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Journal ArticleDOI

Statistical Analysis with Missing Data

Martin G. Gibson
- 01 Mar 1989 - 
- Vol. 38, Iss: 1, pp 82-83
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This article is published in The Statistician.The article was published on 1989-03-01. It has received 3152 citations till now. The article focuses on the topics: Missing data.

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Citations
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mice: Multivariate Imputation by Chained Equations in R

TL;DR: Mice adds new functionality for imputing multilevel data, automatic predictor selection, data handling, post-processing imputed values, specialized pooling routines, model selection tools, and diagnostic graphs.
Journal ArticleDOI

A comparison of inclusive and restrictive strategies in modern missing data procedures.

TL;DR: A simulation was presented to assess the potential costs and benefits of a restrictive strategy, which makes minimal use of auxiliary variables, versus an inclusive strategy,Which shows that the inclusive strategy is to be greatly preferred.
Journal ArticleDOI

Maximum likelihood estimation via the ECM algorithm: A general framework

TL;DR: In many cases, complete-data maximum likelihood estimation is relatively simple when conditional on some function of the parameters being estimated as mentioned in this paper, and convergence is stable, with each iteration increasing the likelihood.
References
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Journal ArticleDOI

mice: Multivariate Imputation by Chained Equations in R

TL;DR: Mice adds new functionality for imputing multilevel data, automatic predictor selection, data handling, post-processing imputed values, specialized pooling routines, model selection tools, and diagnostic graphs.
Journal ArticleDOI

Multitask Learning

TL;DR: Multi-task Learning (MTL) as mentioned in this paper is an approach to inductive transfer that improves generalization by using the domain information contained in the training signals of related tasks as an inductive bias.
Journal ArticleDOI

A comparison of inclusive and restrictive strategies in modern missing data procedures.

TL;DR: A simulation was presented to assess the potential costs and benefits of a restrictive strategy, which makes minimal use of auxiliary variables, versus an inclusive strategy,Which shows that the inclusive strategy is to be greatly preferred.
Journal ArticleDOI

Maximum likelihood estimation via the ECM algorithm: A general framework

TL;DR: In many cases, complete-data maximum likelihood estimation is relatively simple when conditional on some function of the parameters being estimated as mentioned in this paper, and convergence is stable, with each iteration increasing the likelihood.