MIDAS: A SAS Macro for Multiple Imputation Using Distance-Aided Selection of Donors

MIDAS: A SAS Macro for Multiple Imputation Using Distance-Aided Selection of Donors

In this paper we describe MIDAS: a SAS macro for multiple imputation using distance aided selection of donors which implements an iterative predictive mean matching hot-deck for imputing missing data. This is a flexible multiple imputation approach that can handle data in a variety of formats: conti...

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Main Authors: Juned Siddique, Ofer Harel
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2009-01-01
Series:Journal of Statistical Software
Online Access:http://www.jstatsoft.org/v29/i09/paper
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spelling doaj-ffc9b9a6ab2b46b0a55e4881454b58772020-11-25T00:07:21ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602009-01-01299MIDAS: A SAS Macro for Multiple Imputation Using Distance-Aided Selection of DonorsJuned SiddiqueOfer HarelIn this paper we describe MIDAS: a SAS macro for multiple imputation using distance aided selection of donors which implements an iterative predictive mean matching hot-deck for imputing missing data. This is a flexible multiple imputation approach that can handle data in a variety of formats: continuous, ordinal, and scaled. Because the imputation models are implicit, it is not necessary to specify a parametric distribution for each variable to be imputed. MIDAS also allows the user to address the sensitivity of their inferences to different assumptions concerning the missing data mechanism. An example using MIDAS to impute missing data is presented and MIDAS is compared to existing missing data software.http://www.jstatsoft.org/v29/i09/paper
collection DOAJ
language English
format Article
sources DOAJ
author Juned Siddique
Ofer Harel
spellingShingle Juned Siddique
Ofer Harel
MIDAS: A SAS Macro for Multiple Imputation Using Distance-Aided Selection of Donors
Journal of Statistical Software
author_facet Juned Siddique
Ofer Harel
author_sort Juned Siddique
title MIDAS: A SAS Macro for Multiple Imputation Using Distance-Aided Selection of Donors
title_short MIDAS: A SAS Macro for Multiple Imputation Using Distance-Aided Selection of Donors
title_full MIDAS: A SAS Macro for Multiple Imputation Using Distance-Aided Selection of Donors
title_fullStr MIDAS: A SAS Macro for Multiple Imputation Using Distance-Aided Selection of Donors
title_full_unstemmed MIDAS: A SAS Macro for Multiple Imputation Using Distance-Aided Selection of Donors
title_sort midas: a sas macro for multiple imputation using distance-aided selection of donors
publisher Foundation for Open Access Statistics
series Journal of Statistical Software
issn 1548-7660
publishDate 2009-01-01
description In this paper we describe MIDAS: a SAS macro for multiple imputation using distance aided selection of donors which implements an iterative predictive mean matching hot-deck for imputing missing data. This is a flexible multiple imputation approach that can handle data in a variety of formats: continuous, ordinal, and scaled. Because the imputation models are implicit, it is not necessary to specify a parametric distribution for each variable to be imputed. MIDAS also allows the user to address the sensitivity of their inferences to different assumptions concerning the missing data mechanism. An example using MIDAS to impute missing data is presented and MIDAS is compared to existing missing data software.
url http://www.jstatsoft.org/v29/i09/paper
work_keys_str_mv AT junedsiddique midasasasmacroformultipleimputationusingdistanceaidedselectionofdonors
AT oferharel midasasasmacroformultipleimputationusingdistanceaidedselectionofdonors
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