White, IR;
Audigier, V;
Jolani, S;
Debray, T;
Quartagno, M;
Carpenter, J;
van Buuren, S;
(2018)
Multiple imputation for multilevel data with continuous and binary variables.
Statistical Science
, 33
(2)
pp. 160-183.
10.1214/18-STS646.
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Abstract
We present and compare multiple imputation methods for multilevel continuous and binary data where variables are systematically and sporadically missing. The methods are compared from a theoretical point of view and through an extensive simulation study motivated by a real dataset comprising multiple studies. The comparisons show that these multiple imputation methods are the most appropriate to handle missing values in a multilevel setting and why their relative performances can vary according to the missing data pattern, the multilevel structure and the type of missing variables. This study shows that valid inferences can only be obtained if the dataset includes a large number of clusters. In addition, it highlights that heteroscedastic multiple imputation methods provide more accurate inferences than homoscedastic methods, which should be reserved for data with few individuals per cluster. Finally, guidelines are given to choose the most suitable multiple imputation method according to the structure of the data.
| Type: | Article |
|---|---|
| Title: | Multiple imputation for multilevel data with continuous and binary variables |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1214/18-STS646 |
| Publisher version: | http://dx.doi.org/10.1214/18-STS646 |
| Language: | English |
| Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Missing data, systematically missing values, multilevel data, mixed data, multiple imputation, joint modelling, fully conditional specification |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology > MRC Clinical Trials Unit at UCL |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10047904 |
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