na.omit.scdf

scdf objects
Removes any row with a missing value

A collection of procedures for analysing, visualising,
and managing single-case data. These include piecewise linear regression
models, multilevel models, overlap indices ('PND', 'PEM', 'PAND', 'PET', 'tau-u',
'baseline corrected tau', 'CDC'), and randomization tests. Data preparation functions
support outlier detection, handling missing values, scaling, and custom transformations.
An export function helps to generate
html, word, and latex tables in a publication friendly style. More details can be
found in the online book 'Analyzing single-case data with R and scan', Juergen Wilbert (2025)
<https://jazznbass.github.io/scan-Book/>.

Juergen Wilbert

scan

Single-Case Data Analyses for Single and Multiple Baseline
Designs

Timo Lueke

na.omit.scdf function

<dl><dt>object</dt>
<dd>A scdf.</dd>
<dt>...</dt>
<dd>not implemented yet.</dd></dl>

Arguments

scdf objects
Removes any row with a missing value — na.omit.scdf

<dl>

<dt>object</dt>
<dd>A scdf.</dd>


<dt>...</dt>
<dd>not implemented yet.</dd>

</dl>

na.omit.scdf: scdf objects Removes any row with a missing value

Description

Usage

Value

Arguments