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Functional Regression, Jeffrey S. Morris 2015 The University of Texas

Functional Regression, Jeffrey S. Morris

Jeffrey S. Morris

Functional data analysis (FDA) involves the analysis of data whose ideal units of observation are functions defined on some continuous domain, and the observed data consist of a sample of functions taken from some population, sampled on a discrete grid. Ramsay and Silverman's 1997 textbook sparked the development of this field, which has accelerated in the past 10 years to become one of the fastest growing areas of statistics, fueled by the growing number of applications yielding this type of data. One unique characteristic of FDA is the need to combine information both across and within functions, which Ramsay ...


Modeling Count Data; Errata And Comments, Joseph M. Hilbe 2014 SelectedWorks

Modeling Count Data; Errata And Comments, Joseph M. Hilbe

Joseph M Hilbe

Modeling Count Data: Errata and Comments PDF. Will be updated on a continuing basis.


Enhanced Precision In The Analysis Of Randomized Trials With Ordinal Outcomes, Iván Díaz, Elizabeth Colantuoni, Michael Rosenblum 2014 COBRA

Enhanced Precision In The Analysis Of Randomized Trials With Ordinal Outcomes, Iván Díaz, Elizabeth Colantuoni, Michael Rosenblum

Johns Hopkins University, Dept. of Biostatistics Working Papers

We present a general method for estimating the effect of a treatment on an ordinal outcome in randomized trials. The method is robust in that it does not rely on the proportional odds assumption. Our estimator leverages information in prognostic baseline variables, and has all of the following properties: (i) it is consistent; (ii) it is locally efficient; (iii) it is guaranteed to match or improve the precision of the standard, unadjusted estimator. To the best of our knowledge, this is the first estimator of the causal relation between a treatment and an ordinal outcome to satisfy these properties. We ...


Applications Of The Wei-Lachin Multivariate One-Sided Test For Multiple Outcomes On Possibly Different Scales, John M. Lachin 2014 Himmelfarb Health Sciences Library, The George Washington University

Applications Of The Wei-Lachin Multivariate One-Sided Test For Multiple Outcomes On Possibly Different Scales, John M. Lachin

GW Biostatistics Center Faculty Publications

Many studies aim to assess whether a therapy has a beneficial effect on multiple outcomes simultaneously relative to a control. Often the joint null hypothesis of no difference for the set of outcomes is tested using separate tests with a correction for multiple tests, or using a multivariate T2-like MANOVA or global test. However, a more powerful test in this case is a multivariate one-sided or one-directional test directed at detecting a simultaneous beneficial treatment effect on each outcome, though not necessarily of the same magnitude. The Wei-Lachin test is a simple 1 df test obtained from a simple ...


Optimal Bayesian Adaptive Trials When Treatment Efficacy Depends On Biomarkers, Yifan Zhang, Lorenzo Trippa, Giovanni Parmigiani 2014 COBRA

Optimal Bayesian Adaptive Trials When Treatment Efficacy Depends On Biomarkers, Yifan Zhang, Lorenzo Trippa, Giovanni Parmigiani

Harvard University Biostatistics Working Paper Series

No abstract provided.


Hiv Testing Implementation In Two Urban Cities: Practice, Policy And Perceived Barriers, Camden J. Hallmark, Jennifer Skillicorn, Thomas P. Giordano, Jessica A. Davila, Marlene McNeese, Nestor Rocha, Avemaria Smith, Stacey Cooper, Amanda D. Castel 2014 Himmelfarb Health Sciences Library, The George Washington University

Hiv Testing Implementation In Two Urban Cities: Practice, Policy And Perceived Barriers, Camden J. Hallmark, Jennifer Skillicorn, Thomas P. Giordano, Jessica A. Davila, Marlene Mcneese, Nestor Rocha, Avemaria Smith, Stacey Cooper, Amanda D. Castel

Epidemiology and Biostatistics Faculty Publications

Background

Although funding has supported the scale up of routine, opt-out HIV testing in the US, variance in implementation mechanisms and barriers in high-burden jurisdictions remains unknown.

Methods

We conducted a survey of health care organizations in Washington, DC and Houston/Harris County to determine number of HIV tests completed in 2011, policy and practices associated with HIV testing, funding mechanisms, and reported barriers to testing in each jurisdiction and to compare results between jurisdictions.

Results

In 2012, 43 Houston and 35 DC HIV-testing organizations participated in the survey. Participants represented 85% of Department of Health-supported testers in DC and ...


Generalized Quantile Treatment Effect, Sergio Venturini, Francesca Dominici, Giovanni Parmigiani 2014 COBRA

Generalized Quantile Treatment Effect, Sergio Venturini, Francesca Dominici, Giovanni Parmigiani

Harvard University Biostatistics Working Paper Series

No abstract provided.


A Bayesian Approach To Joint Modeling Of Menstrual Cycle Length And Fecundity, Kirsten J. Lum, Rajeshwari Sundaram, Germaine M. Buck-Louis, Thomas A. Louis 2014 COBRA

A Bayesian Approach To Joint Modeling Of Menstrual Cycle Length And Fecundity, Kirsten J. Lum, Rajeshwari Sundaram, Germaine M. Buck-Louis, Thomas A. Louis

Johns Hopkins University, Dept. of Biostatistics Working Papers

Female menstrual cycle length is thought to play an important role in couple fecundity, or the biologic capacity for reproduction irrespective of pregnancy intentions. A complete assessment of the association between menstrual cycle length and fecundity requires a model that accounts for multiple risk factors (both male and female) and the couple's intercourse pattern relative to ovulation. We employ a Bayesian joint model consisting of a mixed effects accelerated failure time model for longitudinal menstrual cycle lengths and a hierarchical model for the conditional probability of pregnancy in a menstrual cycle given no pregnancy in previous cycles of trying ...


Applying Multiple Imputation For External Calibration To Propensty Score Analysis, Yenny Webb-Vargas, Kara E. Rudolph, D. Lenis, Peter Murakami, Elizabeth A. Stuart 2014 COBRA

Applying Multiple Imputation For External Calibration To Propensty Score Analysis, Yenny Webb-Vargas, Kara E. Rudolph, D. Lenis, Peter Murakami, Elizabeth A. Stuart

Johns Hopkins University, Dept. of Biostatistics Working Papers

Although covariate measurement error is likely the norm rather than the exception, methods for handling covariate measurement error in propensity score methods have not been widely investigated. We consider a multiple imputation-based approach that uses an external calibration sample with information on the true and mismeasured covariates, Multiple Imputation for External Calibration (MI-EC), to correct for the measurement error. We investigate the performance of MI-EC using simulation studies. As expected, a naive method that simply uses the covariate measured with error leads to bias in the treatment effect estimate. Another approach that uses only the joint distribution of the true ...


Spatiotemporal Crime Analysis, James Q. Tay, Abish Malik, Sherry Towers, David Ebert 2014 Purdue University

Spatiotemporal Crime Analysis, James Q. Tay, Abish Malik, Sherry Towers, David Ebert

The Summer Undergraduate Research Fellowship (SURF) Symposium

There has been a rise in the use of visual analytic techniques to create interactive predictive environments in a range of different applications. These tools help the user sift through massive amounts of data, presenting most useful results in a visual context and enabling the person to rapidly form proactive strategies. In this paper, we present one such visual analytic environment that uses historical crime data to predict future occurrences of crimes, both geographically and temporally. Due to the complexity of this analysis, it is necessary to find an appropriate statistical method for correlative analysis of spatiotemporal data, as well ...


Stochastic Variation In Network Epidemic Models: Implications For The Design Of Community Level Hiv Prevention Trials, David Boren, Patrick Sullivan, Chris Beyrer, Stefan Baral, Linda-Gail Becker, Ron Brookmeyer 2014 SelectedWorks

Stochastic Variation In Network Epidemic Models: Implications For The Design Of Community Level Hiv Prevention Trials, David Boren, Patrick Sullivan, Chris Beyrer, Stefan Baral, Linda-Gail Becker, Ron Brookmeyer

Ron Brookmeyer

Important sources of variation in the spread of HIV in communities arise from overlapping sexual networks and heterogeneity in biological and behavioral risk factors in populations. These sources of variation are not routinely accounted for in the design of HIV prevention trials. In this paper, we use agent based models to account for these sources of variation. We illustrate the approach with an agent based model for the spread of HIV infection among men who have sex with men (MSM) in South Africa. We find that traditional sample size approaches that rely on binomial (or Poisson) models are inadequate and ...


Using Graphs To Characterize Nationwide Physician Referral Networks, Ding Tong, Shu-Xia Li, Isuru Ranasinghe, Sudhakar Nuti, Hongyu Zhao, Harlan Krumholz 2014 Yale University

Using Graphs To Characterize Nationwide Physician Referral Networks, Ding Tong, Shu-Xia Li, Isuru Ranasinghe, Sudhakar Nuti, Hongyu Zhao, Harlan Krumholz

Yale Day of Data

AIM:

Evaluating physician referral network characteristics can help to understand how physicians and hospitals interact to provide patient services within the US healthcare system and ultimately how this may influence patient outcomes.

METHOD:

We used the 2012-2013 national Physician Referral data from the Centers for Medicare & Medicaid Services (CMS), which consists of 73,071,804 pairs of referrals from one health provider to another in calendar year 2012 and the first two quarters of year 2013 within 30 days of care. These referrals are from 642,144 national-wide physicians and 4,811 hospitals. We obtained information for each provider, physician ...


Stratified Meta-Analysis To Examine Data Biases In Lung Cancer Studies Of Refinery Workers, Sherman Selix 2014 Yale University

Stratified Meta-Analysis To Examine Data Biases In Lung Cancer Studies Of Refinery Workers, Sherman Selix

Yale Day of Data

Petroleum refineries employ a variety of workers who historically experienced different potentials for asbestos exposure depending on job tasks. Associations between petroleum refinery work and lung cancer related to occupational asbestos exposure have been quantified among various locations, corporations, and time periods. To combine the data from several individual refinery studies and examine an overall effect, a systematic review and stratified meta-analysis was employed. Using set search terms among four databases, 112 potential publications were identified, of which 29 qualified for meta-analysis. Risk estimates and confidence intervals were extracted from these publications to construct four separate datasets. Inverse variance weighting ...


Online Targeted Learning, Mark J. van der Laan, Samuel D. Lendle 2014 COBRA

Online Targeted Learning, Mark J. Van Der Laan, Samuel D. Lendle

U.C. Berkeley Division of Biostatistics Working Paper Series

We consider the case that the data comes in sequentially and can be viewed as sample of independent and identically distributed observations from a fixed data generating distribution. The goal is to estimate a particular path wise target parameter of this data generating distribution that is known to be an element of a particular semi-parametric statistical model. We want our estimator to be asymptotically efficient, but we also want that our estimator can be calculated by updating the current estimator based on the new block of data without having to revisit the past data, so that it is computationally much ...


Estimation Of The Overall Treatment Effect In The Presence Of Interference In Cluster-Randomized Trials Of Infectious Disease Prevention, Nicole Bohme Carnegie, Rui Wang, Victor De Gruttola 2014 COBRA

Estimation Of The Overall Treatment Effect In The Presence Of Interference In Cluster-Randomized Trials Of Infectious Disease Prevention, Nicole Bohme Carnegie, Rui Wang, Victor De Gruttola

Harvard University Biostatistics Working Paper Series

No abstract provided.


Computational Methods For Historical Research On Wikipedia’S Archives, Jonathan Cohen 2014 Chapman University

Computational Methods For Historical Research On Wikipedia’S Archives, Jonathan Cohen

e-Research: A Journal of Undergraduate Work

This paper presents a novel study of geographic information implicit in the English Wikipedia archive. This project demonstrates a method to extract data from the archive with data mining, map the global distribution of Wikipedia editors through geocoding in GIS, and proceed with a spatial analysis of Wikipedia use in metropolitan cities.


Cox Regression Models With Functional Covariates For Survival Data, Jonathan E. Gellar, Elizabeth Colantuoni, Dale M. Needham, Ciprian M. Crainiceanu 2014 COBRA

Cox Regression Models With Functional Covariates For Survival Data, Jonathan E. Gellar, Elizabeth Colantuoni, Dale M. Needham, Ciprian M. Crainiceanu

Johns Hopkins University, Dept. of Biostatistics Working Papers

We extend the Cox proportional hazards model to cases when the exposure is a densely sampled functional process, measured at baseline. The fundamental idea is to combine penalized signal regression with methods developed for mixed effects proportional hazards models. The model is fit by maximizing the penalized partial likelihood, with smoothing parameters estimated by a likelihood-based criterion such as AIC or EPIC. The model may be extended to allow for multiple functional predictors, time varying coefficients, and missing or unequally-spaced data. Methods were inspired by and applied to a study of the association between time to death after hospital discharge ...


Targeted Learning Of An Optimal Dynamic Treatment, And Statistical Inference For Its Mean Outcome, Mark J. van der Laan, Alexander R. Luedtke 2014 COBRA

Targeted Learning Of An Optimal Dynamic Treatment, And Statistical Inference For Its Mean Outcome, Mark J. Van Der Laan, Alexander R. Luedtke

U.C. Berkeley Division of Biostatistics Working Paper Series

Suppose we observe n independent and identically distributed observations of a time-dependent random variable consisting of baseline covariates, initial treatment and censoring indicator, intermediate covariates, subsequent treatment and censoring indicator, and a final outcome. For example, this could be data generated by a sequentially randomized controlled trial, where subjects are sequentially randomized to a first line and second line treatment, possibly assigned in response to an intermediate biomarker, and are subject to right-censoring. In this article we consider estimation of an optimal dynamic multiple time-point treatment rule defined as the rule that maximizes the mean outcome under the dynamic treatment ...


Comparing Partial Least Square Approaches In Gene-Or Region-Based Association Study For Multiple Quantitative Phenotypes, Zhongshang Yuan, Xiaoshuai Zhang, Fangyu Li, Jinghua Zhao, Fuzhong Xue 2014 Wayne State University

Comparing Partial Least Square Approaches In Gene-Or Region-Based Association Study For Multiple Quantitative Phenotypes, Zhongshang Yuan, Xiaoshuai Zhang, Fangyu Li, Jinghua Zhao, Fuzhong Xue

Human Biology Open Access Pre-Prints

On thinking quantitatively of complex diseases, there are at least three statistical strategies for association study: single SNP on single trait, gene-or region (with multiple SNPs) on single trait and on multiple traits. The third of which is the most general in dissecting the genetic mechanism underlying complex diseases underpinning multiple quantitative traits. Gene-or region association methods based on partial least square (PLS) approaches have been shown to have apparent power advantage. However, few attempts are developed for multiple quantitative phenotypes or traits underlying a condition or disease, and the performance of various PLS approaches used in association study for ...


Inferences In Log-Rate Models, Herbert C. Heien, William A. Baumann 2014 Minnesota State University, Mankato

Inferences In Log-Rate Models, Herbert C. Heien, William A. Baumann

Journal of Undergraduate Research at Minnesota State University, Mankato

Log-Rate models are used in analyzing rates of individuals who are exposed to a risk of having a certain characteristic. The explanatory variables could be categorical or in a continuous scale. In finding a Log-Rate Model, parameters are estimated and goodness-of-fit are studied to carefully extract the best model to fit our data. Here we revisit three aspects of Log-Rate Models using the data set give at the end of the paper. The three aspects are parameter estimation, goodness-of-fit of the model, and marginal effect of the factors.


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