Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Aging; Effect modifiers; Environmental exposure; Frail elderly; Respiratory function tests (1)
- Bivariate survival data; Copula model; Interval sampling; Semi-stationarity. (1)
- Case-control study; cross-validation; threshold regression model (1)
- Errors in variables; nonlinear models; logistic regression; integral equations (1)
- Nuisance parameters; Random effects; Multisite time series data; Air pollution; Hospital admissions (1)
Articles 1 - 12 of 12
Full-Text Articles in Medicine and Health Sciences
Flexible Distributed Lag Models Using Random Functions With Application To Estimating Mortality Displacement From Heat-Related Deaths, Roger D. Peng
Flexible Distributed Lag Models Using Random Functions With Application To Estimating Mortality Displacement From Heat-Related Deaths, Roger D. Peng
Johns Hopkins University, Dept. of Biostatistics Working Papers
No abstract provided.
On The Definition Of A Confounder, Tyler J. Vanderweele, Ilya Shpitser
On The Definition Of A Confounder, Tyler J. Vanderweele, Ilya Shpitser
COBRA Preprint Series
The causal inference literature has provided a clear formal definition of confounding expressed in terms of counterfactual independence. The causal inference literature has not, however, produced a clear formal definition of a confounder, as it has given priority to the concept of confounding over that of a confounder. We consider a number of candidate definitions arising from various more informal statements made in the literature. We consider the properties satisfied by each candidate definition, principally focusing on (i) whether under the candidate definition control for all "confounders" suffices to control for "confounding" and (ii) whether each confounder in some context …
Components Of The Indirect Effect In Vaccine Trials: Identification Of Contagion And Infectiousness Effects, Tyler J. Vanderweele, Eric J. Tchetgen, M. Elizabeth Halloran
Components Of The Indirect Effect In Vaccine Trials: Identification Of Contagion And Infectiousness Effects, Tyler J. Vanderweele, Eric J. Tchetgen, M. Elizabeth Halloran
COBRA Preprint Series
Vaccination of one person may prevent the infection of another either because (i) the vaccine prevents the first from being infected and from infecting the second or because (ii) even if the first person is infected, the vaccine may render the infection less infectious. We might refer to the first of these mechanisms as a contagion effect and the second as an infectiousness effect. In this paper, for the simple setting of a randomized vaccine trial with households of size two, we use counterfactual theory under interference to provide formal definitions of a contagion effect and an infectiousness effect. Using …
Assessing Association For Bivariate Survival Data With Interval Sampling: A Copula Model Approach With Application To Aids Study, Hong Zhu, Mei-Cheng Wang
Assessing Association For Bivariate Survival Data With Interval Sampling: A Copula Model Approach With Application To Aids Study, Hong Zhu, Mei-Cheng Wang
Johns Hopkins University, Dept. of Biostatistics Working Papers
In disease surveillance systems or registries, bivariate survival data are typically collected under interval sampling. It refers to a situation when entry into a registry is at the time of the first failure event (e.g., HIV infection) within a calendar time interval, the time of the initiating event (e.g., birth) is retrospectively identified for all the cases in the registry, and subsequently the second failure event (e.g., death) is observed during the follow-up. Sampling bias is induced due to the selection process that the data are collected conditioning on the first failure event occurs within a time interval. Consequently, the …
A Regularization Corrected Score Method For Nonlinear Regression Models With Covariate Error, David M. Zucker, Malka Gorfine, Yi Li, Donna Spiegelman
A Regularization Corrected Score Method For Nonlinear Regression Models With Covariate Error, David M. Zucker, Malka Gorfine, Yi Li, Donna Spiegelman
Harvard University Biostatistics Working Paper Series
No abstract provided.
Estimation Of Risk Ratios In Cohort Studies With Common Outcomes: A Simple And Efficient Two-Stage Approach, Eric J. Tchetgen
Estimation Of Risk Ratios In Cohort Studies With Common Outcomes: A Simple And Efficient Two-Stage Approach, Eric J. Tchetgen
Harvard University Biostatistics Working Paper Series
No abstract provided.
On The Nondifferential Misclassification Of A Binary Confounder, Elizabeth L. Ogburn, Tyler J. Vanderweele
On The Nondifferential Misclassification Of A Binary Confounder, Elizabeth L. Ogburn, Tyler J. Vanderweele
COBRA Preprint Series
Abstract Consider a study with binary exposure, outcome, and confounder, where the confounder is nondifferentially misclassified. Epidemiologists have long accepted the unproven but oft-cited result that, if the confounder is binary, odds ratios, risk ratios, and risk differences which control for the mismeasured confounder will lie between the crude and the true measures. In this paper the authors provide an analytic proof of the result in the absence of a qualitative interaction between treatment and confounder, and demonstrate via counterexample that the result need not hold when there is a qualitative interaction between treatment and confounder. They also present an …
Modification By Frailty Status Of Ambient Air Pollution Effects On Lung Function In Older Adults In The Cardiovascular Health Study, Sandrah P. Eckel, Thomas A. Louis, Paulo H.M. Chaves, Linda P. Fried, Helene G. Margolis
Modification By Frailty Status Of Ambient Air Pollution Effects On Lung Function In Older Adults In The Cardiovascular Health Study, Sandrah P. Eckel, Thomas A. Louis, Paulo H.M. Chaves, Linda P. Fried, Helene G. Margolis
Johns Hopkins University, Dept. of Biostatistics Working Papers
Older adult susceptibility to air pollution health effects is well-recognized. Advanced age may act as a partial surrogate for conditions associated with aging. The authors investigated whether gerontologic frailty (a clinical health status metric) modified the effects of ambient ozone or particulate matter (PM10) air pollution on lung function in 3382 older adults using 7 years of followup data from the Cardiovascular Health Study (CHS) and the CHS Environmental Factors Ancillary Study. Monthly average pollution and annual frailty assessments were related to up to 3 repeated measurements of lung function using novel cumulative summaries of pollution and frailty histories that …
Variable Importance Analysis With The Multipim R Package, Stephan J. Ritter, Nicholas P. Jewell, Alan E. Hubbard
Variable Importance Analysis With The Multipim R Package, Stephan J. Ritter, Nicholas P. Jewell, Alan E. Hubbard
U.C. Berkeley Division of Biostatistics Working Paper Series
We describe the R package multiPIM, including statistical background, functionality and user options. The package is for variable importance analysis, and is meant primarily for analyzing data from exploratory epidemiological studies, though it could certainly be applied in other areas as well. The approach taken to variable importance comes from the causal inference field, and is different from approaches taken in other R packages. By default, multiPIM uses a double robust targeted maximum likelihood estimator (TMLE) of a parameter akin to the attributable risk. Several regression methods/machine learning algorithms are available for estimating the nuisance parameters of the models, including …
Reduced Bayesian Hierarchical Models: Estimating Health Effects Of Simultaneous Exposure To Multiple Pollutants, Jennifer F. Bobb, Francesca Dominici, Roger D. Peng
Reduced Bayesian Hierarchical Models: Estimating Health Effects Of Simultaneous Exposure To Multiple Pollutants, Jennifer F. Bobb, Francesca Dominici, Roger D. Peng
Johns Hopkins University, Dept. of Biostatistics Working Papers
Quantifying the health effects associated with simultaneous exposure to many air pollutants is now a research priority of the US EPA. Bayesian hierarchical models (BHM) have been extensively used in multisite time series studies of air pollution and health to estimate health effects of a single pollutant adjusted for potential confounding of other pollutants and other time-varying factors. However, when the scientific goal is to estimate the impacts of many pollutants jointly, a straightforward application of BHM is challenged by the need to specify a random-effect distribution on a high-dimensional vector of nuisance parameters, which often do not have an …
Bayesian Effect Estimation Accounting For Adjustment Uncertainty, Chi Wang, Giovanni Parmigiani, Francesca Dominici
Bayesian Effect Estimation Accounting For Adjustment Uncertainty, Chi Wang, Giovanni Parmigiani, Francesca Dominici
Harvard University Biostatistics Working Paper Series
No abstract provided.
Threshold Regression Models Adapted To Case-Control Studies, And The Risk Of Lung Cancer Due To Occupational Exposure To Asbestos In France, Antoine Chambaz, Dominique Choudat, Catherine Huber, Jean-Claude Pairon, Mark J. Van Der Laan
Threshold Regression Models Adapted To Case-Control Studies, And The Risk Of Lung Cancer Due To Occupational Exposure To Asbestos In France, Antoine Chambaz, Dominique Choudat, Catherine Huber, Jean-Claude Pairon, Mark J. Van Der Laan
U.C. Berkeley Division of Biostatistics Working Paper Series
Asbestos has been known for many years as a powerful carcinogen. Our purpose is quantify the relationship between an occupational exposure to asbestos and an increase of the risk of lung cancer. Furthermore, we wish to tackle the very delicate question of the evaluation, in subjects suffering from a lung cancer, of how much the amount of exposure to asbestos explains the occurrence of the cancer. For this purpose, we rely on a recent French case-control study. We build a large collection of threshold regression models, data-adaptively select a better model in it by multi-fold likelihood-based cross-validation, then fit the …