相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。Inference on Selected Subgroups in Clinical Trials
Xinzhou Guo et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2021)
Reduced exposure to vasopressors through permissive hypotension to reduce mortality in critically ill peoble aged 65 and over; the 65 RCT
Paul R. Mouncey et al.
HEALTH TECHNOLOGY ASSESSMENT (2021)
The Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement: Explanation and Elaboration
David M. Kent et al.
ANNALS OF INTERNAL MEDICINE (2020)
Effect of Reduced Exposure to Vasopressors on 90-Day Mortality in Older Critically Ill Patients With Vasodilatory Hypotension A Randomized Clinical Trial
Francois Lamontagne et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2020)
Machine learning analysis plans for randomised controlled trials: detecting treatment effect heterogeneity with strict control of type I error
James A. Watson et al.
TRIALS (2020)
Metalearners for estimating heterogeneous treatment effects using machine learning
Soren R. Kunzel et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2019)
GENERALIZED RANDOM FORESTS
Susan Athey et al.
ANNALS OF STATISTICS (2019)
Understanding of interaction (subgroup) analysis in clinical trials
Milos Brankovic et al.
EUROPEAN JOURNAL OF CLINICAL INVESTIGATION (2019)
Assessing heterogeneous effects and their determinants via estimation of potential outcomes
Anton Nilsson et al.
EUROPEAN JOURNAL OF EPIDEMIOLOGY (2019)
Models with interactions overestimated heterogeneity of treatment effects and were prone to treatment mistargeting
David van Klaveren et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2019)
Identification of predicted individual treatment effects in randomized clinical trials
Andrea Lamont et al.
STATISTICAL METHODS IN MEDICAL RESEARCH (2018)
Pooled analysis of higher versus lower blood pressure targets for vasopressor therapy septic and vasodilatory shock
Francois Lamontagne et al.
INTENSIVE CARE MEDICINE (2018)
Predicting risk for adverse health events using random forest
Guy Cafri et al.
JOURNAL OF APPLIED STATISTICS (2018)
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
Stefan Wager et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2018)
Patient Variability Seldom Assessed in Cost-effectiveness Studies
Tara A. Lavelle et al.
MEDICAL DECISION MAKING (2018)
Iterative random forests to discover predictive and stable high-order interactions
Sumanta Basu et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2018)
Personalized evidence based medicine: predictive approaches to heterogeneous treatment effects
David M. Kent et al.
BMJ-BRITISH MEDICAL JOURNAL (2018)
Evaluating the impact of treating the optimal subgroup
Alexander R. Luedtke et al.
STATISTICAL METHODS IN MEDICAL RESEARCH (2017)
Multiplicity considerations in subgroup analysis
Alex Dmitrienko et al.
STATISTICS IN MEDICINE (2017)
A general statistical framework for subgroup identification and comparative treatment scoring
Shuai Chen et al.
BIOMETRICS (2017)
EXACT POST-SELECTION INFERENCE, WITH APPLICATION TO THE LASSO
Jason D. Lee et al.
ANNALS OF STATISTICS (2016)
Higher versus lower blood pressure targets for vasopressor therapy in shock: a multicentre pilot randomized controlled trial
Francois Lamontagne et al.
INTENSIVE CARE MEDICINE (2016)
Recursive partitioning for heterogeneous causal effects
Susan Athey et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2016)
No improvement in the reporting of clinical trial subgroup effects in high-impact general medical journals
Nicole B. Gabler et al.
TRIALS (2016)
Regularized Outcome Weighted Subgroup Identification for Differential Treatment Effects
Yaoyao Xu et al.
BIOMETRICS (2015)
Are Elderly Patients With Clinically Localized Prostate Cancer Overtreated? Exploring Heterogeneity in Survival Effects
Anirban Basu et al.
MEDICAL CARE (2015)
A regression tree approach to identifying subgroups with differential treatment effects
Wei-Yin Loh et al.
STATISTICS IN MEDICINE (2015)
The Value of Heterogeneity for Cost-Effectiveness Subgroup Analysis: Conceptual Framework and Application
Manuel A. Espinoza et al.
MEDICAL DECISION MAKING (2014)
High versus Low Blood-Pressure Target in Patients with Septic Shock
Pierre Asfar et al.
NEW ENGLAND JOURNAL OF MEDICINE (2014)
ESTIMATING PERSON-CENTERED TREATMENT (PeT) EFFECTS USING INSTRUMENTAL VARIABLES: AN APPLICATION TO EVALUATING PROSTATE CANCER TREATMENTS
Anirban Basu
JOURNAL OF APPLIED ECONOMETRICS (2014)
ESTIMATING TREATMENT EFFECT HETEROGENEITY IN RANDOMIZED PROGRAM EVALUATION
Kosuke Imai et al.
ANNALS OF APPLIED STATISTICS (2013)
A new variable selection approach using Random Forests
A. Hapfelmeier et al.
COMPUTATIONAL STATISTICS & DATA ANALYSIS (2013)
Estimating Individualized Treatment Rules Using Outcome Weighted Learning
Yingqi Zhao et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2012)
Methods for Estimating Subgroup Effects in Cost-Effectiveness Analyses That Use Observational Data
Noemi Kreif et al.
MEDICAL DECISION MAKING (2012)
Economics of individualization in comparative effectiveness research and a basis for a patient-centered health care
Anirban Basu
JOURNAL OF HEALTH ECONOMICS (2011)
Subgroup identification based on differential effect search-A recursive partitioning method for establishing response to treatment in patient subpopulations
Ilya Lipkovich et al.
STATISTICS IN MEDICINE (2011)
Multivariate random forests
Mark Segal et al.
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY (2011)
The Path to Personalized Medicine
Margaret A. Hamburg et al.
NEW ENGLAND JOURNAL OF MEDICINE (2010)
Use of instrumental variables in the presence of heterogeneity and self-selection: An application to treatments of breast cancer patients
Anirban Basu et al.
HEALTH ECONOMICS (2007)
Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference
Daniel E. Ho et al.
POLITICAL ANALYSIS (2007)
Value of information on preference heterogeneity and individualized care
Anirban Basu et al.
MEDICAL DECISION MAKING (2007)
Methods for incorporating covariate adjustment, subgroup analysis and between-centre differences into cost-effectiveness evaluations
RM Nixon et al.
HEALTH ECONOMICS (2005)
Estimating marginal and incremental effects on health outcomes using flexible link and variance function models
A Basu et al.
BIOSTATISTICS (2005)
Regression methods for covariate adjustment and subgroup analysis for non-censored cost-effectiveness data
AR Willan et al.
HEALTH ECONOMICS (2004)
Quantifying epidemologic risk factors using non-parametric regression: model selection remains the greatest challenge
PS Rosenberg et al.
STATISTICS IN MEDICINE (2003)
Something old, something new, something borrowed, something blue: a framework for the marriage of health econometrics and cost-effectiveness analysis
JS Hoch et al.
HEALTH ECONOMICS (2002)
分享论文
