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20152021
most citedAn Empirical Comparison of Multiple Imputation Methods for Categorical Data

66 citations · 94 across the 8 of their papers we have counts for

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5 papers · 1 filter

stat.ME2020

Multiple Imputation for Nonignorable Item Nonresponse in Complex Surveys Using Auxiliary Margin

Olanrewaju Akande, Jerome P. Reiter

We outline a framework for multiple imputation of nonignorable item nonresponse when the marginal distributions of some of the variables with missing values are known. In particula…

stat.ME2020★ 11 cited

A Comparative Study of Imputation Methods for Multivariate Ordinal Data

Chayut Wongkamthong, Olanrewaju Akande

Missing data remains a very common problem in large datasets, including survey and census data containing many ordinal responses, such as political polls and opinion surveys. Multi…

stat.ME2019

Leveraging Auxiliary Information on Marginal Distributions in Nonignorable Models for Item and Unit Nonresponse

Olanrewaju Akande, Gabriel Madson, D. Sunshine Hillygus +1

Often, government agencies and survey organizations know the population counts or percentages for some of the variables in a survey. These may be available from auxiliary sources,…

stat.ME2018

Simultaneous Edit and Imputation for Household Data with Structural Zeros

Olanrewaju Akande, Andrés Barrientos, Jerome P. Reiter

Multivariate categorical data nested within households often include reported values that fail edit constraints---for example, a participating household reports a child's age as ol…

stat.ME2017★ 3 cited

Multiple Imputation of Missing Values in Household Data with Structural Zeros

Olanrewaju Akande, Jerome Reiter, Andrés F. Barrientos

We present an approach for imputation of missing items in multivariate categorical data nested within households. The approach relies on a latent class model that (i) allows for ho…