Bayesian nonparametric estimation of targeted agent effects on biomarker change to predict clinical outcome (English)
- New search for: Graziani, Rebecca
- New search for: Graziani, Rebecca
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In:
Biometrics
;
71
, 1
; 188-197
;
2015
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ISSN:
- Article (Journal) / Print
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Title:Bayesian nonparametric estimation of targeted agent effects on biomarker change to predict clinical outcome
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Contributors:
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Published in:Biometrics ; 71, 1 ; 188-197
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Publisher:
- New search for: Blackwell
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Place of publication:Malden, Mass. [u.a.]
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Publication date:2015
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ISSN:
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ZDBID:
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DOI:
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Type of media:Article (Journal)
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Type of material:Print
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Language:English
- New search for: 42.11 / 42.11
- Further information on Basic classification
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Keywords:
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Classification:
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Source:
Table of contents – Volume 71, Issue 1
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 1
-
Causal mediation analysis with multiple mediatorsDaniel, R. M et al. | 2015
- 15
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On the relationship between the causal-inference and meta-analytic paradigms for the validation of surrogate endpointsAriel Alonso et al. | 2015
- 25
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Estimation of treatment effects in all-comers randomized clinical trials with a predictive markerYuki Choai et al. | 2015
- 33
-
Minimum clinically important difference in medical studiesHedayat, A. S et al. | 2015
- 42
-
Case-base methods for studying vaccination safetyOlli Saarela et al. | 2015
- 53
-
Group variable selection via convex log‐exp‐sum penalty with application to a breast cancer survivor studyGeng, Zhigeng et al. | 2015
- 63
-
Sparse kernel machine regression for ordinal outcomesShen, Yuanyuan et al. | 2015
- 71
-
Regression analysis of mixed recurrent‐event and panel‐count data with additive rate modelsZhu, Liang et al. | 2015
- 80
-
A discrete time event‐history approach to informative drop‐out in mixed latent Markov models with covariatesBartolucci, Francesco et al. | 2015
- 90
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A joint model for multistate disease processes and random informative observation times, with applications to electronic medical records dataLange, Jane M et al. | 2015
- 102
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Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time-to-event in presence of censoring and competing risksPaul Blanche et al. | 2015
- 114
-
Disease risk estimation by combining case–control data with aggregated information on the population at riskChang, Xiaohui et al. | 2015
- 122
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Instrumental variable additive hazards modelsJialiang Li et al. | 2015
- 131
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On the selection of ordinary differential equation models with application to predator-prey dynamical modelsXinyu Zhang et al. | 2015
- 139
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An alternative approach to confidence interval estimation for the win ratio statisticLuo, Xiaodong et al. | 2015
- 146
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Combining one-sample confidence procedures for inference in the two-sample caseMichael P Fay et al. | 2015
- 157
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Testing the mean matrix in high‐dimensional transposable dataTouloumis, Anestis et al. | 2015
- 167
-
Spatial variable selection methods for investigating acute health effects of fine particulate matter componentsLaura F Boehm Vock et al. | 2015
- 178
-
Simultaneous variable selection for joint models of longitudinal and survival outcomesZangdong He et al. | 2015
- 188
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Bayesian nonparametric estimation of targeted agent effects on biomarker change to predict clinical outcomeGraziani, Rebecca et al. | 2015
- 198
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Model choice problems using approximate Bayesian computation with applications to pathogen transmission data setsLee, Xing Ju et al. | 2015
- 208
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A Bayesian approach to estimate the biomass of anchovies off the coast of PerúZaida C Quiroz et al. | 2015
- 218
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Bayesian designs and the control of frequentist characteristics: A practical solutionVentz, Steffen et al. | 2015
- 227
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On the analysis of hybrid designs that combine group‐ and individual‐level dataSmoot, E et al. | 2015
- 237
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Computational aspects of N‐mixture modelsDennis, Emily B et al. | 2015
- 247
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Structured functional principal component analysisHaochang Shou et al. | 2015
- 258
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Estimating the size of populations at high risk for HIV using respondent-driven sampling dataMark S Handcock et al. | 2015
- 267
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Reader reaction to “A robust method for estimating optimal treatment regimes” by Zhang et al. (2012)Taylor, Jeremy M. G et al. | 2015
- 267
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Response to reader reaction| 2015
- fmvii
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Report of the editors—2014| 2015