Search results for: Peter B. Gilbert

Items from 1 to 20 out of 54 results

article

A semiparametric Cox–Aalen transformation model with censored data

Xi Ning, Yinghao Pan, Yanqing Sun, Peter B. Gilbert

Biometrics > 79 > 4 > 3111 - 3125

We propose a broad class of so‐called Cox–Aalen transformation models that incorporate both multiplicative and additive covariate effects on the baseline hazard function within a transformation. The proposed models provide a highly flexible and versatile class of semiparametric models that include the transformation models and the Cox–Aalen model as special cases. Specifically, it extends the transformation...

article

Nonparametric estimation of the causal effect of a stochastic threshold‐based intervention

Lars van der Laan, Wenbo Zhang, Peter B. Gilbert

Biometrics > 79 > 2 > 1014 - 1028

Identifying a biomarker or treatment‐dose threshold that marks a specified level of risk is an important problem, especially in clinical trials. In view of this goal, we consider a covariate‐adjusted threshold‐based interventional estimand, which happens to equal the binary treatment–specific mean estimand from the causal inference literature obtained by dichotomizing the continuous biomarker or treatment...

article

Semiparametric additive time‐varying coefficients model for longitudinal data with censored time origin

Yanqing Sun, Qiong Shou, Peter B. Gilbert, Fei Heng, more

Biometrics > 79 > 2 > 695 - 710

Statistical analysis of longitudinal data often involves modeling treatment effects on clinically relevant longitudinal biomarkers since an initial event (the time origin). In some studies including preventive HIV vaccine efficacy trials, some participants have biomarkers measured starting at the time origin, whereas others have biomarkers measured starting later with the time origin unknown. The...

article

Estimation of conditional cumulative incidence functions under generalized semiparametric regression models with missing covariates, with application to analysis of biomarker correlates in vaccine trials

Yanqing Sun, Fei Heng, Unkyung Lee, Peter B. Gilbert

Canadian Journal of Statistics > 51 > 1 > 235 - 257

This article presents generalized semiparametric regression models for conditional cumulative incidence functions with competing risks data when covariates are missing by sampling design or happenstance. A doubly robust augmented inverse probability weighted (AIPW) complete‐case approach to estimation and inference is investigated. This approach modifies IPW complete‐case estimating equations by exploiting...

article

Innovative vaccine approaches—a Keystone Symposia report

Jennifer Cable, Rino Rappuoli, Elizabeth J. Klemm, Gagandeep Kang, more

Annals of the New York Academy of Sciences > 1511 > 1 > 59 - 86

The rapid development of COVID‐19 vaccines was the result of decades of research to establish flexible vaccine platforms and understand pathogens with pandemic potential, as well as several novel changes to the vaccine discovery and development processes that partnered industry and governments. And while vaccines offer the potential to drastically improve global health, low‐and‐middle‐income countries...

article

Efficient nonparametric inference on the effects of stochastic interventions under two‐phase sampling, with applications to vaccine efficacy trials

Nima S. Hejazi, Mark J. van der Laan, Holly E. Janes, Peter B. Gilbert, more

Biometrics > 77 > 4 > 1241 - 1253

The advent and subsequent widespread availability of preventive vaccines has altered the course of public health over the past century. Despite this success, effective vaccines to prevent many high‐burden diseases, including human immunodeficiency virus (HIV), have been slow to develop. Vaccine development can be aided by the identification of immune response markers that serve as effective surrogates...

article

Semiparametric regression analysis of partly interval‐censored failure time data with application to an AIDS clinical trial

Qingning Zhou, Yanqing Sun, Peter B. Gilbert

Statistics in Medicine > 40 > 20 > 4376 - 4394

Failure time data subject to various types of censoring commonly arise in epidemiological and biomedical studies. Motivated by an AIDS clinical trial, we consider regression analysis of failure time data that include exact and left‐, interval‐, and/or right‐censored observations, which are often referred to as partly interval‐censored failure time data. We study the effects of potentially time‐dependent...

article

Nonparametric variable importance assessment using machine learning techniques

Brian D. Williamson, Peter B. Gilbert, Marco Carone, Noah Simon

Biometrics > 77 > 1 > 9 - 22

In a regression setting, it is often of interest to quantify the importance of various features in predicting the response. Commonly, the variable importance measure used is determined by the regression technique employed. For this reason, practitioners often only resort to one of a few regression techniques for which a variable importance measure is naturally defined. Unfortunately, these regression...

article

Rejoinder to “Nonparametric variable importance assessment using machine learning techniques”

Brian D. Williamson, Peter B. Gilbert, Marco Carone, Noah Simon

Biometrics > 77 > 1 > 28 - 30

article

A regularized estimation approach for case‐cohort periodic follow‐up studies with an application to HIV vaccine trials

Hui Zhao, Qiwei Wu, Peter B. Gilbert, Ying Q. Chen, more

Biometrical Journal > 62 > 5 > 1176 - 1191

This paper discusses regression analysis of the failure time data arising from case‐cohort periodic follow‐up studies, and one feature of such data, which makes their analysis much more difficult, is that they are usually interval‐censored rather than right‐censored. Although some methods have been developed for general failure time data, there does not seem to exist an established procedure for the...

article

A hybrid approach for the stratified mark‐specific proportional hazards model with missing covariates and missing marks, with application to vaccine efficacy trials

Yanqing Sun, Li Qi, Fei Heng, Peter B. Gilbert

Journal of the Royal Statistical Society: Series C (Applied Statistics) > 69 > 4 > 791 - 814

Deployment of the recently licensed tetravalent dengue vaccine based on a chimeric yellow fever virus, CYD‐TDV, requires understanding of how the risk of dengue disease in vaccine recipients depends jointly on a host biomarker measured after vaccination (neutralization titre—neutralizing antibodies) and on a ‘mark’ feature of the dengue disease failure event (the amino acid sequence distance of the...

article

Assessing pharmacokinetic marker correlates of outcome, with application to antibody prevention efficacy trials

Peter B. Gilbert, Yuanyuan Zhang, Erika Rudnicki, Yunda Huang

Statistics in Medicine > 38 > 23 > 4503 - 4518

The Antibody Mediated Prevention efficacy trials are the first studies to evaluate whether passive administration of a broadly neutralizing monoclonal antibody can prevent human immunodeficiency virus (HIV) acquisition. The trials randomize 4600 HIV‐negative volunteers to receive 10 infusions of the monoclonal antibody VRC01 or placebo. The primary objective compares the incidence of HIV infection...

article

Analysis of generalized semiparametric mixed varying‐coefficients models for longitudinal data

Yanqing Sun, Li Qi, Fei Heng, Peter B. Gilbert

Canadian Journal of Statistics > 47 > 3 > 352 - 373

The generalized semiparametric mixed varying‐coefficient effects model for longitudinal data can accommodate a variety of link functions and flexibly model different types of covariate effects, including time‐constant, time‐varying and covariate‐varying effects. The time‐varying effects are unspecified functions of time and the covariate‐varying effects are nonparametric functions of a possibly time‐dependent...

article

HAI and NAI titer correlates of inactivated and live attenuated influenza vaccine efficacy

Peter B Gilbert, Youyi Fong, Michal Juraska, Lindsay N Carpp, more

BMC Infectious Diseases > 2019 > 19 > 1 > 1-12

Background High hemagglutination inhibition (HAI) and neuraminidase inhibition (NAI) titers are generally associated with reduced influenza risk. While repeated influenza vaccination reduces seroresponse, vaccine effectiveness is not always reduced. Methods During the 2007-2008 influenza season, a randomized, placebo-controlled trial (FLUVACS) evaluated the efficacies of live-attenuated (LAIV) and...

article

Estimation of the optimal surrogate based on a randomized trial

Brenda L. Price, Peter B. Gilbert, Mark J. van der Laan

Biometrics > 74 > 4 > 1271 - 1281

A common scientific problem is to determine a surrogate outcome for a long‐term outcome so that future randomized studies can restrict themselves to only collecting the surrogate outcome. We consider the setting that we observe n independent and identically distributed observations of a random variable consisting of baseline covariates, a treatment, a vector of candidate surrogate outcomes at an...

article

Hypothesis tests for stratified mark‐specific proportional hazards models with missing covariates, with application to HIV vaccine efficacy trials

Yanqing Sun, Li Qi, Guangren Yang, Peter B. Gilbert

Biometrical Journal > 60 > 3 > 516 - 536

This article develops hypothesis testing procedures for the stratified mark‐specific proportional hazards model with missing covariates where the baseline functions may vary with strata. The mark‐specific proportional hazards model has been studied to evaluate mark‐specific relative risks where the mark is the genetic distance of an infecting HIV sequence to an HIV sequence represented inside the...

article

Viral Kinetic Correlates of Cytomegalovirus Disease and Death after Hematopoietic Cell Transplant

Elizabeth R. Duke, Peter B. Gilbert, Terry L. Stevens-Ayers, Jonathan L. Golob, more

Biology of Blood and Marrow Transplantation > 2018 > 24 > 3(S) > S20

article

Improved estimation of the cumulative incidence of rare outcomes

David Benkeser, Marco Carone, Peter B. Gilbert

Statistics in Medicine > 37 > 2 > 280 - 293

Studying the incidence of rare events is both scientifically important and statistically challenging. When few events are observed, standard survival analysis estimators behave erratically, particularly if covariate adjustment is necessary. In these settings, it is possible to improve upon existing estimators by considering estimation in a bounded statistical model. This bounded model incorporates...

article

chngpt: threshold regression model estimation and inference

Youyi Fong, Ying Huang, Peter B. Gilbert, Sallie R. Permar

BMC Bioinformatics > 2017 > 18 > 1 > 1-7

Background Threshold regression models are a diverse set of non-regular regression models that all depend on change points or thresholds. They provide a simple but elegant and interpretable way to model certain kinds of nonlinear relationships between the outcome and a predictor. Results The R package chngpt provides both estimation and hypothesis testing functionalities for four common variants...

article

Immune correlates of protection for dengue: State of the art and research agenda

Leah C. Katzelnick, Eva Harris, Ralph Baric, Beth-Ann Coller, more

Vaccine > 2017 > 35 > 36 > 4659-4669

Dengue viruses (DENV1-4) are mosquito-borne flaviviruses estimated to cause up to ∼400 million infections and ∼100 million dengue cases each year. Factors that contribute to protection from and risk of dengue and severe dengue disease have been studied extensively but are still not fully understood. Results from Phase 3 vaccine efficacy trials have recently become available for one vaccine candidate,...

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INFONA - science communication portal

Search results for: Peter B. Gilbert

A semiparametric Cox–Aalen transformation model with censored data

Nonparametric estimation of the causal effect of a stochastic threshold‐based intervention

Semiparametric additive time‐varying coefficients model for longitudinal data with censored time origin

Estimation of conditional cumulative incidence functions under generalized semiparametric regression models with missing covariates, with application to analysis of biomarker correlates in vaccine trials

Innovative vaccine approaches—a Keystone Symposia report

Efficient nonparametric inference on the effects of stochastic interventions under two‐phase sampling, with applications to vaccine efficacy trials

Semiparametric regression analysis of partly interval‐censored failure time data with application to an AIDS clinical trial

Nonparametric variable importance assessment using machine learning techniques

Rejoinder to “Nonparametric variable importance assessment using machine learning techniques”

A regularized estimation approach for case‐cohort periodic follow‐up studies with an application to HIV vaccine trials

A hybrid approach for the stratified mark‐specific proportional hazards model with missing covariates and missing marks, with application to vaccine efficacy trials

Assessing pharmacokinetic marker correlates of outcome, with application to antibody prevention efficacy trials

Analysis of generalized semiparametric mixed varying‐coefficients models for longitudinal data

HAI and NAI titer correlates of inactivated and live attenuated influenza vaccine efficacy

Estimation of the optimal surrogate based on a randomized trial

Hypothesis tests for stratified mark‐specific proportional hazards models with missing covariates, with application to HIV vaccine efficacy trials

Viral Kinetic Correlates of Cytomegalovirus Disease and Death after Hematopoietic Cell Transplant

Improved estimation of the cumulative incidence of rare outcomes

chngpt: threshold regression model estimation and inference

Immune correlates of protection for dengue: State of the art and research agenda

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