble can be …

Targeted Maximum Likelihood Estimation For Dynamic And Static Longitudinal Marginal Structural Working Models, Maya L. Petersen, Joshua Schwab, Susan Gruber, Nello Blaser, Michael Schomaker, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

This paper describes a targeted maximum likelihood estimator (TMLE) for the parameters of longitudinal static and dynamic marginal structural models. We consider a longitudinal data structure consisting of baseline covariates, time-dependent intervention nodes, intermediate time-dependent covariates, and a possibly time dependent outcome. The intervention nodes at each time point can include a binary treatment as well as a right-censoring indicator. Given a class of dynamic or static interventions, a marginal structural model is used to model the mean of the intervention specific counterfactual outcome as a function of the intervention, time point, and possibly a subset of baseline covariates. Because …

Varying Index Coefficient Models, Shujie Ma, Peter Xuekun Song

The University of Michigan Department of Biostatistics Working Paper Series

It has been a long history of utilizing interactions in regression analysis to investigate interactive effects of covariates on response variables. In this paper we aim to address two kinds of new challenges resulted from the inclusion of such high-order effects in the regression model for complex data. The first kind arises from a situation where interaction effects of individual covariates are weak but those of combined covariates are strong, and the other kind pertains to the presence of nonlinear interactive effects. Generalizing the single index coefficient regression model (Xia and Li, 1999), we propose a new class of semiparametric …

Modeling A Sensor To Improve Its Efficacy, Nabin K. Malakar, Daniil Gladkov, Kevin H. Knuth

Physics Faculty Scholarship

Robots rely on sensors to provide them with information about their surroundings. However, high-quality sensors can be extremely expensive and cost-prohibitive. Thus many robotic systems must make due with lower-quality sensors. Here we demonstrate via a case study how modeling a sensor can improve its efficacy when employed within a Bayesian inferential framework. As a test bed we employ a robotic arm that is designed to autonomously take its own measurements using an inexpensive LEGO light sensor to estimate the position and radius of a white circle on a black field. The light sensor integrates the light arriving from a …

Balancing Score Adjusted Targeted Minimum Loss-Based Estimation, Samuel D. Lendle, Bruce Fireman, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Adjusting for a balancing score is sufficient for bias reduction when estimating causal effects including the average treatment effect and effect among the treated. Estimators that adjust for the propensity score in a nonparametric way, such as matching on an estimate of the propensity score, can be consistent when the estimated propensity score is not consistent for the true propensity score but converges to some other balancing score. We call this property the balancing score property, and discuss a class of estimators that have this property. We introduce a targeted minimum loss-based estimator (TMLE) for a treatment specific mean with …

Pilot Comparative Effectiveness Study Of Surface Perturbation Treadmill Training To Prevent Falls In Older Adults, Jon D. Lurie, Alexandra B. Zagaria, Dawna M. Pidgeon, Judith L. Forman, Kevin Spratt

Dartmouth Scholarship

Falls are the leading cause of fatal and non-fatal injuries among older adults. Exercise programs appear to reduce fall risk, but the optimal type, frequency, and duration of exercise is unknown. External perturbations such as tripping and slipping are a major contributor to falls, and task-specific perturbation training to enhance dynamic stability has emerged as a promising approach to modifying fall risk. The purpose of this pilot study was 1) to determine the feasibility of conducting a large pragmatic randomized trial comparing a multidimensional exercise program inclusive of the surface perturbation treadmill training (SPTT) to multidimensional exercise alone (Standard PT); …

Optimal Tests Of Treatment Effects For The Overall Population And Two Subpopulations In Randomized Trials, Using Sparse Linear Programming, Michael Rosenblum, Han Liu, En-Hsu Yen

Johns Hopkins University, Dept. of Biostatistics Working Papers

We propose new, optimal methods for analyzing randomized trials, when it is suspected that treatment effects may differ in two predefined subpopulations. Such sub-populations could be defined by a biomarker or risk factor measured at baseline. The goal is to simultaneously learn which subpopulations benefit from an experimental treatment, while providing strong control of the familywise Type I error rate. We formalize this as a multiple testing problem and show it is computationally infeasible to solve using existing techniques. Our solution involves a novel approach, in which we first transform the original multiple testing problem into a large, sparse linear …

Estimating Effects On Rare Outcomes: Knowledge Is Power, Laura B. Balzer, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Many of the secondary outcomes in observational studies and randomized trials are rare. Methods for estimating causal effects and associations with rare outcomes, however, are limited, and this represents a missed opportunity for investigation. In this article, we construct a new targeted minimum loss-based estimator (TMLE) for the effect of an exposure or treatment on a rare outcome. We focus on the causal risk difference and statistical models incorporating bounds on the conditional risk of the outcome, given the exposure and covariates. By construction, the proposed estimator constrains the predicted outcomes to respect this model knowledge. Theoretically, this bounding provides …

Time Scales Integral Inequalities For Superquadratic Functions, Josipa Barić, Rabia Bibi, Martin Bohner, Josip Pečarić

Mathematics and Statistics Faculty Research & Creative Works

In this paper, two different methods of proving Jensen's inequality on time scales for superquadratic functions are demonstrated. Some refinements of classical inequalities on time scales are obtained using properties of superquadratic functions and some known results for isotonic linear functionals. © 2013 The Korean Mathematical Society.

Linking And Retaining Hiv Patients In Care: The Importance Of Provider Attitudes And Behaviors, Manya Magnus, Jane Herwehe, Michelli Murtaza-Rossini, Petera Reine, Damien Cuffie, Deann Gruber, Michael Kaiser

Epidemiology Faculty Publications

Retention in HIV treatment may reduce morbidity and mortality, as well as slow the epidemic. Myriad barriers to retention include stigma, homophobia, structural barriers, transportation, and insurance. The purpose of this study was to evaluate patient perceptions of provider attitudes among HIV-infected persons within a state-wide public hospital system in Louisiana. A convenience sample of patients attending HIV clinics throughout the state participated in an anonymous interview. Factors associated with negative perceptions of care were evaluated in conjunction with a validated stigma measure. Factors associated with having a delayed entry into or break in care were evaluated in conjunction with …

Más-O-Menos: A Simple Sign Averaging Method For Discrimination In Genomic Data Analysis, Sihai Dave Zhao, Giovanni Parmigiani, Curtis Huttenhower, Levi Waldron

Harvard University Biostatistics Working Paper Series

No abstract provided.

An Alternative Approach To Reduce Dimensionality In Data Envelopment Analysis, Grace Lee Ching Yap, Wan Rosmanira Ismail, Zaidi Isa

Journal of Modern Applied Statistical Methods

Principal component analysis reduces dimensionality; however, uncorrelated components imply the existence of variables with weights of opposite signs. This complicates the application in data envelopment analysis. To overcome problems due to signs, a modification to the component axes is proposed and was verified using Monte Carlo simulations.

Robustness Of Dewma Versus Ewma Control Charts To Non-Normal Processes, Saad Saeed Alkahtani

Journal of Modern Applied Statistical Methods

Exponentially weighted moving average (EWMA) and double EWMA (DEWMA) control charts were designed under the normality assumption. This study considers various skewed (Gamma) and symmetric non-normal (t) distributions to examine the effect of non-normality on the average run length (ARL) performance of EWMA and DEWMA. ARL performances were investigated and compared using Monte Carlo simulations. Results show that DEWMA charts can be designed to be robust to non-normality, that the ARL performances of EWMA and DEWMA charts were more robust to t distributions and DEWMA was more robust to non-normality for larger values of the smoothing parameter.

An Approximate Approach To The Economic Design Of X̅ Charts By Considering The Cost Of Quality, M. A. A. Cox

Journal of Modern Applied Statistical Methods

The selection of three parameters {h,k,n} is necessary to design a x̅ control chart. A cost model employing a Burr distribution is examined. Previously employed methods are refined and extended. A series of approximations are proposed that enable a rapid parameter selection. It is hoped that reducing the computational complexity of previous approaches will lead to wider utilization of x̅ control charts.

Modeling And Handling Overdispersion Health Science Data With Zero-Inflated Poisson Model, Nur Syabiha Binti Zafakali, Wan Muhamad Amir Bin W Ahmad

Journal of Modern Applied Statistical Methods

Health sciences research often involves analyses of repeated measurement or longitudinal count data analyses that exhibit excess zeros. Overdispersion occurs when count data measurements have greater variability than allowed. This phenomenon can be carried over to zero-inflated count data modeling. Referred to as zero-inflation, the Zero-Inflated Poisson (ZIP) model can be used to model such data. The Zero-Inflated Negative Binomial (ZINB) model is used to account for overdispersion detected in count data. The ZINB model is considered as an alternative for the Zero-Inflated Generalized Poisson (ZIGP) model for zero-inflated overdispersed count data. Consequently, zero-inflated models have been proposed for the …

A Note On Α-Curvature Of The Manifolds Of The Length-Biased Lognormal And Gamma Distributions In View Of Related Applications In Data Analysis, Makarand V. Ratnaparkhi, Uttara V. Naik-Nimbalkar

Journal of Modern Applied Statistical Methods

The α-curvature tensors of the statistical manifolds of the length-biased versions of the log-normal and gamma distributions are derived and discussed. This study was designed to investigate observations related to the parameter estimation for the length-biased lognormal distribution as a model for the lengthbiased data from oil field exploration.

The Probit Link Function In Generalized Linear Models For Data Mining Applications, Mehdi Razzaghi

Journal of Modern Applied Statistical Methods

The use of logistic regression for outcome classification of dichotomous variables is well known in data mining applications. The estimated probability of the logit transformation belongs to the class of canonical link functions that follow from particular probability distribution functions. A closely related model is the probit link which can be used for binary responses. Although the probit link is not canonical, in some cases the overall fit of the model can be improved by using non-canonical link functions. This article reviews the properties of the probit link function and discusses its applications in data mining problems. Contrasts and comparisons …

Parameter Estimation Of A Class Of Hidden Markov Model With Diagnostics, E. B. Nkemnole, O. Abass, R. A. Kasumu

Journal of Modern Applied Statistical Methods

A stochastic volatility (SV) problem is formulated as a state space form of a Hidden Markov model (HMM). The SV model assumes that the distribution of asset returns conditional on the latent volatility is normal. This article analyzes the SV model with the student-t distribution and the generalized error distribution (GED) and compares these distributions with a mixture of normal distributions from Kim and Stoffer (2008). A Sequential Monte Carlo with Expectation Maximization (SMCEM) algorithm technique was used to estimate parameters for the extended volatility model; the Akaike Information Criteria (AIC) and forecast statistics were calculated to compare distribution fit. …

Estimation And Testing In Type I Generalized Half Logistic Distribution, R. R. L. Kantam, V. Ramakrishna, M. S. Ravikumar

Journal of Modern Applied Statistical Methods

A generalization of the half logistic distribution is developed through exponentiation of its cumulative distribution function and termed the Type I Generalized Half Logistic Distribution (GHLD). GHLD’s distributional characteristics and parameter estimation using maximum likelihood and modified maximum likelihood methods are presented with comparisons. Comparison of Type I GHLD and the exponential distribution is conducted via likelihood ratio criterion.

P-Values Versus Significance Levels, Phillip I. Good

Journal of Modern Applied Statistical Methods

In this article Phillip Good responds to Richard Anderson's article Conceptual Distinction between the Critical p Value and the Type I Error Rate in Permutation Testing.

Randomization Test P-Values Versus Significance Levels, Bryan Manly

Journal of Modern Applied Statistical Methods

Bryan Manly responds to Richard Anderson's article Conceptual Distinction between the Critical p Value and the Type I Error Rate in Permutation Testing.

Conceptual Distinction Between The Critical P Value And The Type I Error Rate In Permutation Testing: Author Response To Peer Comments, Richard B. Anderson

Journal of Modern Applied Statistical Methods

Richard Anderson responds to comments regarding his target article Conceptual Distinction between the Critical p Value and the Type I Error Rate in Permutation Testing.