nhanes2


A small data set with non-monotone missing values.


datasets

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.

Stef van Buuren

mice

Multivariate Imputation by Chained Equations

nhanes2 function

A data frame with 25 observations on the following 4 variables.
<dl>
<dt>age</dt><dd>Age group (1=20-39, 2=40-59, 3=60+)</dd> <dt>bmi</dt><dd>Body mass index (kg/m**2)</dd> <dt>hyp</dt><dd>Hypertensive (1=no,2=yes)</dd> <dt>chl</dt><dd>Total serum cholesterol (mg/dL)</dd>
 </dl>

Format

Schafer, J.L. (1997).  <em>Analysis of Incomplete Multivariate
Data.</em> London: Chapman & Hall. Table 6.14.

nhanes2: NHANES example - mixed numerical and discrete variables

Description

Arguments

Format

Source

Details

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Examples