A Simple Method for Estimating Interactions between a Treatment and a Large Number of Covariates.
about
Lasso adjustments of treatment effect estimates in randomized experiments.Recursive partitioning for heterogeneous causal effectsGreedy outcome weighted tree learning of optimal personalized treatment rules.An NGS Workflow Blueprint for DNA Sequencing Data and Its Application in Individualized Molecular Oncology.Tutorial in biostatistics: data-driven subgroup identification and analysis in clinical trials.The Use of Covariates and Random Effects in Evaluating Predictive Biomarkers Under a Potential Outcome Framework.Using decision lists to construct interpretable and parsimonious treatment regimes.Evaluation of Alcohol-Related Personalized Normative Feedback With and Without an Injunctive Message.Flexible functional regression methods for estimating individualized treatment regimes.Incorporating Patient Preferences into Estimation of Optimal Individualized Treatment Rules.Multi-subgroup gene screening using semi-parametric hierarchical mixture models and the optimal discovery procedure: Application to a randomized clinical trial in multiple myeloma.A general statistical framework for subgroup identification and comparative treatment scoring.Patient subgroup identification for clinical drug development.Post hoc subgroups in clinical trials: Anathema or analytics?Identification of biomarker-by-treatment interactions in randomized clinical trials with survival outcomes and high-dimensional spaces.Testing interaction between treatment and high-dimensional covariates in randomized clinical trials.New methods for treatment effect calibration, with applications to non-inferiority trials.Data Shared Lasso: A Novel Tool to Discover UpliftDOUBLY ROBUST ESTIMATION OF OPTIMAL TREATMENT REGIMES FOR SURVIVAL DATA-WITH APPLICATION TO AN HIV/AIDS STUDY.Individual treatment effect prediction for amyotrophic lateral sclerosis patients.C-learning: A new classification framework to estimate optimal dynamic treatment regimes.A simulation study on estimating biomarker-treatment interaction effects in randomized trials with prognostic variables.Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting.Some methods for heterogeneous treatment effect estimation in high dimensions.Identification of subpopulations with distinct treatment benefit rate using the Bayesian tree.Statistical Analysis Plan for Stage 1 EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care) Study.Innovative methods for the identification of predictive biomarker signatures in oncology: Application to bevacizumab.
P2860
Q27320776-DDAC7D90-D369-47DD-8AC5-7951C06595C1Q27320968-971EEF25-9396-4337-B4C3-34B02F4F1C79Q30843804-0D51BEA7-50EB-4BA0-8D40-476F984272A1Q31077769-E5CA0708-A967-4344-9B3E-B70782D4A686Q31119441-27506721-FE08-4038-ABBD-897D48F69B8EQ36467574-E8174082-F05C-4FE5-88E7-8861957472F0Q36470116-03775239-1544-45DA-83B0-DAEBC7E90042Q36717471-68508E80-0CAB-462C-808A-8823E192871DQ38606271-2D960A04-48A8-4851-9C3D-318F215BCE48Q38662474-10A877CB-EAC4-4555-91F6-817EE06B58B7Q38789383-F869CFF1-427B-4A61-A7A4-2E89E68A4989Q38955394-473A5462-3D6C-4F40-BEFB-21F9C0896EEFQ38986237-520125CD-5EF5-48B5-8562-66C33FF254C5Q38997037-62A55E3A-BAA0-431B-82B4-5DFF7468405FQ39175273-984C79CE-E4C3-4F8E-B896-701CC7BB90E3Q39267252-69A76C84-7B1F-428B-9377-73C025C56E88Q40545878-9620A213-469C-41E8-B28B-602DA8DFBD6FQ42698240-161E8A71-2C6D-4DAA-8647-CBAFA19B80ECQ47178726-AA6050ED-8D6F-4EFE-8B9A-AAC267AD226BQ47213485-93F891C3-6BFA-478E-9ED7-4414F9ABE193Q47580192-75DD9590-66AF-49B8-BB76-04F4E4001BE5Q49795733-B16972CC-9B33-4758-9B2E-AA100D8A3923Q49905853-502F27F0-4B06-4B74-8A77-9B5BE26DC00CQ50420714-24A69936-0C0A-4227-8386-A2F75F838A98Q50555961-D2376CCE-C910-4269-950E-D840541AEC9DQ52089873-ECD7984F-57E4-47BE-BEA7-93B162C2A280Q55005400-64714C36-9A95-4837-9965-E068F2636C78
P2860
A Simple Method for Estimating Interactions between a Treatment and a Large Number of Covariates.
description
2014 nî lūn-bûn
@nan
2014 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի հոտեմբերին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
name
A Simple Method for Estimating ...... a Large Number of Covariates.
@ast
A Simple Method for Estimating ...... a Large Number of Covariates.
@en
type
label
A Simple Method for Estimating ...... a Large Number of Covariates.
@ast
A Simple Method for Estimating ...... a Large Number of Covariates.
@en
prefLabel
A Simple Method for Estimating ...... a Large Number of Covariates.
@ast
A Simple Method for Estimating ...... a Large Number of Covariates.
@en
P2093
P2860
P1476
A Simple Method for Estimating ...... a Large Number of Covariates.
@en
P2093
Andrew J Gentles
Ash A Alizadeh
P2860
P304
P356
10.1080/01621459.2014.951443
P407
P577
2014-10-01T00:00:00Z