March 2018
Beginner to intermediate
570 pages
13h 42m
English
Let's focus on the univariate case, where only one column contains missing data and we use all the other (completed) columns to impute the missing values before generalizing to a multivariate case.
mice actually has a few different imputation methods up its sleeve, each best suited for a particular use case. mice will often choose sensible defaults based on the data type (continuous, binary, non-binary categorical, and so on).
The most important method is what the package calls the norm method. This method is very much like stochastic regression. Each of the m imputations is created by adding a normal noise term to the output of a linear regression predicting the missing variable. What makes ...