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Title of Journal: Intensive Care Med

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Abbravation: Intensive Care Medicine

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Springer Berlin Heidelberg

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DOI

10.1007/s11852-008-0040-9

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1432-1238

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Reporting and handling missing values in clinical

Authors: Aurélien Vesin Elie Azoulay Stéphane Ruckly Lucile Vignoud Kateřina Rusinovà Dominique Benoit Marcio Soares Paulo AzeivedoMaia Fekri Abroug Judith Benbenishty Jean Francois Timsit
Publish Date: 2013/05/18
Volume: 39, Issue: 8, Pages: 1396-1404
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Abstract

Missing values occur in nearly all clinical studies despite the best efforts of the investigators and cause frequently unrecognised biases Our aims were 1 to assess the reporting and handling of missing values in the critical care literature 2 to describe the impact of various techniques for handling missing values on the study results 3 to provide guidance on the management of clinical study analysis in case of missing dataAmong 44 published manuscripts 16 364  provided no information on whether missing data occurred 6 136  declared having no missing data 20 455  reported that missing values occurred but did not handle them and only 2 45  used sophisticated missing data handling methods In our example using the Conflicus study database we evaluated correlations linking job strain intensity to the type and proportion of missing values Overall 8  of data were missing however using only complete cases would have resulted in discarding 24  of the questionnaires A greater number and a higher percentage of missing values for a particular variable were significantly associated with a lower job strain score indicating greater stress Among respondents who fully completed the job strain questionnaire the comparison of those whose questionnaires did and did not have missing values showed significant differences in terms of age number of children and country of birth We provided an algorithm to manage clinical studies analysis in case of missing data

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