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Journal of the American Statistical Association Volume 112, 2017 - Issue 517
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Theory and Methods

Conditions for Ignoring the Missing-Data Mechanism in Likelihood Inferences for Parameter Subsets

Roderick J. LittleDepartment of Biostatistics, University of Michigan, Ann Arbor, MI
,
Donald B. RubinDepartment of Statistics, Harvard University, Cambridge, MA
&
Sahar Z. ZangenehVaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA
Pages 314-320 | Received 01 Nov 2013, Published online: 03 May 2017

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Julian Morimoto. (2024) The effect of sample size and missingness on inference with missing data. Communications in Statistics - Theory and Methods 53:9, pages 3292-3311.
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Articles from other publishers (17)

Marie du Roy de Chaumaray & Matthieu Marbac. (2023) Clustering data with non-ignorable missingness using semi-parametric mixture models assuming independence within components. Advances in Data Analysis and Classification 17:4, pages 1081-1122.
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Emilien Arnaud, Mahmoud Elbattah, Christine Ammirati, Gilles Dequen & Daniel Aiham Ghazali. (2023) Predictive models in emergency medicine and their missing data strategies: a systematic review. npj Digital Medicine 6:1.
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Sahar Z. Zangeneh & Roderick J. Little. (2022) Likelihood‐Based Inference for the Finite Population Mean with Post‐Stratification Information Under Non‐Ignorable Non‐Response. International Statistical Review 90:S1.
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Subhra Sankar Dhar & Ujjwal Das. (2021) On distance based goodness of fit tests for missing data when missing occurs at random. Australian & New Zealand Journal of Statistics 63:2, pages 331-356.
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Roderick J. Little. (2021) Missing Data Assumptions. Annual Review of Statistics and Its Application 8:1, pages 89-107.
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Xi Wang & Vernon M. Chinchilli. (2020) Analysis of crossover designs with nonignorable dropout. Statistics in Medicine 40:1, pages 64-84.
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Alicia Garcia-Alvarez, Corbin A Cunningham, Byron Mui, Lia Penn, Erin M Spaulding, J Michael Oakes, Jasmin Divers, Stephanie L Dickinson, Xiao Xu & Lawrence J Cheskin. (2020) A randomized, placebo-controlled crossover trial of a decaffeinated energy drink shows no significant acute effect on mental energy. The American Journal of Clinical Nutrition 111:3, pages 719-727.
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Stuart G. Baker. (2019) Maximum likelihood estimation with missing outcomes: From simplicity to complexity. Statistics in Medicine 38:22, pages 4453-4474.
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Roderick Little & Donald Rubin. 2019. Statistical Analysis with Missing Data, Third Edition. Statistical Analysis with Missing Data, Third Edition 405 428 .
Matthias von Davier, Youngmi Cho & Tianshu Pan. (2019) Effects of Discontinue Rules on Psychometric Properties of Test Scores. Psychometrika 84:1, pages 147-163.
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Claudia Di Caterina, Giuliana Cortese & Nicola Sartori. (2019) Monte Carlo modified profile likelihood in models for clustered data. Electronic Journal of Statistics 13:1.
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Zhichao Jiang & Peng Ding. (2018) Using missing types to improve partial identification with application to a study of HIV prevalence in Malawi. The Annals of Applied Statistics 12:3.
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Mina Fahimi Pirehgalin & Birgit Vogel-Heuser. (2018) Estimation of Missing Values in Incomplete Industrial Process Data Sets Using ECM Algorithm. Estimation of Missing Values in Incomplete Industrial Process Data Sets Using ECM Algorithm.
Iris Weiß & Birgit Vogel-Heuser. (2018) Assessment of variance & distribution in data for effective use of statistical methods for product quality prediction. at - Automatisierungstechnik 66:4, pages 344-355.
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Emma D. Wilson, Quentin Clairon, Robin Henderson & C. James Taylor. (2018) Dealing with observational data in control. Annual Reviews in Control 46, pages 94-106.
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Yuzhe Liu & Vanathi Gopalakrishnan. (2017) An Overview and Evaluation of Recent Machine Learning Imputation Methods Using Cardiac Imaging Data. Data 2:1, pages 8.
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Roderick J. Little. 2014. Wiley StatsRef: Statistics Reference Online. Wiley StatsRef: Statistics Reference Online 1 5 .

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