Multiple imputation for continuous and categorical data: comparing joint multivariate normal and conditional approaches.

J Kropko, B Goodrich, A Gelman, J Hill - Political Analysis, 2014 - cambridge.org
Multiple imputation (MI) is an approach for handling missing values in a data set that allows
researchers to use the entirety of the observed data. Although MI has become more …
被引用次数：118 相关文章

Multiple Imputation for Continuous and Categorical Data: Comparing Joint Multivariate Normal and Conditional Approaches

J Kropko, B Goodrich, A Gelman, J Hill - Political Analysis, 2014 - JSTOR
We consider the relative performance of two common approaches to multiple imputation
(MI): joint multivariate normal (MVN) MI, in which the data are modeled as a sample from a …

Multiple Imputation for Continuous and Categorical Data: Comparing Joint Multivariate Normal and Conditional Approaches.

J Kropko, B Goodrich, A Gelman, J Hill - Grantee Submission, 2014 - ERIC
We consider the relative performance of two common approaches to multiple imputation
(MI): joint multivariate normal (MVN) MI, in which the data are modeled as a sample from a …

Multiple Imputation for Continuous and Categorical Data: Comparing Joint Multivariate Normal and Conditional Approaches.

J Kropko, B Goodrich, A Gelman, J Hill - Political Analysis, 2014 - search.ebscohost.com
We consider the relative performance of two common approaches to multiple imputation
(MI): joint multivariate normal (MVN) MI, in which the data are modeled as a sample from a …
[PDF] psu.edu

[PDF][PDF] Multiple Imputation for Continuous and Categorical Data: Comparing Joint Multivariate Normal and Conditional Approaches

J Kropko, B Goodrich, A Gelman, J Hill - Political Analysis, 2014 - Citeseer
Multiple imputation (MI) is an approach for handling missing values in a data set that allows
researchers to use the entirety of the observed data. Although MI has become more …

Multiple imputation for continuous and categorical data: Comparing joint multivariate normal and conditional approaches

J Kropko, B Goodrich, A Gelman, J Hill - Political Analysis, 2014 - nyuscholars.nyu.edu
We consider the relative performance of two common approaches to multiple imputation
(MI): joint multivariate normal (MVN) MI, in which the data are modeled as a sample from a …

Multiple Imputation for Continuous and Categorical Data: Comparing Joint Multivariate Normal and Conditional Approaches

J Kropko, B Goodrich, A Gelman, J Hill - Political Analysis, 2014 - ideas.repec.org
We consider the relative performance of two common approaches to multiple imputation
(MI): joint multivariate normal (MVN) MI, in which the data are modeled as a sample from a …

Multiple Imputation for Continuous and Categorical Data: Comparing Joint Multivariate Normal and Conditional Approaches

J Kropko, B Goodrich, A Gelman, J Hill - Political Analysis, 2014 - econpapers.repec.org
We consider the relative performance of two common approaches to multiple imputation
(MI): joint multivariate normal (MVN) MI, in which the data are modeled as a sample from a …

Multiple Imputation for Continuous and Categorical Data: Comparing Joint Multivariate Normal and Conditional Approaches

J Kropko, B Goodrich, A Gelman, J Hill - Political Analysis - cambridge.org
We consider the relative performance of two common approaches to multiple imputation
(MI): joint multivariate normal (MVN) MI, in which the data are modeled as a sample from a …

[引用][C] Multiple Imputation for Continuous and Categorical Data: Comparing Joint Multivariate Normal and Conditional Approaches

J Kropko, B Goodrich, A Gelman, J Hill - Political analysis, 2014 - Oxford University Press