Filters








69,080 Hits in 5.3 sec

Set-valued dynamic treatment regimes for competing outcomes [article]

Eric B. Laber, Daniel J. Lizotte, Bradley Ferguson
2012 arXiv   pre-print
We propose a method for constructing dynamic treatment regimes that accommodates competing outcomes by recommending sets of treatments at each decision point.  ...  Current methods for estimating optimal dynamic treatment regimes, for example Q-learning, require the specification of a single outcome by which the 'goodness' of competing dynamic treatment regimes are  ...  This is a multisite, clinical trial of persons with schizophrenia comparing the effectiveness of randomly assigned medication treatment.  ... 
arXiv:1207.3100v2 fatcat:quzejza5sbd6hgscuwfyhmupfu

Set-valued dynamic treatment regimes for competing outcomes

Eric B. Laber, Daniel J. Lizotte, Bradley Ferguson
2014 Biometrics  
Composite outcomes A natural approach is to combine competing outcomes into a single composite outcome A single composite outcome for all patients (e.g., Wang et al., 2012) Elicited by panel of experts  ...  A patient presenting with H1 = h1 is offered treatments π Ideal 1∆ (h1) τ 2 ∈S(π Ideal 2∆ ) π Ideal 1∆ (h1, τ2) Decision rule τ 2 is compatible with set-valued rule π 2 if τ 2 (h 2 ) ∈ π 2 (h 2 ) for all  ...  Discussion Introduced set-valued dynamic treatment regimes (SVDTRs) One approach to dealing with competing outcomes under:  ... 
doi:10.1111/biom.12132 pmid:24400912 pmcid:PMC3954452 fatcat:lchh4ajdy5fmpbcmm3qqwbubuy

Multi-stage optimal dynamic treatment regimes for survival outcomes with dependent censoring [article]

Hunyong Cho, Shannon T. Holloway, David J. Couper, Michael R. Kosorok
2022 arXiv   pre-print
We propose a reinforcement learning method for estimating an optimal dynamic treatment regime for survival outcomes with dependent censoring.  ...  Simulations and data analysis results suggest that the new estimator brings higher expected outcomes than existing methods in various settings. An R package dtrSurv is available on CRAN.  ...  The authors thank Donglin Zeng for bringing the composite criterion optimization into the discussion and the editors and anonymous reviewers for their constructive  ... 
arXiv:2012.03294v2 fatcat:oaer4wk5rbhqzooqrk5f3a5amm

Estimating the Comparative Effectiveness of Feeding Interventions in the Pediatric Intensive Care Unit: A Demonstration of Longitudinal Targeted Maximum Likelihood Estimation

Noémi Kreif, Linh Tran, Richard Grieve, Bianca De Stavola, Robert C Tasker, Maya Petersen
2017 American Journal of Epidemiology  
Dynamic regimes, or individualized treatment rules, in contrast, define a set of rules as a function of time-varying patient characteristics (2-6).  ...  The latter arises in longitudinal settings, when the uptake of treatment may depend on factors that influence the outcome and are also affected by earlier treatments. It is widely  ...  Mark van der Laan and Josh Schwab for expert advice and Dr. Elizabeth Allen for data access. Conflict of interest: none declared.  ... 
doi:10.1093/aje/kwx213 pmid:28992064 pmcid:PMC5860499 fatcat:g5z367db7zc73h3ausdwn6nx3q

Identification, Estimation and Approximation of Risk under Interventions that Depend on the Natural Value of Treatment Using Observational Data

Jessica G. Young, Miguel A. Hernán, James M. Robins
2014 Epidemiologic Methods  
Geneva: World Health Organization) introduced the extended g-formula to estimate from observational data the risk of failure under hypothetical interventions wherein a subject's treatment at time  ...  In the main text, this notation was reserved only for deterministic regimes (dynamic or static) that do not depend on the natural value of treatment.  ...  dynamic regimes based on an explicit deterministic mechanism depending on the natural value of treatment.  ... 
doi:10.1515/em-2012-0001 pmid:25866704 pmcid:PMC4387917 fatcat:xz5hgygiwbar7pvjezamsla7ay

Inference about the expected performance of a data-driven dynamic treatment regime

Bibhas Chakraborty, Eric B Laber, Ying-Qi Zhao
2014 Clinical Trials  
Background-A dynamic treatment regime (DTR) comprises a sequence of decision rules, one per stage of intervention, that recommends how to individualize treatment to patients based on evolving treatment  ...  The Value of a DTR is the expected outcome when the DTR is used to assign treatments to a population of interest.  ...  We discussed the case where the Value of a competing regime (say, standard care) was known and compared with an estimated optimal regime.  ... 
doi:10.1177/1740774514537727 pmid:24925083 pmcid:PMC4265005 fatcat:3cdacvo7rzfc5bd525gdkxtkpe

Variable Selection in Regression-based Estimation of Dynamic Treatment Regimes [article]

Zeyu Bian, Erica EM Moodie, Susan M Shortreed, Sahir Bhatnagar
2021 arXiv   pre-print
Dynamic treatment regimes (DTRs) consist of a sequence of decision rules, one per stage of intervention, that finds effective treatments for individual patients according to patient information history  ...  We propose a variable selection method for DTR estimation using penalized dynamic weighted least squares.  ...  regimes for treatment decision making and value functions.  ... 
arXiv:2101.07359v3 fatcat:sv2coikuuvf5zjkzv5e2g4xmpq

Response to reader reaction

2014 Biometrics  
outcome, or value, under a regime in a specified class ; we have referred to estimators for an optimal regime found by maximizing an estimator for the value in η as value search or policy search estimators  ...  The authors replied as follows We applaud Taylor, Cheng, and Foster (henceforth TCF) for carrying out additional empirical studies of methods for estimating optimal treatment regimes, as further elucidation  ...  We thank TCF again for a thoughtful and important demonstration of the relative merits of estimators for optimal dynamic treatment regimes.  ... 
doi:10.1111/biom.12229 pmid:25355405 pmcid:PMC4447210 fatcat:f2p4awtlxnbbxanx72qwlok3la

Robust estimation of optimal dynamic treatment regimes for sequential treatment decisions

B. Zhang, A. A. Tsiatis, E. B. Laber, M. Davidian
2013 Biometrika  
A dynamic treatment regime is a list of sequential decision rules for assigning treatment based on a patient's history.  ...  Q-learning requires postulated regression models for the outcome, while A-learning involves models for that part of the outcome regression representing treatment contrasts and for treatment assignment.  ...  A dynamic treatment regime is a set of sequential decision rules, each corresponding to a decision point in the treatment process.  ... 
doi:10.1093/biomet/ast014 pmid:24302771 pmcid:PMC3843953 fatcat:waa54cpndncj5jegplyvs7th7q

Bayesian Nonparametric Estimation for Dynamic Treatment Regimes With Sequential Transition Times

Yanxun Xu, Peter Müller, Abdus S. Wahed, Peter F. Thall
2016 Journal of the American Statistical Association  
For the general setting, we propose estimating mean overall outcome time by assuming a Bayesian nonparametric regression model for the logarithm of each transition time.  ...  Dynamic treatment regimes in oncology and other disease areas often can be characterized by an alternating sequence of treatments or other actions and transition times between disease states.  ...  We would also like to point out some recent literature for dynamic treatment regimes for survival outcomes.  ... 
doi:10.1080/01621459.2015.1086353 pmid:28018015 pmcid:PMC5175473 fatcat:oovqy6qj5bgrnp36km2hf24vo4

Q-Learning: Flexible Learning About Useful Utilities

Erica E. M. Moodie, Nema Dean, Yue Ru Sun
2013 Statistics in Biosciences  
Dynamic treatment regimes are fast becoming an important part of medicine, with the corresponding change in emphasis from treatment of the disease to treatment of the individual patient.  ...  Q-learning is a popular method for estimating the optimal treatment regime, originally in randomized trials but more recently also in observational data.  ...  Bibhas Chakraborty for insightful discussions. This work is supported by Dr. Moodie's Discovery Grant from the Canada's Natural Sciences and Engineering Research Council (NSERC).  ... 
doi:10.1007/s12561-013-9103-z fatcat:mpsokkbotffkjmswdsyynmtu3y

Effectiveness of Incumbent's Strategic Communication during Economic Crisis under Electoral Authoritarianism: Evidence from Turkey

SELIM ERDEM AYTAÇ
2021 American Political Science Review  
In contrast, changing the political agenda away from the economy to an issue area that is more favorable for the incumbent is more effective for shoring up popular support.  ...  Understanding the dynamics of regime stability in these countries is important foremost for the vast number of their citizens facing actual and potential repression and limited political rights.  ...  multiple treatment arms and outcomes, we are likely to encounter the multiple comparisons problem.  ... 
doi:10.1017/s0003055421000587 fatcat:cbdb4wd3uvamlpwwvexe2ivbz4

Improved Doubly Robust Estimation in Marginal Mean Models for Dynamic Regimes

Hao Sun, Ashkan Ertefaie, Xin Lu, Brent A. Johnson
2020 Journal of Causal Inference  
They have become a popular tool in causal inference, including applications to dynamic treatment regimes.  ...  The doubly robust estimators for the mean response to a dynamic treatment regime may be conceived through the augmented inverse probability weighted (AIPW) estimating function, defined as the sum of the  ...  It would be interesting to compare some of these competing methods in examples of dynamic treatment regimes, such as the treatment length problem.  ... 
doi:10.1515/jci-2020-0015 fatcat:sh6t2mpph5eszctwfahh5pv3p4

Comment

Jingxiang Chen, Yufeng Liu, Donglin Zeng, Rui Song, Yingqi Zhao, Michael R. Kosorok
2016 Journal of the American Statistical Association  
Xu, Müller, Wahed, and Thall proposed a Bayesian model to analyze an acute leukemia study involving multi-stage chemotherapy regimes.  ...  The numerical studies show that these methods can be flexible and have advantages in some situations to handle treatment heterogeneity while being robust to model misspecification.  ...  We would also like to point out some recent literature for dynamic treatment regimes for survival outcomes.  ... 
doi:10.1080/01621459.2016.1200914 pmid:28003710 pmcid:PMC5167482 fatcat:xsnqgk57qjbendefjg27dgbkey

Tree-based reinforcement learning for estimating optimal dynamic treatment regimes

Yebin Tao, Lu Wang, Daniel Almirall
2018 Annals of Applied Statistics  
With the proposed method, we identify dynamic SUD treatment regimes for adolescents.  ...  Dynamic treatment regimes (DTRs) are sequences of treatment decision rules, in which treatment may be adapted over time in response to the changing course of an individual.  ...  The authors thank the grantees and their participants for agreeing to share their data to support the development of the statistical methodology.  ... 
doi:10.1214/18-aoas1137 pmid:30984321 pmcid:PMC6457899 fatcat:ro26iocfu5cqzowa6xjqf3ifky
« Previous Showing results 1 — 15 out of 69,080 results