appendbreak

data

warp.model

Label to signal that this is a newly added observation


A custom function to insert rows in long data with new pseudo-observations
that are being done on the specified break ages. There should be a
column called <code>first</code> in <code>data</code> with logical data that codes whether
the current row is the first for subject <code>id</code>. Furthermore,
the function assumes that columns <code>age</code>, <code>occ</code>,
<code>hgt.z</code>, <code>wgt.z</code> and
<code>bmi.z</code> are available. This function is used on the <code>tbc</code>
data in FIMD chapter 9. Check that out to see it in action.


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.

appendbreak: Appends specified break to the data

Description

Usage

Arguments

Value