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MICT: multiple imputation for categorical time-series

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dc.contributor.author Halpin, Brendan
dc.date.accessioned 2015-09-22T10:23:58Z
dc.date.available 2015-09-22T10:23:58Z
dc.date.issued 2015
dc.identifier.uri http://hdl.handle.net/10344/4647
dc.description non-peer-reviewed en_US
dc.description.abstract The MICT package provides a method for multiple imputation for categorical time-series data such as lifecourse or employment-status histories that preserves longitudinal consistency, using a monotonic series of imputations. It allows flexible imputation specifications, with a model appropriate to the target variable (mlogit, ologit etc.). Where transitions are substantially less frequent than once per time-unit, and where missingness tends to be consecutive (as is typical of lifecourse data), it produces imputations with better longitudinal consistency than mi impute or ice. en_US
dc.language.iso eng en_US
dc.publisher Department of Sociology: University of Limerick en_US
dc.relation.ispartofseries Department of Sociology;Working Paper WP2015-02
dc.relation.uri http://www3.ul.ie/sociology/index.php?pagid=working-papers
dc.subject MICT en_US
dc.subject time-series data en_US
dc.subject labour en_US
dc.title MICT: multiple imputation for categorical time-series en_US
dc.type info:eu-repo/semantics/workingPaper en_US
dc.type.supercollection all_ul_research en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US
dc.internal.authorcontactother Brendan.halpin@ul.ie


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