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Log-Linear Model To Assess Socioeconomic And Environmental Factors With Childhood Diarrhea Using Hospital Based Surveillance, Krishnan Rajendran, Thandavarayan Ramamurthy, Sujit Kumar Bhattacharya

Journal of Modern Applied Statistical Methods

Categorical outcomes with environment factors analyzed by log linear model are frequent in the environmental epidemiological literature. Epidemiological and socio-economical factors were obtained on 1,119 children below the age of 5 from Infectious Diseases Hospital (IDH) at the Kolkata, India. Significant associations of diarrhea were observed in the rural areas with family income, father’s occupation as a daily labor, literacy of parents, non-cemented floor and wall constructed of mud, and type of storage (wide mouthed earthen pot). The results of the study with specific Log linear model confirm environmental factors were important implications for childhood diarrhea in the rural community. …

Robust General Linear Models And Graphics Via A User Interface (Web Rglm), Kimberly Crimin, Asheber Abebe, Joseph W. Mckean

Journal of Modern Applied Statistical Methods

Rank-based procedures provide superior estimation and testing techniques when the data deviate from normality or contain gross outliers. However, these robust techniques are rarely incorporated in a nonparametric statistics or methods courses due to the lack of computational tools. One reason for this is the existence of certain unavoidable complexities in the numerical methods due to the absence of a closedform solution for the rank estimation problem. This article introduces a user interface, Web RGLM, which may be used to perform rank-based analyses of linear models across the World Wide Web. These models include simple location problems to complicated ANOVA …

Effect On Recreation Benefit Estimates From Correcting For On-Site Sampling Biases And Heterogeneous Trip Overdispersion In Count Data Recreation Demand Models (Stata), Roberto Martínez-Espiñeira, Joseph M. Hilbe

Journal of Modern Applied Statistical Methods

Correction procedures (STATA commands NBSTRAT and GNBSTRAT) are applied to simultaneously account for zero-truncation, endogenous stratification, and overdispersion, and also consider heterogeneity in the overdispersion parameter. Their effect is shown on welfare estimates from previous studies, confirming that the routines perform the appropriate correction and only when endogenous stratification is expected.

Computing Multivariate Process Capability Indices (Excel), Michele Scagliarini, Raffaele Vermiglio

Journal of Modern Applied Statistical Methods

In manufacturing industry there is growing interest in measures of process capability under multivariate setting. Although there are many statistical packages to assess univariate capability, a current problem with the multivariate measures of capability is the shortage of user friendly software. In this article a Visual Basic program has been developed to realize an Excel spreadsheet that may be used to compute two multivariate measures of capability. The aim of this article is to provide a useful tool for practitioners dealing with multivariate capability assessment problems. The features of the program include easy data entry and clear report format.

Logit Estimation Using Warner’S Randomized Response Model, Zawar Hussain, Javid Shabbir

Journal of Modern Applied Statistical Methods

A modified hidden logit estimation procedure is presented based on Warner (1965) randomized response model. Monte Carlo simulations explore the behavior of this estimator and compare its performance with the ordinary logits estimator. Warner’s model is more protective and less jeopardizing.

Estimation Of Covariance Matrix In Signal Processing When The Noise Covariance Matrix Is Arbitrary, Madhusudan Bhandary

Journal of Modern Applied Statistical Methods

An estimator of the covariance matrix in signal processing is derived when the noise covariance matrix is arbitrary based on the method of maximum likelihood estimation. The estimator is a continuous function of the eigenvalues and eigenvectors of the matrix Σ̂₁^1/2S^∗Σ̂₁^1/2, where S^∗ is the sample covariance matrix of observations consisting of both noise and signals and Σ̂₁ is the estimator of covariance matrix based on observations consisting of noise only. Strong consistency and asymptotic normality of the estimator are briefly discussed.

On The Length Of Nhl Shootouts, W. J. Hurley

Journal of Modern Applied Statistical Methods

When NHL teams are tied after 60 minutes of regulation time and 5 minutes of sudden-death overtime, they go to a shootout to determine who gets the overtime point. Teams alternate shots until a winner is determined. The probability of observing shootouts of various lengths is calculated.

A Study In Rule-Specific Issue Categorization For E-Rulemaking, Claire Cardie, Cynthia R. Farina, Adil Aijaz, Matt Rawding, Stephen Purpura

Cornell Law Faculty Publications

We address the e-rulemaking problem of categorizing public comments according to the issues that they address. In contrast to previous text categorization research in e-rulemaking, and in an attempt to more closely duplicate the comment analysis process in federal agencies, we employ a set of rule-specific categories, each of which corresponds to a significant issue raised in the comments. We describe the creation of a corpus to support this text categorization task and report interannotator agreement results for a group of six annotators. We outline those features of the task and of the e-rulemaking context that engender both a non-traditional …

Nonparametric Heteroscedastic Transformation Regression Models For Skewed Data With An Application To Health Care Costs, Xiao-Hua Zhou, Huazhen Lin, Eric Johnson

UW Biostatistics Working Paper Series

No abstract provided.

On The Optimality Of The Neighbor-Joining Algorithm, Kord Eickmeyer, Peter Huggins, Lior Pachter, Ruriko Yoshida

Statistics Faculty Publications

The popular neighbor-joining (NJ) algorithm used in phylogenetics is a greedy algorithm for finding the balanced minimum evolution (BME) tree associated to a dissimilarity map. From this point of view, NJ is "optimal" when the algorithm outputs the tree which minimizes the balanced minimum evolution criterion. We use the fact that the NJ tree topology and the BME tree topology are determined by polyhedral subdivisions of the spaces of dissimilarity maps R(n2)+ to study the optimality of the neighbor-joining algorithm. In particular, we investigate and compare the polyhedral subdivisions for n ≤ 8. This requires the measurement of volumes of …

Semiparametric Inferential Procedures For Comparing Multivariate Roc Curves With Interaction Terms, Liansheng Tang, Xiao-Hua Zhou

UW Biostatistics Working Paper Series

Multivariate ROC curve models that include an interaction term be- tween biomarker type and false positive rate is important in comparative biomarker studies, because such interaction allows ROC curves of different biomarkers to cross each other. However, there has been limited work in drawing inference for comparing multivariate ROC curves, especially when the interaction terms are present. In this article we derive the asymptotic covariance of three estimators for multivariate ROC models. These covariance estimates have not been readily available in the literature, and bootstrap methods have to be used to obtain co- variance estimates. With the readily available variance …

Matrix Pooling: An Accurate And Cost Effective Testing Algorithm For Detection Of Acute Hiv Infection, Bethany L. Hedt, Marcello Pagano

Harvard University Biostatistics Working Paper Series

No abstract provided.

Semi-Parametric Maximum Likelihood Estimates For Roc Curves Of Continuous-Scale Tests, Xiao-Hua Zhou, Huazhen Lin

UW Biostatistics Working Paper Series

No abstract provided.

A Matrix Pooling Algorithm For Disease Detection, Bethany L. Hedt, Marcello Pagano

Harvard University Biostatistics Working Paper Series

No abstract provided.

The Optimal Weighting Of Pre-Election Polling Data, Gregory K. Johnson

Theses and Dissertations

Pre-election polls are used to test the political landscape and predict election results. The relative weights for the state-level data from the 2006 U.S. senatorial races are considered based on the date on which the polls were conducted. Long- and short-memory weight functions are developed to specify the relative value of historical polling data. An optimal weight function is estimated by minimizing the discrepancy function between estimates from weighted polls and the election outcomes.

Properties Of Monotonic Effects On Directed Acyclic Graphs, Tyler J. Vanderweele, James M. Robins

COBRA Preprint Series

Various relationships are shown hold between monotonic effects and weak monotonic effects and the monotonicity of certain conditional expectations. Counterexamples are provided to show that the results do not hold under less restrictive conditions. Monotonic effects are furthermore used to relate signed edges on a causal directed acyclic graph to qualitative effect modification. The theory is applied to an example concerning the direct effect of smoking on cardiovascular disease controlling for hypercholesterolemia. Monotonicity assumptions are used to construct a test for whether there is a variable that confounds the relationship between the mediator, hypercholesterolemia, and the outcome, cardiovascular disease.

Nonparametric Inference Procedure For Percentiles Of The Random Effect Distribution In Meta Analysis, Rui Wang, Lu Tian, Tianxi Cai, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

A Bayesian Approach To Modeling Associations Between Pulsatile Hormones, Nichole E. Carlson, Timothy D. Johnson, Morton B. Brown

The University of Michigan Department of Biostatistics Working Paper Series

Many hormones are secreted in pulses. The pulsatile relationship between hormones regulates many biological processes. To understand endocrine system regulation, time series of hormone concentrations are collected. The goal is to characterize pulsatile patterns and associations between hormones. Currently each hormone on each subject is fitted univariately. This leads to estimates of the number of pulses and estimates of the amount of hormone secreted; however, when the signal-to-noise ratio is small, pulse detection and parameter estimation remains di±cult with existing approaches. In this paper, we present a bivariate deconvolution model of pulsatile hormone data focusing on incorporating pulsatile associations. Through …

Parametric Non-Mixture Cure Models For Schedule-Finding Of Therapeutic Agents, Thomas M. Braun, Changying A. Liu

The University of Michigan Department of Biostatistics Working Paper Series

We propose a Phase I clinical trial design that seeks to determine the cumulative safety of a series of administrations of a fixed dose of an investigational agent. In contrast to traditional Phase I trials that are designed to solely find the maximum tolerated dose (MTD) of the agent, our design instead identifies a maximum tolerated schedule (MTS) that includes an MTD as well as a vector of recommended administration times. Our model is based upon a non-mixture cure model that constrains the probability of toxicity for all subjects to monotonically increase with both dose and the number of administrations …

Quasigeometric Distributions And Extra Inning Baseball Games, Darren B. Glass, Philip J. Lowry

Math Faculty Publications

Each July, the eyes of baseball fans across the country turn to Major League Baseball’s All-Star Game, gathering the best and most popular players from baseball’s two leagues to play against each other in a single game. In most sports, the All-Star Game is an exhibition played purely for entertainment. Since 2003, the baseball All-Star Game has actually ‘counted’, because the winning league gets home field advantage in the World Series. Just one year before this rule went into effect, there was no winner in the All-Star Game, as both teams ran out of pitchers in the 11th inning and …

Mechanistic Home Range Models And Resource Selection Analysis: A Reconciliation And Unification, Paul R. Moorcroft, Alex Barnett

Dartmouth Scholarship

In the three decades since its introduction, resource selection analysis (RSA) has become a widespread method for analyzing spatial patterns of animal relocations obtained from telemetry studies. Recently, mechanistic home range models have been proposed as an alternative framework for studying patterns of animal space-use. In contrast to RSA models, mechanistic home range models are derived from underlying mechanistic descriptions of individual movement behavior and yield spatially explicit predictions for patterns of animal space-use. In addition, their mechanistic underpinning means that, unlike RSA, mechanistic home range models can also be used to predict changes in space-use following perturbation. In this …

An Impregnable Lightweight Device Discovery (Ildd) Model For The Pervasive Computing Environment Of Enterprise Applications, Munirul H. Haque, Sheikh Iqbal Ahamed

Mathematics, Statistics and Computer Science Faculty Research and Publications

The worldwide use of handheld devices (personal digital assistants, cell phones, etc.) with wireless connectivity will reach 2.6 billion units this year and 4 billion by 2010. More specifically, these handheld devices have become an integral part of industrial applications. These devices form pervasive ad hoc wireless networks that aide in industry applications. However, pervasive computing is susceptible and vulnerable to malicious active and passive snoopers. This is due to the unavoidable interdevice dependency, as well as a common shared medium, very transitory connectivity, and the absence of a fixed trust infrastructure. In order to ensure security and privacy in …

Composite Poisson Models For Goal Scoring, Philip J. Everson, P. Goldsmith-Pinkham

Mathematics & Statistics Faculty Works

Goal scoring in sports such as hockey and soccer is often modeled as a Poisson process. We work with a Poisson model where the mean goals scored by the home team is the sum of parameters for the home team's offense, the road team's defense, and a home advantage. The mean goals for the road team is the sum of parameters for the road team's offense and for the home team's defense. The best teams have a large offensive parameter value and a small defensive parameter value. A level-2 model connects the offensive and defensive parameters for the k teams. …

Caffeine Model Identification For Vigilance Performance Prediction, Chun-Hui Huang

Mechanical & Aerospace Engineering Theses & Dissertations

The pharmacodynamics and pharmacokinetics of caffeine have been well characterized. In this study, a caffeine dynamic model is developed to describe its pharmacodynamic effects on vigilance performance. Validated biomathematical models developed to address both individual and group fatigue and alertness in a non-laboratory setting represent a tremendous commercial opportunity. First, a test data set with caffeine effects isolated from circadian and homeostatic effects is created. Then a modeling approach for input and output effects is developed and different model structures for the caffeine effects are considered. Observer/Kalman filter Identification (OKID) algorithm is proposed and developed to identify the caffeine model …

Stochastic Calculations For Computation Of Radiation Effects And Cell Survivability Under Voltage Pulsing, Madhuri Ganapathiraju

Electrical & Computer Engineering Theses & Dissertations

Statistical computations are an important tool for the analysis of stochastic phenomena and processes that are characterized by variability. Biological systems (e.g., cells, tissues etc.) are perfect examples wherein response to a given external stimulus can be varied and needs to be adequately considered. The Monte Carlo method of analysis has now been recognized as the most effective way of treating stochastic variability.

This thesis uses Monte Carlo based simulations to probe two problems that require the quantification and modeling of effects caused by energy deposition onto biological matter from external sources. One problem involves the probabilistic study of the …

Skill Evaluation In Women's Volleyball, Lindsay W. Florence, Gilbert W. Fellingham, Pat R. Vehrs, Nina P. Mortensen

Faculty Publications

The Brigham Young University Women's Volleyball Team recorded and rated all skills (pass, set, attack, etc.) and recorded rally outcomes (point for BYU, rally continues, point for opponent) for the entire 2006 home volleyball season. Only sequences of events occurring on BYU's side of the net were considered. Events followed one of these general patterns: serve-outcome, pass-set-attack-outcome, or block-dig-set-attack-outcome. These sequences of events were assumed to be first-order Markov chains where the quality of each contact depended only on the quality of the previous contact but not explicitly on contacts further removed in the sequence. We represented these sequences in …

Uncertainty Assessment Of Aircraft Maintenance Times By Using Evidence Theory And Expert Judgment Elicitation, Huseyin Kudak

Engineering Management & Systems Engineering Theses & Dissertations

The goal of this study is to demonstrate the use of the Dempster-Shafer Theory of evidence as a decision aid to predict aircraft maintenance times during wartime operations using expert judgment elicitation. Increased precision in time estimation enables the jet engine aircraft maintenance facility commander to make more accurate decisions for the Air Force's wartime tactical operations allowing the commander to gain a decisive advantage. A questionnaire was designed to elicit judgments from experts in the Aircraft Maintenance Facility (AMF) to investigate maintenance times of the major failure modes (Ignition, Fuel, and Electrical). Results of the expert judgment elicitation were …

Abstracts In High Profile Journals Often Fail To Report Harm, Enrique Bernal-Delgado, Elliot S. Fisher

Dartmouth Scholarship

To describe how frequently harm is reported in the abstract of high impact factor medical journals. We carried out a blinded structured review of a random sample of 363 Randomised Controlled Trials (RCTs) carried out on human beings, and published in high impact factor medical journals in 2003. Main endpoint: 1) Proportion of articles reporting harm in the abstract; and 2) Proportion of articles that reported harm in the abstract when harm was reported in the main body of the article. Analysis: Corrected Prevalence Ratio (cPR) and its exact confidence interval were calculated. Non-conditional logistic regression was used.

Scramjet Fuel Injection Array Optimization Utilizing Mixed Variable Pattern Search With Kriging Surrogates, Bryan Sparkman

Theses and Dissertations

Fuel-air mixing analysis of scramjet aircraft is often performed through ex- perimental research or Computational Fluid Dynamics (cfd) algorithms. Design optimization with these approaches is often impossible under a limited budget due to their high cost per run. This investigation uses jetpen, a known inexpensive analysis tool, to build upon a previous case study of scramjet design optimization. Mixed Variable Pattern Search (mvps) is compared to evolutionary algorithms in the optimization of two scramjet designs. The ¯rst revisits the previously stud- ied approach and compares the quality of mvps to prior results. The second applies mvps to a new scramjet …

Targeted Methods For Biomarker Discovery, The Search For A Standard, Catherine Tuglus, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

More often than not biomarker studies analyze large quantities of variables with complicated and generally unknown correlation structure. There are numerous statistical methods which attempt to unravel these variables and determine the underlying mechanism through identification of causally related biomarkers. Results from these methods are generally difficult to interpret and nearly impossible to compare across studies. The FDA has currently called for a standardization of methods and protocol for biomarker detection. In response, we propose targeted variable importance (tVIM) as a standardized method for biomarker discovery. Through the use of targeted Maximum Likelihood, tVIM provides double robust estimates of variable …