Functional Regression, 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, 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.

Mdc-R-Code, 2014 SelectedWorks

#### Mdc-R-Code, Joseph M. Hilbe

*Joseph M Hilbe*

Modeling Count Data: R code in book provided for use

On The Restricted Mean Survival Time Curve Survival Analysis, 2014 COBRA

#### On The Restricted Mean Survival Time Curve Survival Analysis, Lihui Zhao, Brian Claggett, Lu Tian, Hajime Uno, Marc A. Pfeffer, Scott D. Solomon, Lorenzo Trippa, L. J. Wei

*Harvard University Biostatistics Working Paper Series*

No abstract provided.

Quantifying An Adherence Path-Specific Effect Of Antiretroviral Therapy In The Nigeria Pepfar Program, 2014 COBRA

#### Quantifying An Adherence Path-Specific Effect Of Antiretroviral Therapy In The Nigeria Pepfar Program, Caleb Miles, Ilya Shpitser, Phyllis Kanki, Seema Meloni, Eric J. Tchetgen Tchetgen

*Harvard University Biostatistics Working Paper Series*

No abstract provided.

Top Of The Order: Modeling The Optimal Locations Of Minor League Baseball Teams, 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, 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, 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, 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, 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, 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

*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

*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, 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, 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, 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 *T*2-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, 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, 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, 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, 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 ...