process_cond

This is an internal helper function used by <code>raw_plot</code> and <code>randomization_test</code>
to process the condition variable in the input data frame. It sets the factor
levels and labels of the condition variable based on the provided <code>cond_levels</code>
and <code>cond_labels</code> parameters.

internal

In some situations where researchers would like to demonstrate
causal effects, it is hard to obtain a sample size that would allow for a
well-powered randomized controlled trial. Single case designs are experimental
designs that can be used to demonstrate causal effects with only one participant
or with only a few participants. The 'scdtb' package provides a suite of tools
for analyzing data from studies that use single case designs. The nap() function
can be used to compute the nonoverlap of all pairs as outlined by the What
Works Clearinghouse (2022) <https://ies.ed.gov/ncee/wwc/Handbooks>. The
package also offers the mixed_model_analysis() and cross_lagged() functions
which implement mixed effects models and cross lagged analyses as described
in Maric & van der Werff (2020) <doi:10.4324/9780429273872-9>. The
randomization_test() function implements randomization tests based on methods
presented in Onghena (2020) <doi:10.4324/9780429273872-8>. The scdtb() 'shiny'
application can be used to upload single case design data and access various
'scdtb' tools for plotting and analysis.

Mackson Ncube

scdtb

Single Case Design Tools

mightymetrika, LLC 

process_cond function

<dl><dt>.df</dt>
<dd>A data frame containing the data to be processed. Must contain a column
specified by <code>.cond</code>.</dd>
<dt>.cond</dt>
<dd>The name of the column in <code>.df</code> that contains the condition variable.</dd>
<dt>cond_levels</dt>
<dd>(Optional) A vector of values indicating the order of condition
levels. This is used to set the factor levels of the condition
variable.</dd>
<dt>cond_labels</dt>
<dd>(Optional) A vector of labels corresponding to the condition
levels. These are used for the legend. If not provided, the
<code>cond_levels</code> are used as labels.</dd></dl>

Arguments

Process Condition Variable — process_cond

<dl>

<dt>.df</dt>
<dd>A data frame containing the data to be processed. Must contain a column
specified by <code>.cond</code>.</dd>


<dt>.cond</dt>
<dd>The name of the column in <code>.df</code> that contains the condition variable.</dd>


<dt>cond_levels</dt>
<dd>(Optional) A vector of values indicating the order of condition
levels. This is used to set the factor levels of the condition
variable.</dd>


<dt>cond_labels</dt>
<dd>(Optional) A vector of labels corresponding to the condition
levels. These are used for the legend. If not provided, the
<code>cond_levels</code> are used as labels.</dd>

</dl>

process_cond: Process Condition Variable

Description

Usage

Value

Arguments