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Multiple imputation of missing values: update
Royston, Patrick - In: Stata Journal 5 (2005) 2, pp. 188-201
This article describes a substantial update to mvis, which brings it more closely in line with the feature set of S …://www.multiple-imputation.com). To make a clear distinction from mvis,the principal program of the new Stata release is called ice. I will give details … of how to use the new features and a practical illustrative example using real data. All the facilities of mvis are …
Persistent link: https://www.econbiz.de/10005568782
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Multiple imputation of missing values: further update of ice, with an emphasis on interval censoring
Royston, Patrick - In: Stata Journal 7 (2007) 4, pp. 445-464
Multiple imputation of missing data continues to be a topic of considerable interest and importance to applied researchers. In this article, the ice package for multiple imputation is further updated. Special attention in this article is paid to imputing interval-censored observations, and a...
Persistent link: https://www.econbiz.de/10005450169
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A new framework for managing and analyzing multiply imputed data in Stata
Carlin, John B.; Galati, John C.; Royston, Patrick - In: Stata Journal 8 (2008) 1, pp. 49-67
and micombine commands. Stacking into a single dataset simplifies the management of the imputed datasets compared with …
Persistent link: https://www.econbiz.de/10005583254
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Missing data : better "not to have them" but what if you do?, part 1
Temme, Dirk; Jensen, Sarah - In: Marketing : ZFP ; journal of research and management 41 (2019) 4, pp. 21-32
Persistent link: https://www.econbiz.de/10012149201
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Multiple imputation of missing values: New features for mim
Royston, Patrick; Carlin, John B.; White, Ian R. - In: Stata Journal 9 (2009) 2, pp. 252-264
We present an update of mim, a program for managing multiply im- puted datasets and performing inference (estimating parameters) using Rubin’s rules for combining estimates from imputed datasets. The new features of particular importance are an option for estimating the Monte Carlo error (due...
Persistent link: https://www.econbiz.de/10004964302
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Diagnostics for multiple imputation in Stata
Eddings, Wesley; Marchenko, Yulia - In: Stata Journal 12 (2012) 3, pp. 353-367
Our new command midiagplots makes diagnostic plots for multiple imputations created by mi impute. The plots compare the distribution of the imputed values with that of the observed values so that problems with the imputation model can be corrected before the imputed data are analyzed. We include...
Persistent link: https://www.econbiz.de/10010631452
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Analysis of partially observed clustered data using generalized estimating equations and multiple imputation
Aloisio, Kathryn M.; Swanson, Sonja A.; Micali, Nadia; … - In: Stata Journal 14 (2014) 4, pp. 863-883
Clustered data arise in many settings, particularly within the social and biomedical sciences. For example, multiple-source reports are commonly collected in child and adolescent psychiatric epidemiologic studies where researchers use various informants (for instance, parents and adolescents) to...
Persistent link: https://www.econbiz.de/10011105649
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Multiple imputation of missing values: Further update of ice, with an emphasis on categorical variables
Royston, Patrick - In: Stata Journal 9 (2009) 3, pp. 466-477
Multiple imputation of missing data continues to be a topic of considerable interest and importance to applied researchers. In this article, the ice package for multiple imputation by chained equations (also known as fully con- ditional specification) is further updated. Special attention is...
Persistent link: https://www.econbiz.de/10008619654
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Semiparametric Estimators for the Regression Coefficients inthe Linear Transformation Competing Risks Models with Missing Causeof Failure
Gao, Guozhi - 2006
In many clinical studies, researchers are mainly interested in studying the effects of some prognostic factors on the hazard of failure from a specific cause while individuals may failure from multiple causes. This leads to a competing risks problem. Often, due to various reasons such as finite...
Persistent link: https://www.econbiz.de/10009431243
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A novel approach for imputation of missing continuous attribute values in databases using genetic algorithm
Devi Priya, R.; Kuppuswami, S. - In: International journal of information technology and … 14 (2015) 2/3, pp. 185-200
Persistent link: https://www.econbiz.de/10011526987