Statistics and Probability Commons^™

Session 1-4-A: Results From The Swedish Longitudinal Gambling Study (Swelogs): Changes Between 1998, 2009, And 2010, Ula Romild, Jessika Svensson

International Conference on Gambling & Risk Taking

Public Health Objectives

1. The overarching aim of Sweden’s national public health policy is to create social conditions that will ensure good health, on equal terms for the entire population.

2. The aim for society’s measures against problem gambling is to reduce harm from exaggerated gambling.

Session 1-4-D: Leading Together: The Evolution Of Responsible Gambling In Canada, Jim Engel, Paul Pellizzari, Paul W. Smith

International Conference on Gambling & Risk Taking

Agenda

Background: Gambling in Canada
Responsible Gambling Framework
The notion of “player sustainability”
Video Lottery Terminals (VLTs)
Internet gambling
Branding RG
Data analytics
Voluntary Self-Exclusion
RG Standards
Leading together: collaboration across jurisdictions

Session 1-4-A: Comparing Longitudinal Studies Of Gambling: Methods & Findin, Rachel A. Volberg

International Conference on Gambling & Risk Taking

What do we know about risk factors for PG?

Vast majority of research carried out on PG risk factors has involved cross-sectional surveys

PG status at a single point in time statistically correlated with behaviors & characteristics assessed at the same time

Cannot resolve the “chicken and egg” problem

• Does PG precede other disorders?
• Do other disorders precede PG?
• Or does one underlying condition account for both?

Session 1-4-A: Pathways Of Gambling Problem Severity: Follow-Up From A General Population Survey, Sylvia Kairouz, Christelle Luce

International Conference on Gambling & Risk Taking

Study objectives

Describe trajectories of change in gambling patterns and problems among a cohort of gamblers;

Model change over time based on life events.

Session 1-4-B: Gambling And Marijuana Use In The Netherlands: Is Legalization The Best Tool For Dealing With "Naughty Habits?", William N. Thompson, Laura K. Thompson

International Conference on Gambling & Risk Taking

In 1976, the Netherlands embraced two policy initiatives which encompassed similar objectives. The policies sought to control “undesired substances” via the process of legalization. One legalization process involved casino gambling. The policies have sometimes led to desired results (the right road), while at other times they have led to undesirable results (the wrong road). Now in 2013, without an observable crossroad or even fork in the road, The Netherlands is poised to deviate from a right road to travel down a wrong road by placing rather severe restrictions upon the operations of “Coffee Houses” which have been “serving” customers measured …

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 …