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On the performance of bias-reduction techniques for variance estimation in approximate Bayesian bootstrap imputation

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  • Demirtas, Hakan
  • Arguelles, Lester M.
  • Chung, Hwan
  • Hedeker, Donald

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  • Demirtas, Hakan & Arguelles, Lester M. & Chung, Hwan & Hedeker, Donald, 2007. "On the performance of bias-reduction techniques for variance estimation in approximate Bayesian bootstrap imputation," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 4064-4068, May.
    • Handle: RePEc:eee:csdana:v:51:y:2007:i:8:p:4064-4068
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    References listed on IDEAS

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    1. Michael Parzen & Stuart R. Lipsitz & Garrett M. Fitzmaurice, 2005. "A note on reducing the bias of the approximate Bayesian bootstrap imputation variance estimator," Biometrika, Biometrika Trust, vol. 92(4), pages 971-974, December.
    2. J. K. Kim, 2002. "A note on approximate Bayesian bootstrap imputation," Biometrika, Biometrika Trust, vol. 89(2), pages 470-477, June.
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    1. repec:jss:jstsof:29:i09 is not listed on IDEAS
    2. Siddique, Juned & Belin, Thomas R., 2008. "Using an Approximate Bayesian Bootstrap to multiply impute nonignorable missing data," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 405-415, December.
    3. Bailey, Michael & Hopkins, Daniel J. & Rogers, Todd, 2013. "Unresponsive and Unpersuaded: The Unintended Consequences of Voter Persuasion Efforts," Working Paper Series rwp13-034, Harvard University, John F. Kennedy School of Government.
    4. Hakan Demirtas & Robab Ahmadian & Sema Atis & Fatma Ezgi Can & Ilker Ercan, 2016. "A nonnormal look at polychoric correlations: modeling the change in correlations before and after discretization," Computational Statistics, Springer, vol. 31(4), pages 1385-1401, December.
    5. Demirtas, Hakan, 2008. "On imputing continuous data when the eventual interest pertains to ordinalized outcomes via threshold concept," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 2261-2271, January.
    6. Pendharkar, Parag C., 2008. "Maximum entropy and least square error minimizing procedures for estimating missing conditional probabilities in Bayesian networks," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3583-3602, March.

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