ic,data.frame-method

ic,matrix-method

ic,mids-method

An <code>R</code> object. Currently supported are methods for the
following classes: <code>mids</code>, <code>mira</code>, <code>mipo</code>, <code>data.frame</code>
and <code>matrix</code>. In addition, <code>x</code> can be a vector of any kind.

A logical flag for matrices and arrays. If <code>drop=TRUE</code> the
result is coerced to the lowest possible dimension.

drop

Extracts incomplete cases from a data set. Missing values in <code>x</code> are coded
as <code>NA</code>.
The companion function for selecting the complete cases is <code>cc()</code>.

univar

Multiple imputation using Fully Conditional Specification (FCS)
    implemented by the MICE algorithm. Each variable has its own imputation
    model. Built-in imputation models are provided for continuous data
    (predictive mean matching, normal), binary data (logistic regression),
    unordered categorical data (polytomous logistic regression) and ordered
    categorical data (proportional odds). MICE can also impute continuous
    two-level data (normal model, pan, second-level variables). Passive
    imputation can be used to maintain consistency between variables. Various
    diagnostic plots are available to inspect the quality of the imputations.

State of Data and AI Literacy Report 2025

ic: Incomplete cases

Description

Usage

Arguments

Value

See Also

Examples