Calibrated imputation of numerical data under linear edit restrictions
Pannekoek, Jeroen, Shlomo, Natalie and De Waal, Ton (2009) Calibrated imputation of numerical data under linear edit restrictions. Southampton, UK, Southampton Statistical Sciences Research Institute, 25pp. (S3RI Methodology Working Papers, (M09/17) ).
A common problem faced by statistical offices is that data may be missing from collected data sets. The typical way to overcome this problem is to impute the missing data. The problem of imputing missing data is complicated by the fact that statistical data often have to satisfy certain edit rules and that values of variables sometimes have to sum up to known totals. Standard imputation methods for numerical data as described in the literature generally do not take such edit rules and totals into account. In the paper we describe algorithms for imputation of missing numerical data that do take edit restrictions into account and that ensure that sums are calibrated to known totals. The methods sequentially impute the missing data, i.e. the variables with missing values are imputed one by one. To assess the performance of the imputation methods a simulation study is carried out as well as an evaluation study based on a real dataset.
|Item Type:||Monograph (Working Paper)|
|Subjects:||H Social Sciences > HA Statistics|
|Divisions:||University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute
|Date Deposited:||23 Oct 2009|
|Last Modified:||03 Mar 2012 06:50|
|Contributors:||Pannekoek, Jeroen (Author)
Shlomo, Natalie (Author)
De Waal, Ton (Author)
|Date:||23 October 2009|
|Publisher:||Southampton Statistical Sciences Research Institute|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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