Statistics and Probability Commons^™

On The Three Dimensional Interaction Between Flexible Fibers And Fluid Flow, Bogdan Nita, Ryan Allaire

Department of Mathematics Faculty Scholarship and Creative Works

In this paper we discuss the deformation of a flexible fiber clamped to a spherical body and immersed in a flow of fluid moving with a speed ranging between 0 and 50 cm/s by means of three dimensional numerical simulation developed in COMSOL . The effects of flow speed and initial configuration angle of the fiber relative to the flow are analyzed. A rigorous analysis of the numerical procedure is performed and our code is benchmarked against well established cases. The flow velocity and pressure are used to compute drag forces upon the fiber. Of particular interest is the behavior …

Correlation Of Positron Emission Tomography/Computed Tomography Scan With Smoking, Tumor Size, Stage And Differentiation In Head And Neck Cancer Patients, Jordan L. Pleitz, Partha Sinha, Emily V. Dressler, Rony K. Aouad

Otolaryngology--Head & Neck Surgery Faculty Publications

The goal of this study was to identify associations between positron emission tomography/computed tomography (PET/CT) maximum standardized uptake value (SUVmax) in patients presenting with head and neck squamous cell carcinoma (SCC) with tumor site, size, histologic differentiation, smoking, and diabetes. Charts of patients with oropharyngeal and laryngeal SCC who underwent ¹⁸F-fluorodeoxyglucose PET/CT scans were reviewed between May 2007 and August 2013. Statistical analyses included modeling log-transformed SUVmax values by tumor site, size, histologic differentiation, smoking status, and diabetes using unadjusted linear regressions. Differences were considered statistically significant for P< 0.05. A total of 111 patients (54 with oropharynx and 57 with larynx cancers) were included, 83 men and 28 women with an average age of 57.5 years old. There was a significantly higher pack-year smoking history (P = 0.005) in the larynx cancer group. While tumor …

Longitudinal Measurement And Hierarchical Classification Framework For The Prediction Of Alzheimer's Disease, Meiyan Huang, Wei Yang, Qianjin Feng, Wufan Chen, Michael Weiner, Paul Aisen, Ronald Petersen, Clifford R. Jack Jr., William Jagust, John Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, Andrew Saykin, John Morris, Leslie M. Shaw, Jeffrey Kaye, Joseph Quinn, Lisa Silbert, Betty Lind, Raina Carter, Sara Dolen, Lon S. Schneider, Sonia Pawluczyk, Mauricio Beccera, Liberty Teodoro, Bryan Spann, James Brewer, Helen Vanderswag, Adam Fleisher, Charles D. Smith, Greg A. Jicha, Peter A. Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad

Neurology Faculty Publications

Accurate prediction of Alzheimer’s disease (AD) is important for the early diagnosis and treatment of this condition. Mild cognitive impairment (MCI) is an early stage of AD. Therefore, patients with MCI who are at high risk of fully developing AD should be identified to accurately predict AD. However, the relationship between brain images and AD is difficult to construct because of the complex characteristics of neuroimaging data. To address this problem, we present a longitudinal measurement of MCI brain images and a hierarchical classification method for AD prediction. Longitudinal images obtained from individuals with MCI were investigated to acquire important …

Assessing The Impact Of Retreat Mechanisms In A Simple Antarctic Ice Sheet Model Using Bayesian Calibration, Kelsey L. Ruckert, Gary Shaffer, David Pollard, Yawen Guan, Tony E. Wong, Chris E. Forest, Klaus Keller

Department of Statistics: Faculty Publications

The response of the Antarctic ice sheet (AIS) to changing climate forcings is an important driver of sea-level changes. Anthropogenic climate change may drive a sizeable AIS tipping point response with subsequent increases in coastal flooding risks. Many studies analyzing flood risks use simple models to project the future responses of AIS and its sea-level contributions. These analyses have provided important new insights, but they are often silent on the effects of potentially important processes such as Marine Ice Sheet Instability (MISI) or Marine Ice Cliff Instability (MICI). These approximations can be well justified and result in more parsimonious and …

Quantifying The Totality Of Treatment Effect With Multiple Event-Time Observations In The Presence Of A Terminal Event From A Comparative Clinical Study, Brian Claggett, Lu Tian, Haoda Fu, Scott D. Solomon, L. J. Wei

Harvard University Biostatistics Working Paper Series

To evaluate the totality of one treatment's benefit/risk profile relative to an alternative treatment via a longitudinal comparative clinical study, the timing and occurrence of multiple clinical events are typically collected during the patient's followup. These multiple observations reflect the patient's disease progression/burden over time. The standard practice is to create a composite endpoint from the multiple outcomes, the timing of the occurrence of the first clinical event, to evaluate the treatment via the standard survival analysis techniques. By ignoring all events after the composite outcome, this type of assessment may not be ideal. Various parametric or semi-parametric procedures have …

Real Data Is Messy... And Manageable, Beverly Wood, Carl Clark

Publications

Using real data in an introductory statistics course is a delicate balance between reality and manageability. The internet is awash with data that is useful for students to answer questions of interest to them but it is not always formatted as neatly as textbook data. The ASA's recently endorsed GAISE College Report 2016 points to the plausibility of considering multivariable thinking even if only at a rudimentary level. With both messy and multivariable data in mind, we present some activities/projects and sources for data to give introductory students the opportunity to engage with real data.

Quantifying Similarity In Reliability Surfaces Using The Probability Of Agreement, Nathaniel Stevens, C. M. Anderson-Cook

Mathematics

When separate populations exhibit similar reliability as a function of multiple explanatory variables, combining them into a single population is tempting. This can simplify future predictions and reduce uncertainty associated with estimation. However, combining these populations may introduce bias if the underlying relationships are in fact different. The probability of agreement formally and intuitively quantifies the similarity of estimated reliability surfaces across a two-factor input space. An example from the reliability literature demonstrates the utility of the approach when deciding whether to combine two populations or to keep them as distinct. New graphical summaries provide strategies for visualizing the results.

Tuning Parameter Selection In Cox Proportional Hazards Model With A Diverging Number Of Parameters, Andy Ni, Jianwen Cai

Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series

Regularized variable selection is a powerful tool for identifying the true regression model from a large number of candidates by applying penalties to the objective functions. The penalty functions typically involve a tuning parameter that control the complexity of the selected model. The ability of the regularized variable selection methods to identify the true model critically depends on the correct choice of the tuning parameter. In this study we develop a consistent tuning parameter selection method for regularized Cox's proportional hazards model with a diverging number of parameters. The tuning parameter is selected by minimizing the generalized information criterion. We …

Variance Prior Specification For A Basket Trial Design Using Bayesian Hierarchical Modeling, Kristen Cunanan, Alexia Iasonos, Ronglai Shen, Mithat Gonen

Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series

Background: In the era of targeted therapies, clinical trials in oncology are rapidly evolving, wherein patients from multiple diseases are now enrolled and treated according to their genomic mutation(s). In such trials, known as basket trials, the different disease cohorts form the different baskets for inference. Several approaches have been proposed in the literature to efficiently use information from all baskets while simultaneously screening to find individual baskets where the drug works. Most proposed methods are developed in a Bayesian paradigm that requires specifying a prior distribution for a variance parameter, which controls the degree to which information is shared …

Optimized Variable Selection Via Repeated Data Splitting, Marinela Capanu, Colin B. Begg, Mithat Gonen

Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series

We introduce a new variable selection procedure that repeatedly splits the data into two sets, one for estimation and one for validation, to obtain an empirically optimized threshold which is then used to screen for variables to include in the final model. Simulation results show that the proposed variable selection technique enjoys superior performance compared to candidate methods, being amongst those with the lowest inclusion of noisy predictors while having the highest power to detect the correct model and being unaffected by correlations among the predictors. We illustrate the methods by applying them to a cohort of patients undergoing hepatectomy …

Mediation Analysis For Censored Survival Data Under An Accelerated Failure Time Model, Isabel Fulcher, Eric J. Tchetgen Tchetgen, Paige Williams

Harvard University Biostatistics Working Paper Series

Recent advances in causal mediation analysis have formalized conditions for estimating direct and indirect effects in various contexts. These approaches have been extended to a number of models for survival outcomes including accelerated failure time (AFT) models which are widely used in a broad range of health applications given their intuitive interpretation. In this setting, it has been suggested that under standard assumptions, the “difference” and “product” methods produce equivalent estimates of the indirect effect of exposure on the survival outcome. We formally show that these two methods may produce substantially different estimates in the presence of censoring or truncation, …

Studying The Optimal Scheduling For Controlling Prostate Cancer Under Intermittent Androgen Suppression, Sunil K. Dhar, Hans R. Chaudhry, Bruce G. Bukiet, Zhiming Ji, Nan Gao, Thomas W. Findley

Harvard University Biostatistics Working Paper Series

This retrospective study shows that the majority of patients’ correlations between PSA and Testosterone during the on-treatment period is at least 0.90. Model-based duration calculations to control PSA levels during off-treatment are provided. There are two pairs of models. In one pair, the Generalized Linear Model and Mixed Model are both used to analyze the variability of PSA at the individual patient level by using the variable “Patient ID” as a repeated measure. In the second pair, Patient ID is not used as a repeated measure but additional baseline variables are included to analyze the variability of PSA.

The Pareto-G Extended Weibull Distribution, Oluwaseun Elizabeth Otunuga

Theses, Dissertations and Capstones

In this thesis, the Pareto family of extended Weibull distribution is introduced and discussed extensively. This family consists of the Pareto (Type I) Extended Weibull Distribution or PEW for short, and the Pareto (Type II) Extended Weibull Distribution or otherwise called the Lomax Extended Weibull Distribution or LEW for short. The numbers of the parameters of PEW or LEW depend on the number of parameters for the extended Weibull distribution and type of the Pareto distribution. Some properties of these distributions, such as the hazard rate function, the survival function, moments, skewness, kurtosis, mean deviation and entropies are discussed. The …

Gender Differences In Hiv Care Among Criminal Justice-Involved Persons: Baseline Data From The Care+ Corrections Study., Curt Beckwith, Breana Uhrig Castonguay, Claudia Trezza, Lauri Bazerman, Rudy Patrick, Alice Cates, Halli Olsen, Ann Kurth, Tao Liu, James Peterson, Irene Kuo

Epidemiology Faculty Publications

BACKGROUND: HIV-infected individuals recently released from incarceration have suboptimal linkage and engagement in community HIV care. We conducted a study to evaluate an information and communication technology intervention to increase linkage to community care among HIV-infected persons recently involved in the criminal justice (CJ) system. Baseline characteristics including risk behaviors and HIV care indicators are reported and stratified by gender.

METHODS: We recruited HIV-infected individuals in the District of Columbia jail and persons with a recent history of incarceration through community and street outreach. Participants completed a baseline computer-assisted personal interview regarding HIV care and antiretroviral treatment (ART) adherence, substance …

Use Of National Standards To Monitor Hiv Care And Treatment In A High Prevalence City-Washington, Dc., Amanda D Castel, Arpi Terzian, Rachel Hart, Nabil Rayeed, Mariah M Kalmin, Heather Young, Alan E Greenberg

Epidemiology Faculty Publications

We sought to benchmark the quality of HIV care being received by persons living with HIV in care in Washington, DC and identify individual-level and structural-level differences. Data from the DC Cohort, an observational HIV cohort of persons receiving outpatient care in DC, were used to estimate the Institute of Medicine (IOM) and Department of Health and Human Services (HHS) quality of care measures. Differences in care by demographics and clinic type were assessed using χ2 tests and multivariable regression models. Among 8,047 participants, by HHS standards, 69% of participants were retained in care (RIC), 95% were prescribed antiretroviral therapy …

"It Makes You Feel Like Someone Cares" Acceptability Of A Financial Incentive Intervention For Hiv Viral Suppression In The Hptn 065 (Tlc-Plus) Study., Elizabeth Greene, Allison Pack, Jill Stanton, Victoria Shelus, Elizabeth E Tolley, Jamilah Taylor, Wafaa M El Sadr, Bernard M Branson, Jason Leider, Natella Rakhmanina, Theresa Gamble

Pediatrics Faculty Publications

BACKGROUND: HPTN 065 (TLC-Plus) evaluated the feasibility and effectiveness of providing quarterly $70 gift card financial incentives to HIV-infected patients on antiretroviral therapy (ART) to encourage ART adherence and viral suppression, and represents the largest study to-date of a financial incentive intervention for HIV viral suppression. A post-trial qualitative substudy was undertaken to examine acceptability of the financial incentives among those receiving and implementing the intervention.

METHODS: Between July and October 2013, semi-structured interviews were conducted with 72 patients and 12 investigators from 14 sites; three focus groups were conducted with 12 staff from 10 sites. Qualitative data collection elicited …

Conventional Early Infant Diagnosis In Lesotho From Specimen Collection To Results Usage To Manage Patients: Where Are The Bottlenecks?, Appolinaire Tiam, Michelle M Gill, Heather J Hoffman, Anthony Isavwa, Mafusi Mokone, Matokelo Foso, Jeffrey T Safrit, Lynne M Mofenson, Thorkild Tylleskär, Laura Guay

Epidemiology Faculty Publications

INTRODUCTION: Early infant diagnosis is an important step in identifying children infected with HIV during the perinatal period or in utero. Multiple factors contribute to delayed antiretroviral treatment initiation for HIV-infected children, including delays in the early infant HIV diagnosis cascade.

METHODS: We conducted a retrospective study to evaluate early infant diagnosis turnaround times in Lesotho. Trained staff reviewed records of HIV-exposed infants (aged-6-8 weeks) who received an HIV test during 2011. Study sites were drawn from Highlands, Foothills and Lowlands regions of Lesotho. Central laboratory database data were linked to facility and laboratory register information. Turnaround time geometric means …

A Review Of The Multiple-Sample Tests For The Continuous-Data Type, Dewi Rahardja

Journal of Modern Applied Statistical Methods

For continuous data, various statistical hypotheses testing methods have been extensively discussed in the literature. In this article a review is provided of the multiple-sample continuous-data testing methods. It includes traditional methods, such as the two-sample t-test, Welch ANOVA test, etc., as well as newly-developed ones, such as the various Multiple Comparison Procedure (MCP). A roadmap is provided in a figure or diagram format as to which methods are available in the literature. Additionally, the implementation of these methods in popular statistical software packages such as SAS is also presented. This review will be helpful to determine which continuous-data testing …

Factor Analysis By Limited Scales: Which Factors To Analyze?, Stan Lipovetsky

Journal of Modern Applied Statistical Methods

Factor Analysis (FA) and Principal Component Analysis (PCA) are well-known main tools of the multivariate statistics for data analysis, reduction, and visualization. Commonly, the analysis and interpretation of their solutions is performed for each of several main eigenvectors with variances explaining a big part of the total variability in data. The recommendation is to determine if all the main vectors are really needed in the analysis, or some of them should be skipped if they correspond to the absence of the analyzing features. A simple criterion for identifying redundant vectors of loadings is their negative correlation with the vector of …

Prediction Of Percent Change In Linear Regression By Correlated Variables, Stan Lipovetsky

Journal of Modern Applied Statistical Methods

Multiple linear regression can be applied for predicting an individual value of dependent variable y by the given values of independent variables x. But it is not immediately clear how to estimate percent change in y due to changes in predictors, especially when those are correlated. This work considers several approaches to this problem, including its formulation via predictors adjusted by their correlation structure. Ordinary least squares regression is used, together with Shapley value regression and another model based on solving some system of differential equations. Numerical estimations performed for a real marketing research data demonstrate meaningful results. The considered …