Literature DB >> 7949939

Multiple imputation as a missing data machine.

J Brand1, S van Buuren, E M van Mulligen, T Timmers, E Gelsema.   

Abstract

This paper deals with problems concerning missing data in clinical databases. After signalling some shortcomings of popular solutions to incomplete data problems, we outline the concepts behind multiple imputation. Multiple imputation is a statistically sound method for handling incomplete data. Application of multiple imputation requires a lot of work and not every user is able to do this. A transparent implementation of multiple imputation is necessary. Such an implementation is possible in the HERMES medical workstation. A remaining problem is to find proper imputations.

Mesh：

Year:  1994        PMID： 7949939      PMCID： PMC2247969     

Source DB:  PubMed          Journal:  Proc Annu Symp Comput Appl Med Care        ISSN： 0195-4210


  1 in total

1.  A new architecture for integration of heterogeneous software components.

Authors:  E M van Mulligen; T Timmers; J H van Bemmel
Journal:  Methods Inf Med       Date:  1993-08       Impact factor: 2.176
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  2 in total

1.  Imputation of missing values of tumour stage in population-based cancer registration.

Authors:  Nora Eisemann; Annika Waldmann; Alexander Katalinic
Journal:  BMC Med Res Methodol       Date:  2011-09-19       Impact factor: 4.615

2.  Multiple Imputation to Deal with Missing Clinical Data in Rheumatologic Surveys: an Application in the WHO-ILAR COPCORD Study in Iran.

Authors:  M Mirmohammadkhani; A Rahimi Foroushani; F Davatchi; K Mohammad; A Jamshidi; A Tehrani Banihashemi; K Holakouie Naieni
Journal:  Iran J Public Health       Date:  2012-01-31       Impact factor: 1.429
  2 in total

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