IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v69y2013i1p293-293.html
   My bibliography  Save this article

Targeted Learning by VAN DER LAAN, M. and ROSE, S

Author

Listed:
  • Andrea Rotnitzky

Abstract

No abstract is available for this item.

Suggested Citation

  • Andrea Rotnitzky, 2013. "Targeted Learning by VAN DER LAAN, M. and ROSE, S," Biometrics, The International Biometric Society, vol. 69(1), pages 293-293, March.
    • Handle: RePEc:bla:biomet:v:69:y:2013:i:1:p:293-293
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/biom.12030
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Vaart,A. W. van der, 2000. "Asymptotic Statistics," Cambridge Books, Cambridge University Press, number 9780521784504, January.
    Full references (including those not matched with items on IDEAS)

    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.
    1. Susan Athey & Guido W. Imbens, 2017. "The State of Applied Econometrics: Causality and Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
    2. Shu Yang & Yunshu Zhang, 2023. "Multiply robust matching estimators of average and quantile treatment effects," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(1), pages 235-265, March.
    3. Torben Martinussen & Mats Julius Stensrud, 2023. "Estimation of separable direct and indirect effects in continuous time," Biometrics, The International Biometric Society, vol. 79(1), pages 127-139, March.
    4. Xinyu Li & Wang Miao & Fang Lu & Xiao‐Hua Zhou, 2023. "Improving efficiency of inference in clinical trials with external control data," Biometrics, The International Biometric Society, vol. 79(1), pages 394-403, March.
    5. Budhi Arta Surya, 2021. "Some results on maximum likelihood from incomplete data: finite sample properties and improved M-estimator for resampling," Papers 2108.01243, arXiv.org, revised Jul 2022.
    6. Sant’Anna, Pedro H.C. & Zhao, Jun, 2020. "Doubly robust difference-in-differences estimators," Journal of Econometrics, Elsevier, vol. 219(1), pages 101-122.
    7. Harsh Parikh & Carlos Varjao & Louise Xu & Eric Tchetgen Tchetgen, 2022. "Validating Causal Inference Methods," Papers 2202.04208, arXiv.org, revised Jul 2022.
    8. Ruoxuan Xiong & Allison Koenecke & Michael Powell & Zhu Shen & Joshua T. Vogelstein & Susan Athey, 2021. "Federated Causal Inference in Heterogeneous Observational Data," Papers 2107.11732, arXiv.org, revised Apr 2023.
    9. Laurent Davezies & Xavier D'Haultfoeuille & Yannick Guyonvarch, 2019. "Empirical Process Results for Exchangeable Arrays," Papers 1906.11293, arXiv.org, revised May 2020.
    10. Hamidou Jawara, 2020. "Access to savings and household welfare evidence from a household survey in The Gambia," African Development Review, African Development Bank, vol. 32(2), pages 138-149, June.
    11. Wei, Kecheng & Qin, Guoyou & Zhang, Jiajia & Sui, Xuemei, 2022. "Doubly robust estimation in causal inference with missing outcomes: With an application to the Aerobics Center Longitudinal Study," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
    12. Bryan S. Graham & Keisuke Hirano, 2011. "Robustness to Parametric Assumptions in Missing Data Models," American Economic Review, American Economic Association, vol. 101(3), pages 538-543, May.
    13. Alexander Frankel & Maximilian Kasy, 2022. "Which Findings Should Be Published?," American Economic Journal: Microeconomics, American Economic Association, vol. 14(1), pages 1-38, February.
    14. Jelena Bradic & Weijie Ji & Yuqian Zhang, 2021. "High-dimensional Inference for Dynamic Treatment Effects," Papers 2110.04924, arXiv.org, revised May 2023.
    15. Corder Nathan & Yang Shu, 2020. "Estimating Average Treatment Effects Utilizing Fractional Imputation when Confounders are Subject to Missingness," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 249-271, January.
    16. repec:diw:diwwpp:dp1630 is not listed on IDEAS
    17. Kasy, Maximilian, 2011. "A nonparametric test for path dependence in discrete panel data," Economics Letters, Elsevier, vol. 113(2), pages 172-175.
    18. Graham, Bryan S. & Hahn, Jinyong & Poirier, Alexandre & Powell, James L., 2018. "A quantile correlated random coefficients panel data model," Journal of Econometrics, Elsevier, vol. 206(2), pages 305-335.
    19. Schweer, Sebastian & Wichelhaus, Cornelia, 2020. "Nonparametric estimation of the service time distribution in discrete-time queueing networks," Stochastic Processes and their Applications, Elsevier, vol. 130(8), pages 4643-4666.
    20. Jan Marcus, 2014. "Does Job Loss Make You Smoke and Gain Weight?," Economica, London School of Economics and Political Science, vol. 81(324), pages 626-648, October.
    21. Zetterqvist, Johan & Waernbaum, Ingeborg, 2020. "Semi-parametric estimation of multi-valued treatment effects for the treated:estimating equations and sandwich estimators," Working Paper Series 2020:4, IFAU - Institute for Evaluation of Labour Market and Education Policy.

    More about this item

    Statistics

    Access and download statistics

    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:69:y:2013:i:1:p:293-293. 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.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.