Show simple item record

dc.contributor.authorScheffer, Judi
dc.date.accessioned2013-05-07T21:26:47Z
dc.date.available2013-05-07T21:26:47Z
dc.date.issued2002
dc.identifier.citationScheffer, J. (2002), Dealing with missing data, Research Letters in the Information and Mathematical Sciences, 3, 153-160en
dc.identifier.issn1175-2777
dc.identifier.urihttp://hdl.handle.net/10179/4355
dc.description.abstractWhat is done with missing data? Does the missingness mechanism matter? Is it a good idea to just use the default options in the major statistical packages? Even some highly trained statisticians do this, so can the non-statistician analysing their own data cope with some of the better techniques for handling missing data? This paper shows how the mean and standard deviation are affected by different methods of imputation, given different missingness mechanisms. Better options than the standard default options are available in the major statistical software, offering the chance to 'do the right thing' to the statistical and non-statistical community alike.en
dc.language.isoenen
dc.publisherMassey Universityen
dc.subjectMissing dataen
dc.subjectSurveysen
dc.titleDealing with missing dataen
dc.typeArticleen


Files in this item

Icon

This item appears in the following Collection(s)

Show simple item record