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- Genetics (12)
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Articles 31 - 60 of 212
Full-Text Articles in Statistics and Probability
Leveraging Contact Network Structure In The Design Of Cluster Randomized Trials, Guy Harling, Rui Wang, Jukka-Pekka Onnela, Victor Degruttola
Leveraging Contact Network Structure In The Design Of Cluster Randomized Trials, Guy Harling, Rui Wang, Jukka-Pekka Onnela, Victor Degruttola
Harvard University Biostatistics Working Paper Series
Background: In settings like the Ebola epidemic, where proof-of-principle trials have succeeded but questions remain about the effectiveness of different possible modes of implementation, it may be useful to develop trials that not only generate information about intervention effects but also themselves provide public health benefit. Cluster randomized trials are of particular value for infectious disease prevention research by virtue of their ability to capture both direct and indirect effects of intervention; the latter of which depends heavily on the nature of contact networks within and across clusters. By leveraging information about these networks – in particular the degree …
Using Validation Data To Adjust The Inverse Probability Weighting Estimator For Misclassified Treatment, Danielle Braun, Corwin Zigler, Francesca Dominici, Malka Gorfine
Using Validation Data To Adjust The Inverse Probability Weighting Estimator For Misclassified Treatment, Danielle Braun, Corwin Zigler, Francesca Dominici, Malka Gorfine
Harvard University Biostatistics Working Paper Series
The inverse probability weighting (IPW) estimator is widely used to estimate the treatment effect in observational studies in which patient characteristics might not be balanced by treatment group. The estimator assumes that treatment assignment, is error-free, but in reality treatment assignment can be measured with error. This arises in the context of comparative effectiveness research, using administrative data sources in which accurate procedural or billing codes are not always available. We show the bias introduced to the estimator when using error-prone treatment assignment, and propose an adjusted estimator using a validation study to eliminate this bias. In simulations, we explore …
Estimation And Inference For The Mediation Proportion, Daniel Nevo, Xiaomei Liao, Donna Spiegelman
Estimation And Inference For The Mediation Proportion, Daniel Nevo, Xiaomei Liao, Donna Spiegelman
Harvard University Biostatistics Working Paper Series
In epidemiology, public health and social science, mediation analysis is often undertaken to investigate the extent to which the effect of a risk factor on an outcome of interest is mediated by other covariates. A pivotal quantity of interest in such an analysis is the mediation proportion. A common method for estimating it, termed the "difference method'', compares estimates from models with and without the hypothesized mediator. However, rigorous methodology for estimation and statistical inference for this quantity has not previously been available. We formulated the problem for the Cox model and generalized linear models, and utilize a data duplication …
A Cautionary Note On The Effect Of Treatment Misclassification On The Average Treatment Effect, Danielle Braun, Corwin Zigler, Malka Gorfine, Francesca Dominici
A Cautionary Note On The Effect Of Treatment Misclassification On The Average Treatment Effect, Danielle Braun, Corwin Zigler, Malka Gorfine, Francesca Dominici
Harvard University Biostatistics Working Paper Series
Comparative effectiveness research often relies on large administrative data, such as claims data. Methods to estimate treatment effects assume that treatment assignment is error-free, but in reality the inaccuracy of procedural or billing codes frequently misclassifies patients into treatment groups. Propensity score methods are widely used to analyze observational studies in which patient characteristics might not be balanced by treatment group. We evaluate the impact of treatment misclassification on 1) propensity score estimation; 2) treatment effect estimation conditional on propensity score estimation and implementation. We focus on three common propensity score implementations: subclassification, matching, and inverse probability of treatment weighting …
The Myth Of Making Inferences For An Overall Treatment Efficacy With Data From Multiple Comparative Studies Via Meta-Analysis, Takahiro Hasegawa, Brian Claggett, Lu Tian, Scott D. Solomon, Marc A. Pfeffer, Lee-Jen Wei
The Myth Of Making Inferences For An Overall Treatment Efficacy With Data From Multiple Comparative Studies Via Meta-Analysis, Takahiro Hasegawa, Brian Claggett, Lu Tian, Scott D. Solomon, Marc A. Pfeffer, Lee-Jen Wei
Harvard University Biostatistics Working Paper Series
Meta analysis techniques, if applied appropriately, can provide a summary of the totality of evidence regarding an overall difference between a new treatment and a control group using data from multiple comparative clinical studies. The standard meta analysis procedures, however, may not give a meaningful between-group difference summary measure or identify a meaningful patient population of interest, especially when the fixed effect model assumption is not met. Moreover, a single between-group comparison measure without a reference value obtained from patients in the control arm would likely not be informative enough for clinical decision making. In this paper, we propose a …
Moving Beyond The Conventional Stratified Analysis To Estimate An Overall Treatment Efficacy With The Data From A Comparative Randomized Clinical Study, Lu Tian, Fei Jiang, Takahiro Hasegawa, Hajime Uno, Marc Alan Pfeffer, L.J. Wei
Moving Beyond The Conventional Stratified Analysis To Estimate An Overall Treatment Efficacy With The Data From A Comparative Randomized Clinical Study, Lu Tian, Fei Jiang, Takahiro Hasegawa, Hajime Uno, Marc Alan Pfeffer, L.J. Wei
Harvard University Biostatistics Working Paper Series
No abstract provided.
On Varieties Of Doubly Robust Estimators Under Missing Not At Random With An Ancillary Variable, Wang Miao, Eric Tchetgen Tchetgen
On Varieties Of Doubly Robust Estimators Under Missing Not At Random With An Ancillary Variable, Wang Miao, Eric Tchetgen Tchetgen
Harvard University Biostatistics Working Paper Series
No abstract provided.
On Partial Identification Of The Pure Direct Effect, Caleb Miles, Phyllis Kanki, Seema Meloni, Eric Tchetgen Tchetgen
On Partial Identification Of The Pure Direct Effect, Caleb Miles, Phyllis Kanki, Seema Meloni, Eric Tchetgen Tchetgen
Harvard University Biostatistics Working Paper Series
No abstract provided.
On Simple Relations Between Difference-In-Differences And Negative Outcome Control Of Unobserved Confounding, Tamar Sofer, David B. Richardson, Elena Colincino, Joel Schwartz, Eric J. Tchetgen Tchetgen
On Simple Relations Between Difference-In-Differences And Negative Outcome Control Of Unobserved Confounding, Tamar Sofer, David B. Richardson, Elena Colincino, Joel Schwartz, Eric J. Tchetgen Tchetgen
Harvard University Biostatistics Working Paper Series
No abstract provided.
Lepski's Method And Adaptive Estimation Of Nonlinear Integral Functionals Of Density, Rajarshi Mukherjee, Eric J. Tchetgen Tchetgen, James M. Robins
Lepski's Method And Adaptive Estimation Of Nonlinear Integral Functionals Of Density, Rajarshi Mukherjee, Eric J. Tchetgen Tchetgen, James M. Robins
Harvard University Biostatistics Working Paper Series
No abstract provided.
Negative Outcome Control For Unobserved Confounding Under A Cox Proportional Hazards Model, Eric J. Tchetgen Tchetgen, Tamar Sofer, David Richardson
Negative Outcome Control For Unobserved Confounding Under A Cox Proportional Hazards Model, Eric J. Tchetgen Tchetgen, Tamar Sofer, David Richardson
Harvard University Biostatistics Working Paper Series
No abstract provided.
Survival Analysis With Functions Of Mis-Measured Covariate Histories: The Case Of Chronic Air Pollution Exposure In Relation To Mortality In The Nurses' Health Study, Xiaomei Liao, Molin Wang, Jaime E. Hart, Francine Laden, Donna Spiegelman
Survival Analysis With Functions Of Mis-Measured Covariate Histories: The Case Of Chronic Air Pollution Exposure In Relation To Mortality In The Nurses' Health Study, Xiaomei Liao, Molin Wang, Jaime E. Hart, Francine Laden, Donna Spiegelman
Harvard University Biostatistics Working Paper Series
Environmental epidemiologists are often interested in estimating the effect of functions of time-varying exposure histories, such as the 12-month moving average, in relation to chronic disease incidence or mortality. The individual exposure measurements that comprise such an exposure history are usually mis-measured, at least moderately, and, often, more substantially. To obtain unbiased estimates of Cox model hazard ratios for these complex mis-measured exposure functions, an extended risk set regression calibration (RRC) method for Cox models is developed and applied to a study of long-term exposure to the fine particulate matter ($PM_{2.5}$) component of air pollution in relation to all-cause mortality …
Doubly Robust Estimation Of A Marginal Average Effect Of Treatment On The Treated With An Instrumental Variable, Lan Liu, Wang Miao, Baoluo Sun, James M. Robins, Eric J. Tchetgen Tchetgen
Doubly Robust Estimation Of A Marginal Average Effect Of Treatment On The Treated With An Instrumental Variable, Lan Liu, Wang Miao, Baoluo Sun, James M. Robins, Eric J. Tchetgen Tchetgen
Harvard University Biostatistics Working Paper Series
No abstract provided.
Identification And Doubly Robust Estimation Of Data Missing Not At Random With An Ancillary Variable, Wang Miao, Eric Tchetgen Tchetgen, Zhi Geng
Identification And Doubly Robust Estimation Of Data Missing Not At Random With An Ancillary Variable, Wang Miao, Eric Tchetgen Tchetgen, Zhi Geng
Harvard University Biostatistics Working Paper Series
No abstract provided.
A General Framework For Diagnosing Confounding Of Time-Varying And Other Joint Exposures, John W. Jackson
A General Framework For Diagnosing Confounding Of Time-Varying And Other Joint Exposures, John W. Jackson
Harvard University Biostatistics Working Paper Series
No abstract provided.
Simulation Of Semicompeting Risk Survival Data And Estimation Based On Multistate Frailty Model, Fei Jiang, Sebastien Haneuse
Simulation Of Semicompeting Risk Survival Data And Estimation Based On Multistate Frailty Model, Fei Jiang, Sebastien Haneuse
Harvard University Biostatistics Working Paper Series
We develop a simulation procedure to simulate the semicompeting risk survival data. In addition, we introduce an EM algorithm and a B–spline based estimation procedure to evaluate and implement Xu et al. (2010)’s nonparametric likelihood es- timation approach. The simulation procedure provides a route to simulate samples from the likelihood introduced in Xu et al. (2010)’s. Further, the EM algorithm and the B–spline methods stabilize the estimation and gives accurate estimation results. We illustrate the simulation and the estimation procedure with simluation examples and real data analysis.
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
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.
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
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.
Constrained Bayesian Estimation Of Inverse Probability Weights For Nonmonotone Missing Data, Baoluo Sun, Eric J. Tchetgen Tchetgen
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.
Optimal Bayesian Adaptive Trials When Treatment Efficacy Depends On Biomarkers, Yifan Zhang, Lorenzo Trippa, Giovanni Parmigiani
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.
Generalized Quantile Treatment Effect, Sergio Venturini, Francesca Dominici, Giovanni Parmigiani
Generalized Quantile Treatment Effect, Sergio Venturini, Francesca Dominici, Giovanni Parmigiani
Harvard University Biostatistics Working Paper Series
No abstract provided.
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
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.
Instrumental Variable Estimation In A Survival Context, Eric J. Tchetgen Tchetgen, Stefan Walter, Stijn Vansteelandt, Torben Martinussen, Maria Glymour
Instrumental Variable Estimation In A Survival Context, Eric J. Tchetgen Tchetgen, Stefan Walter, Stijn Vansteelandt, Torben Martinussen, Maria Glymour
Harvard University Biostatistics Working Paper Series
No abstract provided.
Likelihood Based Estimation Of Logistic Structural Nested Mean Models With An Instrumental Variable, Roland A. Matsouaka, Eric J. Tchetgen Tchetgen
Likelihood Based Estimation Of Logistic Structural Nested Mean Models With An Instrumental Variable, Roland A. Matsouaka, Eric J. Tchetgen Tchetgen
Harvard University Biostatistics Working Paper Series
No abstract provided.
A General Approach To Detect Gene (G)-Environment (E) Additive Interaction Leveraging G-E Independence In Case-Control Studies, Eric Tchetgen Tchetgen, Tamar Sofer, Benedict H.W. Wong
A General Approach To Detect Gene (G)-Environment (E) Additive Interaction Leveraging G-E Independence In Case-Control Studies, Eric Tchetgen Tchetgen, Tamar Sofer, Benedict H.W. Wong
Harvard University Biostatistics Working Paper Series
No abstract provided.
A Note On The Control Function Approach With An Instrumental Variable And A Binary Outcome, Eric Tchetgen Tchetgen
A Note On The Control Function Approach With An Instrumental Variable And A Binary Outcome, Eric Tchetgen Tchetgen
Harvard University Biostatistics Working Paper Series
No abstract provided.
A Simple Regression-Based Approach To Account For Survival Bias In Birth Outcomes Research, Eric J. Tchetgen Tchetgen, Kelesitse Phiri, Roger Shapiro
A Simple Regression-Based Approach To Account For Survival Bias In Birth Outcomes Research, Eric J. Tchetgen Tchetgen, Kelesitse Phiri, Roger Shapiro
Harvard University Biostatistics Working Paper Series
No abstract provided.
Control Function Assisted Ipw Estimation With A Secondary Outcome In Case-Control Studies, Tamar Sofer, Marilyn C. Cornelis, Peter Kraft, Eric J. Tchetgen Tchetgen
Control Function Assisted Ipw Estimation With A Secondary Outcome In Case-Control Studies, Tamar Sofer, Marilyn C. Cornelis, Peter Kraft, Eric J. Tchetgen Tchetgen
Harvard University Biostatistics Working Paper Series
No abstract provided.
Predicting The Future Subject's Outcome Via An Optimal Stratification Procedure With Baseline Information, Florence H. Yong, Lu Tian, Sheng Yu, Tianxi Cai, L. J. Wei
Predicting The Future Subject's Outcome Via An Optimal Stratification Procedure With Baseline Information, Florence H. Yong, Lu Tian, Sheng Yu, Tianxi Cai, L. J. Wei
Harvard University Biostatistics Working Paper Series
No abstract provided.
Bounds To Evaluate The Pure/Natural Direct Effect Without Cross-World Counterfactual Independence, Eric Tchetgen Tchetgen, Kelesitse Phiri
Bounds To Evaluate The Pure/Natural Direct Effect Without Cross-World Counterfactual Independence, Eric Tchetgen Tchetgen, Kelesitse Phiri
Harvard University Biostatistics Working Paper Series
No abstract provided.