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Doubly Robust Estimation Of A Marginal Average Effect Of Treatment On The Treated With An Instrumental Variable, Lan Liu, Wang Miao, Baoluo Sun, James M. Robins, Eric J. Tchetgen Tchetgen 2015 Harvard University

Doubly Robust Estimation Of A Marginal Average Effect Of Treatment On The Treated With An Instrumental Variable, Lan Liu, Wang Miao, Baoluo Sun, James M. Robins, Eric J. Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.


One-Step Targeted Minimum Loss-Based Estimation Based On Universal Least Favorable One-Dimensional Submodels, Mark J. van der Laan 2015 University of California, Berkeley, Division of Biostatistics

One-Step Targeted Minimum Loss-Based Estimation Based On Universal Least Favorable One-Dimensional Submodels, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Consider a study in which one observes n independent and identically distributed random variables whose probability distribution is known to be an element of a particular statistical model, and one is concerned with estimation of a particular real valued pathwise differentiable target parameter of this data probability distribution. The canonical gradient of the pathwise derivative of the target parameter, also called the efficient influence curve, defines an asymptotically efficient estimator as an estimator that is asymptotically linear with influence curve equal to the efficient influence curve.The targeted maximum likelihood estimator is a two stage estimator obtained by constructing a ...


Identification And Doubly Robust Estimation Of Data Missing Not At Random With An Ancillary Variable, Wang Miao, Eric Tchetgen Tchetgen, Zhi Geng 2015 Beijing University

Identification And Doubly Robust Estimation Of Data Missing Not At Random With An Ancillary Variable, Wang Miao, Eric Tchetgen Tchetgen, Zhi Geng

Harvard University Biostatistics Working Paper Series

No abstract provided.


Mathematical Models Of Games Of Chance: Epistemological Taxonomy And Potential In Problem-Gambling Research, Catalin Barboianu 2015 University of Bucharest

Mathematical Models Of Games Of Chance: Epistemological Taxonomy And Potential In Problem-Gambling Research, Catalin Barboianu

UNLV Gaming Research & Review Journal

Games of chance are developed in their physical consumer-ready form on the basis of mathematical models, which stand as the premises of their existence and represent their physical processes. There is a prevalence of statistical and probabilistic models in the interest of all parties involved in the study of gambling – researchers, game producers and operators, and players – while functional models are of interest more to math-inclined players than problem-gambling researchers. In this paper I present a structural analysis of the knowledge attached to mathematical models of games of chance and the act of mathematical modeling, arguing that such non-standard knowledge ...


Extended Followup Of A Cohort Of Chromium Production Workers, Herman Jones Gibb, Peter St. John Lees, Jing Wang, Keri O'Leary 2015 George Washington University

Extended Followup Of A Cohort Of Chromium Production Workers, Herman Jones Gibb, Peter St. John Lees, Jing Wang, Keri O'Leary

Epidemiology and Biostatistics Faculty Publications

No abstract provided.


The Relationship Between Self-Determination And Client Outcomes Among The Homeless, Samuel M. Hanna 2015 California State University - San Bernardino

The Relationship Between Self-Determination And Client Outcomes Among The Homeless, Samuel M. Hanna

Electronic Theses, Projects, and Dissertations

This paper has attempted to determine if there is a significant relationship between self-determination and client outcomes among the homeless. The study has been based upon the conceptual framework set forth in Self-Determination Theory. The purpose of the study was to explore the relationship between self-determination and client outcomes among the homeless. Using a data collection instrument, based on empirically validated instrumentation, clients from several homeless service providers in the City of San Bernardino were assessed for the level of self-determination and autonomy support they experience within these agencies. Outcome measures included such things as whether the client was going ...


Advanced Topics In Experimental Design, Jason Anderson 2015 California Polytechnic State University - San Luis Obispo

Advanced Topics In Experimental Design, Jason Anderson

Statistics

No abstract provided.


A Study Of The Parametric And Nonparametric Linear-Circular Correlation Coefficient, Robin Tu 2015 California Polytechnic State University, San Luis Obispo

A Study Of The Parametric And Nonparametric Linear-Circular Correlation Coefficient, Robin Tu

Statistics

Circular statistics are specialized statistical methods that deal specifically with directional data. Data that is angular require specialized techniques due to the modulo 2π (in radians) or modulo 360 (in degrees) nature of angles.

Correlation, typically in terms of Pearson’s correlation coefficient, is a measure of association between two linear random variables x and y. In this paper, the specific circular technique of the parametric and nonparametric linear-circular correlation coefficient will be explored where correlation is no longer between two linear variables x and y, but between a linear random variable x and circular random variable θ.

A simulation ...


#Twittercritic: Sentiment Analysis Of Tweets To Predict Tv Ratings, Isabel Litton 2015 California Polytechnic State University - San Luis Obispo

#Twittercritic: Sentiment Analysis Of Tweets To Predict Tv Ratings, Isabel Litton

Statistics

Twitter has rapidly become one of the most popular sites of the Internet. It functions not just as a microblogging service, but as a crowdsourcing tool for listening, promotion, insight and much more. From the perspective of TV networks, tweets capture the real time reactions of viewers, making them an ideal indicator of a show’s ratings. This paper predicts Internet Movie Database (IMDB) television ratings by text mining Twitter data.

Tweets for five television shows were downloaded over a period of several months utilizing a SAS macro. Television show data, such as rating, show title, episode title, and more ...


A General Framework For Diagnosing Confounding Of Time-Varying And Other Joint Exposures, John W. Jackson 2015 Harvard University

A General Framework For Diagnosing Confounding Of Time-Varying And Other Joint Exposures, John W. Jackson

Harvard University Biostatistics Working Paper Series

No abstract provided.


Using Spatiotemporal Methods To Fill Gaps In Energy Usage Interval Data, Kristin K. Graves 2015 CUNY Hunter College

Using Spatiotemporal Methods To Fill Gaps In Energy Usage Interval Data, Kristin K. Graves

School of Arts & Sciences Theses

Researchers analyzing spatiotemporal or panel data, which varies both in location and over time, often find that their data has holes or gaps. This thesis explores alternative methods for filling those gaps and also suggests a set of techniques for evaluating those gap-filling methods to determine which works best.


Second Order Inference For The Mean Of A Variable Missing At Random, Ivan Diaz, Marco Carone, Mark J. van der Laan 2015 Johns Hopkins University

Second Order Inference For The Mean Of A Variable Missing At Random, Ivan Diaz, Marco Carone, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

We present a second order estimator of the mean of a variable subject to missingness, under the missing at random assumption. The estimator improves upon existing methods by using an approximate second order expansion of the parameter functional, in addition to the first order expansion employed by standard doubly robust methods. This results in weaker assumptions about the convergence rates necessary to establish consistency, local efficiency, and asymptotic linearity. The general estimation strategy is developed under the targeted minimum loss based estimation (TMLE) framework. We present a simulation comparing the sensitivity of the first and second order estimators to the ...


Predicting Future Years Of Life, Health, And Functional Ability: A Healthy Life Calculator For Older Adults, Paula Diehr, Michael Diehr, Alice M. Arnold, Laura Yee, Michelle C. Odden, Calvin H. Hirsch, Stephen Thielke, Bruce Psaty, W Craig Johnson, Jorge Kizer, Anne B. Newman 2015 University of Washington

Predicting Future Years Of Life, Health, And Functional Ability: A Healthy Life Calculator For Older Adults, Paula Diehr, Michael Diehr, Alice M. Arnold, Laura Yee, Michelle C. Odden, Calvin H. Hirsch, Stephen Thielke, Bruce Psaty, W Craig Johnson, Jorge Kizer, Anne B. Newman

UW Biostatistics Working Paper Series

Abstract

Introduction

Planning for the future would be easier if we knew how long we will live and, more importantly, how many years we will be healthy and able to enjoy it. There are few well-documented aids for predicting our future health. We attempted to meet this need for persons 65 years of age and older.

Methods

Data came from the Cardiovascular Health Study, a large longitudinal study of older adults that began in 1990. Years of life (YOL) were defined by measuring time to death. Years of healthy life (YHL) were defined by an annual question about self-rated health ...


Some Models And Methods For The Analysis Of Observational Data, José A. Ferreira 2015 Department of Statistics, Informatics and Modelling

Some Models And Methods For The Analysis Of Observational Data, José A. Ferreira

COBRA Preprint Series

This article provides a short, concise and essentially self-contained exposition of some of the most important models and methods for the analysis of observational data, and a substantial number of illustrations of their application. Although for the most part our presentation follows P. Rosenbaum’s book, “Observational Studies”, and naturally draws on related literature, it contains original elements and simplifies and generalizes some basic results. The illustrations, based on simulated data, show the methods at work in some detail, highlighting pitfalls and emphasizing certain subjective aspects of the statistical analyses.


Image Segmentation Using Fuzzy-Spatial Taxon Cut, Lauren Barghout 2015 U.C. Berkeley

Image Segmentation Using Fuzzy-Spatial Taxon Cut, Lauren Barghout

MODVIS Workshop

Images convey multiple meanings that depend on the context in which the viewer perceptually organizes the scene. This presents a problem for automated image segmentation, because it adds uncertainty to the process of selecting which objects to include or not include within a segment. I’ll discuss the implementation of a fuzzy-logic-natural-vision-processing engine that solves this problem by assuming the scene architecture prior to processing. The scene architecture, a standardized natural-scene-perception-taxonomy comprised of a hierarchy of nested spatial-taxons. Spatial-taxons are regions (pixel-sets) that are figure-like, in that they are perceived as having a contour, are either `thing-like', or a `group ...


Two Essays In Financial Economics, Kyle J. Putnam 2015 University of New Orleans

Two Essays In Financial Economics, Kyle J. Putnam

University of New Orleans Theses and Dissertations

The following dissertation contains two distinct empirical essays which contribute to the overall field of Financial Economics. Chapter 1, entitled “The Determinants of Dynamic Dependence: An Analysis of Commodity Futures and Equity Markets,” examines the determinants of the dynamic equity-commodity return correlations between five commodity futures sub-sectors (energy, foods and fibers, grains and oilseeds, livestock, and precious metals) and a value-weighted equity market index (S&P 500). The study utilizes the traditional DCC model, as well as three time-varying copulas: (i) the normal copula, (ii) the student’s t copula, and (iii) the rotated-gumbel copula as dependence measures. Subsequently, the ...


A Hierarchical Bayesian Model For The Unmixing Analysis Of Compositional Data Subject To Unit-Sum Constraints, Shiyong Yu 2015 Department of Mathematics

A Hierarchical Bayesian Model For The Unmixing Analysis Of Compositional Data Subject To Unit-Sum Constraints, Shiyong Yu

University of New Orleans Theses and Dissertations

Modeling of compositional data is emerging as an active area in statistics. It is assumed that compositional data represent the convex linear mixing of definite numbers of independent sources usually referred to as end members. A generic problem in practice is to appropriately separate the end members and quantify their fractions from compositional data subject to nonnegative and unit-sum constraints. A number of methods essentially related to polytope expansion have been proposed. However, these deterministic methods have some potential problems.

In this study, a hierarchical Bayesian model was formulated, and the algorithms were coded in MATLABÒ. A test run ...


Video Event Understanding With Pattern Theory, Fillipe Souza, Sudeep Sarkar, Anuj Srivastava, Jingyong Su 2015 University of South Florida

Video Event Understanding With Pattern Theory, Fillipe Souza, Sudeep Sarkar, Anuj Srivastava, Jingyong Su

MODVIS Workshop

We propose a combinatorial approach built on Grenander’s pattern theory to generate semantic interpretations of video events of human activities. The basic units of representations, termed generators, are linked with each other using pairwise connections, termed bonds, that satisfy predefined relations. Different generators are specified for different levels, from (image) features at the bottom level to (human) actions at the highest, providing a rich representation of items in a scene. The resulting configurations of connected generators provide scene interpretations; the inference goal is to parse given video data and generate high-probability configurations. The probabilistic structures are imposed using energies ...


Metacognition: Using Confidence Ratings For Type 2 And Type 1 Roc Curves, S A. Klein 2015 UC Berkeley

Metacognition: Using Confidence Ratings For Type 2 And Type 1 Roc Curves, S A. Klein

MODVIS Workshop

In the past five years there has been a surge of renewed interest in metacognition ("thinking about thinking"). The typical experiment involves a binary judgment followed by a multilevel confidence rating. It is a confusing topic because the rating could be made either on one's confidence in the binary response (standard rating Type 1 ROC) or on one's confidence sorted by whether the response was correct (Type 2 ROC). Both are metacognition. After a few remarks on challenging aspects of the Type 2 approach, I will present some interesting results for Type 1 ROC for both memory and ...


Binocular 3d Motion Perception As Bayesian Inference, Martin Lages, Suzanne Heron 2015 University of Glasgow

Binocular 3d Motion Perception As Bayesian Inference, Martin Lages, Suzanne Heron

MODVIS Workshop

The human visual system encodes monocular motion and binocular disparity input before it is integrated into a single 3D percept. Here we propose a geometric-statistical model of human 3D motion perception that solves the aperture problem in 3D by assuming that (i) velocity constraints arise from inverse projection of local 2D velocity constraints in a binocular viewing geometry, (ii) noise from monocular motion and binocular disparity processing is independent, and (iii) slower motions are more likely to occur than faster ones. In two experiments we found that instantiation of this Bayesian model can explain perceived 3D line motion direction under ...


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