Prediction regions for the visualization of incomplete datasets

Article


Dybowski, Richard and Weller, Peter 2001. Prediction regions for the visualization of incomplete datasets. Computational Statistics. 16 (1), pp. 25-41.
AuthorsDybowski, Richard and Weller, Peter
Abstract

A complication in the visualization of biomedical datasets is that they are often incomplete. A response to this is to multiply impute each missing datum prior to visualization in order to convey the uncertainty of the imputations. In our approach, the initially complete cases in a real-valued dataset are represented as points in a principal components plot and, for each initially incomplete case in the dataset, we use an associated prediction region or interval displayed on the same plot to indicate the probable location of
the case. When a case has only one missing datum, a prediction interval is used in place of a region. The prediction region or interval associated with an incomplete case is determined from the dispersion of the multiple imputations of the case mapped onto the plot. We illustrate this approach
with two incomplete datasets: the first is based on two multivariate normal
distributions; the second on a published, simulated health survey.

KeywordsVisualization; Multiple imputation; Prediction regions; MANET; XGobi
JournalComputational Statistics
Journal citation16 (1), pp. 25-41
ISSN0943-4062
Year2001
Accepted author manuscript
License
CC BY-ND
Web address (URL)http://hdl.handle.net/10552/365
Publication dates
Print2001
Publication process dates
Deposited02 Nov 2009
Additional information

Citation:
Dybowski R, Weller P. (2001) "Prediction regions for the visualization of incomplete datasets". Computational Statistics 16 (1) 25-41.

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