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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.


Top Of The Order: Modeling The Optimal Locations Of Minor League Baseball Teams, W. Coleman Conley 2014 Illinois Wesleyan University

Top Of The Order: Modeling The Optimal Locations Of Minor League Baseball Teams, W. Coleman Conley

Undergraduate Economic Review

Over the last twenty-five years, minor league baseball franchises have defined firm mobility. Revisiting the work of Michael C. Davis (2006), I construct a logistic regression model to predict which cities house minor league baseball teams. Six variables are tested for inclusion in the model, including population, income level, the number of major-league professional sports teams in a city, five-year population change, and distance from the closest professional team. Based on the model's predicted probabilities, cities are ranked in order of highest probability of having a team at each of the different levels from Class A to Class AAA.


Negative Binomial Regerssion, 2nd Ed, 2nd Print, Errata And Comments, Joseph Hilbe 2014 SelectedWorks

Negative Binomial Regerssion, 2nd Ed, 2nd Print, Errata And Comments, Joseph Hilbe

Joseph M Hilbe

Errata and Comments for 2nd printing of NBR2, 2nd edition. Previous errata from first printing all corrected. Some added and new text as well.


Constrained Bayesian Estimation Of Inverse Probability Weights For Nonmonotone Missing Data, BaoLuo Sun, Eric J. Tchetgen Tchetgen 2014 COBRA

Constrained Bayesian Estimation Of Inverse Probability Weights For Nonmonotone Missing Data, Baoluo Sun, Eric J. Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.


Should We Love Or Hate Big Data? The Good, The Bad, And The Ugly, Dennis Crossen M.Sc., MBA, Karti Puranam PhD, Madjid Tavana PhD 2014 La Salle University

Should We Love Or Hate Big Data? The Good, The Bad, And The Ugly, Dennis Crossen M.Sc., Mba, Karti Puranam Phd, Madjid Tavana Phd

Explorer Café

No abstract provided.


Testing Gene-Environment Interactions In The Presence Of Measurement Error, Chongzhi Di, Li Hsu, Charles Kooperberg, Alex Reiner, Ross Prentice 2014 COBRA

Testing Gene-Environment Interactions In The Presence Of Measurement Error, Chongzhi Di, Li Hsu, Charles Kooperberg, Alex Reiner, Ross Prentice

UW Biostatistics Working Paper Series

Complex diseases result from an interplay between genetic and environmental risk factors, and it is of great interest to study the gene-environment interaction (GxE) to understand the etiology of complex diseases. Recent developments in genetics field allows one to study GxE systematically. However, one difficulty with GxE arises from the fact that environmental exposures are often measured with error. In this paper, we focus on testing GxE when the environmental exposure E is subject to measurement error. Surprisingly, contrast to the well-established results that the naive test ignoring measurement error is valid in testing the main effects, we find that ...


Personalized Evaluation Of Biomarker Value: A Cost-Benefit Perspective, Ying Huang, Eric Laber 2014 COBRA

Personalized Evaluation Of Biomarker Value: A Cost-Benefit Perspective, Ying Huang, Eric Laber

UW Biostatistics Working Paper Series

For a patient who is facing a treatment decision, the added value of information provided by a biomarker depends on the individual patient’s expected response to treatment with and without the biomarker, as well as his/her tolerance of disease and treatment harm. However, individualized estimators of the value of a biomarker are lacking. We propose a new graphical tool named the subject-specific expected benefit curve for quantifying the personalized value of a biomarker in aiding a treatment decision. We develop semiparametric estimators for two general settings: i) when biomarker data are available from a randomized trial; and ii ...


Cross-Design Synthesis For Extending The Applicability Of Trial Evidence When Treatment Effect Is Heterogeneous-I. Methodology, Ravi Varadhan, Carlos Weiss 2014 COBRA

Cross-Design Synthesis For Extending The Applicability Of Trial Evidence When Treatment Effect Is Heterogeneous-I. Methodology, Ravi Varadhan, Carlos Weiss

Johns Hopkins University, Dept. of Biostatistics Working Papers

Randomized controlled trials (RCTs) provide reliable evidence for approval of new treatments, informing clinical practice, and coverage decisions. The participants in RCTs are often not a representative sample of the larger at-risk population. Hence it is argued that the average treatment effect from the trial is not generalizable to the larger at-risk population. An essential premise of this argument is that there is significant heterogeneity in the treatment effect (HTE). We present a new method to extrapolate the treatment effect from a trial to a target group that is inadequately represented in the trial, when HTE is present. Our method ...


Cross-Design Synthesis For Extending The Applicability Of Trial Evidence When Treatment Effect Is Heterogeneous. Part Ii. Application And External Validation, Carlos Weiss, Ravi Varadhan 2014 COBRA

Cross-Design Synthesis For Extending The Applicability Of Trial Evidence When Treatment Effect Is Heterogeneous. Part Ii. Application And External Validation, Carlos Weiss, Ravi Varadhan

Johns Hopkins University, Dept. of Biostatistics Working Papers

Randomized controlled trials (RCTs) generally provide the most reliable evidence. When participants in RCTs are selected with respect to characteristics that are potential treatment effect modifiers, the average treatment effect from the trials may not be applicable to a specific target population. We present a new method to project the treatment effect from a RCT to a target group that is inadequately represented in the trial when there is heterogeneity in the treatment effect (HTE). The method integrates RCT and observational data through cross-design synthesis. An essential component is to identify HTE and a calibration factor for unmeasured confounding for ...


Estimating Effective Connectivity From Fmri Data Using Factor-Based Subspace Autoregressive Models, Chee-Ming Ting PhD, Abd-Krim Seghouane PhD, Sh-Hussain Salleh PhD, Alias M. Noor PhD 2014 SelectedWorks

Estimating Effective Connectivity From Fmri Data Using Factor-Based Subspace Autoregressive Models, Chee-Ming Ting Phd, Abd-Krim Seghouane Phd, Sh-Hussain Salleh Phd, Alias M. Noor Phd

Chee-Ming Ting PhD

We consider the problem of identifying large-scale effective connectivity of brain networks from fMRI data. Standard vector autoregressive (VAR) models fail to estimate reliably networks with large number of nodes. We propose a new method based on factor modeling for reliable and efficient high-dimensional VAR analysis of large networks. We develop a subspace VAR (SVAR) model from a factor model (FM), where observations are driven by a lower-dimensional subspace of common latent factors with an AR dynamics. We consider two variants of principal components (PC) methods that provide consistent estimates for the FM hence the implied SVAR model, even of ...


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 ...


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