What is multivariate normal imputation?

What is multivariate normal imputation?

Multivariate normal imputation MVNI is a joint modelling approach to imputation where all variables in the imputation model are assumed to follow a multivariate normal distribution. Initially, missing values are imputed based on assumed starting parameter values for the multivariate normal distribution.

What is conditional imputation?

1. Conditional mean imputation. When done carefully, imputation leads to consistent estimators and valid tests. It is a simple and appealing method; it uses all the data, and it separates the missing data part, which is handled by imputation, from the analysis part, which is done by complete data methods.

How is multivariate imputation by chained equations used?

Multivariate Imputation by Chained Equations The mice package implements a method to deal with missing data. The package creates multiple imputations (replacement values) for multivariate missing data. The method is based on Fully Conditional Specification, where each incomplete variable is imputed by a separate model.

What kind of data can the mice algorithm impute?

The MICE algorithm can impute mixes of continuous, binary, unordered categorical and ordered categorical data. In addition, MICE can impute continuous two-level data, and maintain consistency between imputations by means of passive imputation. Many diagnostic plots are implemented to inspect the quality of the imputations.

How to perform multiple imputation using predictive mean?

The mice function will detect which variables is the data set have missing information. The default method of imputation in the MICE package is PMM and the default number of imputations is 5. If you would like to change the default number you can supply a second argument which we demonstrate below.

How does a mouse maintain consistency between imputations?

In addition, MICE can impute continuous two-level data, and maintain consistency between imputations by means of passive imputation. Many diagnostic plots are implemented to inspect the quality of the imputations.