Modeling the impact of hepatitis C viral clearance on end-stage liver disease in an HIV co-infected cohort with targeted maximum likelihood estimation
Author
Abstract
Suggested Citation
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Xiao Yongling & Abrahamowicz Michal & Moodie Erica E. M., 2010. "Accuracy of Conventional and Marginal Structural Cox Model Estimators: A Simulation Study," The International Journal of Biostatistics, De Gruyter, vol. 6(2), pages 1-30, March.
- van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
- van der Laan Mark J., 2010. "Targeted Maximum Likelihood Based Causal Inference: Part II," The International Journal of Biostatistics, De Gruyter, vol. 6(2), pages 1-33, February.
- Zeileis, Achim, 2006. "Object-oriented Computation of Sandwich Estimators," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 16(i09).
- van der Laan Mark J. & Rubin Daniel, 2006. "Targeted Maximum Likelihood Learning," The International Journal of Biostatistics, De Gruyter, vol. 2(1), pages 1-40, December.
- Gruber Susan & van der Laan Mark J., 2010. "A Targeted Maximum Likelihood Estimator of a Causal Effect on a Bounded Continuous Outcome," The International Journal of Biostatistics, De Gruyter, vol. 6(1), pages 1-18, August.
- Susan M. Shortreed & Erica E. M. Moodie, 2012. "Estimating the optimal dynamic antipsychotic treatment regime: evidence from the sequential multiple-assignment randomized Clinical Antipsychotic Trials of Intervention and Effectiveness schizophrenia," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 61(4), pages 577-599, August.
- Heejung Bang & James M. Robins, 2005. "Doubly Robust Estimation in Missing Data and Causal Inference Models," Biometrics, The International Biometric Society, vol. 61(4), pages 962-973, December.
- van der Laan Mark J. & Gruber Susan, 2012. "Targeted Minimum Loss Based Estimation of Causal Effects of Multiple Time Point Interventions," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-41, May.
- van der Laan Mark J., 2010. "Targeted Maximum Likelihood Based Causal Inference: Part I," The International Journal of Biostatistics, De Gruyter, vol. 6(2), pages 1-45, February.
- L. Taylor & X. H. Zhou, 2009. "Multiple Imputation Methods for Treatment Noncompliance and Nonresponse in Randomized Clinical Trials," Biometrics, The International Biometric Society, vol. 65(1), pages 88-95, March.
- Stitelman Ori M. & De Gruttola Victor & van der Laan Mark J., 2012. "A General Implementation of TMLE for Longitudinal Data Applied to Causal Inference in Survival Analysis," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-39, September.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Philipp Baumann & Enzo Rossi & Michael Schomaker, 2022.
"Estimating the effect of central bank independence on inflation using longitudinal targeted maximum likelihood estimation,"
IFC Bulletins chapters, in: Bank for International Settlements (ed.), Machine learning in central banking, volume 57,
Bank for International Settlements.
- Baumann Philipp F. M. & Schomaker Michael & Rossi Enzo, 2021. "Estimating the effect of central bank independence on inflation using longitudinal targeted maximum likelihood estimation," Journal of Causal Inference, De Gruyter, vol. 9(1), pages 109-146, January.
- Philipp F. M. Baumann & Michael Schomaker & Enzo Rossi, 2020. "Estimating the Effect of Central Bank Independence on Inflation Using Longitudinal Targeted Maximum Likelihood Estimation," Papers 2003.02208, arXiv.org, revised May 2021.
- Lan Wen & Jessica G. Young & James M. Robins & Miguel A. Hernán, 2021. "Parametric g‐formula implementations for causal survival analyses," Biometrics, The International Biometric Society, vol. 77(2), pages 740-753, June.
- Lan Wen & Miguel A. Hernán & James M. Robins, 2022. "Multiply robust estimators of causal effects for survival outcomes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 1304-1328, September.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Susan Gruber & Mark J. van der Laan, 2013. "An Application of Targeted Maximum Likelihood Estimation to the Meta-Analysis of Safety Data," Biometrics, The International Biometric Society, vol. 69(1), pages 254-262, March.
- Iván Díaz & Elizabeth Colantuoni & Daniel F. Hanley & Michael Rosenblum, 2019. "Improved precision in the analysis of randomized trials with survival outcomes, without assuming proportional hazards," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(3), pages 439-468, July.
- Frölich, Markus & Huber, Martin & Wiesenfarth, Manuel, 2017.
"The finite sample performance of semi- and non-parametric estimators for treatment effects and policy evaluation,"
Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 91-102.
- Frölich, Markus & Huber, Martin & Wiesenfarth, Manuel, 2015. "The finite sample performance of semi- and nonparametric estimators for treatment effects and policy evaluation," FSES Working Papers 454, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
- Frölich, Markus & Huber, Martin & Wiesenfarth, Manuel, 2015. "The Finite Sample Performance of Semi- and Nonparametric Estimators for Treatment Effects and Policy Evaluation," IZA Discussion Papers 8756, Institute of Labor Economics (IZA).
- Hugo Bodory & Martin Huber & Lukáš Lafférs, 2022.
"Evaluating (weighted) dynamic treatment effects by double machine learning [Identification of causal effects using instrumental variables],"
The Econometrics Journal, Royal Economic Society, vol. 25(3), pages 628-648.
- Hugo Bodory & Martin Huber & Luk'av{s} Laff'ers, 2020. "Evaluating (weighted) dynamic treatment effects by double machine learning," Papers 2012.00370, arXiv.org, revised Jun 2021.
- David Benkeser & Keith Horvath & Cathy J. Reback & Joshua Rusow & Michael Hudgens, 2020. "Design and Analysis Considerations for a Sequentially Randomized HIV Prevention Trial," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(3), pages 446-467, December.
- Kara E. Rudolph & Mark J. Laan, 2017. "Robust estimation of encouragement design intervention effects transported across sites," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1509-1525, November.
- Stitelman Ori M & Wester C. William & De Gruttola Victor & van der Laan Mark J., 2011. "Targeted Maximum Likelihood Estimation of Effect Modification Parameters in Survival Analysis," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-34, March.
- Guo, Xu & Fang, Yun & Zhu, Xuehu & Xu, Wangli & Zhu, Lixing, 2018. "Semiparametric double robust and efficient estimation for mean functionals with response missing at random," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 325-339.
- Waverly Wei & Maya Petersen & Mark J van der Laan & Zeyu Zheng & Chong Wu & Jingshen Wang, 2023. "Efficient targeted learning of heterogeneous treatment effects for multiple subgroups," Biometrics, The International Biometric Society, vol. 79(3), pages 1934-1946, September.
- Paul Frédéric Blanche & Anders Holt & Thomas Scheike, 2023. "On logistic regression with right censored data, with or without competing risks, and its use for estimating treatment effects," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(2), pages 441-482, April.
- Yiyi Huo & Yingying Fan & Fang Han, 2023. "On the adaptation of causal forests to manifold data," Papers 2311.16486, arXiv.org, revised Dec 2023.
- Kara E. Rudolph & Jonathan Levy & Mark J. van der Laan, 2021. "Transporting stochastic direct and indirect effects to new populations," Biometrics, The International Biometric Society, vol. 77(1), pages 197-211, March.
- Gruber Susan & van der Laan Mark J., 2010. "An Application of Collaborative Targeted Maximum Likelihood Estimation in Causal Inference and Genomics," The International Journal of Biostatistics, De Gruyter, vol. 6(1), pages 1-31, May.
- Antonelli Joseph & Cefalu Matthew, 2020. "Averaging causal estimators in high dimensions," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 92-107, January.
- Jacob, Daniel, 2021. "CATE meets ML: Conditional average treatment effect and machine learning," IRTG 1792 Discussion Papers 2021-005, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Zhiwei Zhang & Zhen Chen & James F. Troendle & Jun Zhang, 2012. "Causal Inference on Quantiles with an Obstetric Application," Biometrics, The International Biometric Society, vol. 68(3), pages 697-706, September.
- Rose Sherri & van der Laan Mark J., 2011. "A Targeted Maximum Likelihood Estimator for Two-Stage Designs," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-21, March.
- Zheng Wenjing & van der Laan Mark J., 2012. "Targeted Maximum Likelihood Estimation of Natural Direct Effects," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-40, January.
- Philipp Baumann & Enzo Rossi & Michael Schomaker, 2022.
"Estimating the effect of central bank independence on inflation using longitudinal targeted maximum likelihood estimation,"
IFC Bulletins chapters, in: Bank for International Settlements (ed.), Machine learning in central banking, volume 57,
Bank for International Settlements.
- Baumann Philipp F. M. & Schomaker Michael & Rossi Enzo, 2021. "Estimating the effect of central bank independence on inflation using longitudinal targeted maximum likelihood estimation," Journal of Causal Inference, De Gruyter, vol. 9(1), pages 109-146, January.
- Philipp F. M. Baumann & Michael Schomaker & Enzo Rossi, 2020. "Estimating the Effect of Central Bank Independence on Inflation Using Longitudinal Targeted Maximum Likelihood Estimation," Papers 2003.02208, arXiv.org, revised May 2021.
- repec:jss:jstsof:43:i13 is not listed on IDEAS
- Veronica Sciannameo & Gian Paolo Fadini & Daniele Bottigliengo & Angelo Avogaro & Ileana Baldi & Dario Gregori & Paola Berchialla, 2022. "Assessment of Glucose Lowering Medications’ Effectiveness for Cardiovascular Clinical Risk Management of Real-World Patients with Type 2 Diabetes: Targeted Maximum Likelihood Estimation under Model Mi," IJERPH, MDPI, vol. 19(22), pages 1-13, November.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:biomet:v:70:y:2014:i:1:p:144-152. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.