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Statistical Practice

Bias Reduction in Logistic Regression with Missing Responses When the Missing Data Mechanism is Nonignorable

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Pages 340-349 | Received 01 Dec 2016, Published online: 09 Jul 2018

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Read on this site (2)

Muna Al Shaaibi & Ronald Wesonga. (2021) Bias dynamics for parameter estimation with missing data mechanisms under logistic model. Journal of Statistics and Management Systems 24:4, pages 873-894.
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Irene Epifanio, M. Victoria Ibáñez & Amelia Simó. (2020) Archetypal Analysis With Missing Data: See All Samples by Looking at a Few Based on Extreme Profiles. The American Statistician 74:2, pages 169-183.
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Articles from other publishers (9)

Yuan Bian, Grace Y. Yi & Wenqing He. (2024) A unified framework of analyzing missing data and variable selection using regularized likelihood. Computational Statistics & Data Analysis 194, pages 107919.
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Majid Mojirsheibani, William Pouliot & Andre Shakhbandaryan. (2023) On regression and classification with possibly missing response variables in the data. Metrika.
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Muna Al-Shaaibi & Ronald Wesonga. (2022) Bias reduction in the logistic model parameters with the LogF(1,1) penalty under MAR assumption. Frontiers in Applied Mathematics and Statistics 8.
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Majid Mojirsheibani. (2022) On the maximal deviation of kernel regression estimators with NMAR response variables. Statistical Papers 63:5, pages 1677-1705.
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Veronica M. White, Sebastian Alvarez Avendano, Laura A. Albert, Aleksandra E. Zgierska, Captain Joe Balles & Gabriel Zayas-Cabán. (2021) Impact of a community-policing initiative promoting substance use disorder treatment over criminal charges on arrest recidivism. Drug and Alcohol Dependence 227, pages 108915.
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Brady T. West, Roderick J. Little, Rebecca R. Andridge, Philip S. Boonstra, Erin B. Ware, Anita Pandit & Fernanda Alvarado-Leiton. (2021) Assessing selection bias in regression coefficients estimated from nonprobability samples with applications to genetics and demographic surveys. The Annals of Applied Statistics 15:3.
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Majid Mojirsheibani. (2021) On classification with nonignorable missing data. Journal of Multivariate Analysis 184, pages 104755.
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Chunhua Chen, Jianwei Ren, Lijun Tang & Haohua Liu. (2020) Additive integer-valued data envelopment analysis with missing data: A multi-criteria evaluation approach. PLOS ONE 15:6, pages e0234247.
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Kristin Gustavson, Espen Røysamb & Ingrid Borren. (2019) Preventing bias from selective non-response in population-based survey studies: findings from a Monte Carlo simulation study. BMC Medical Research Methodology 19:1.
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