compute_stats

This is the second step in conducting dropout analysis with <code>dropR</code>.
Outputs all necessary statistics to analyze and visualize dropout, such as
the sample size N of the data (and in each condition if selected), cumulative
dropout and remaining participants in absolute numbers and percent.
If no experimental condition is added, the stats are only calculated for the
whole data in total.

Analysis and visualization of dropout between conditions in surveys and (online) experiments. Features include computation of dropout statistics, comparing dropout between conditions (e.g. Chi square), analyzing survival (e.g. Kaplan-Meier estimation), comparing conditions with the most different rates of dropout (Kolmogorov-Smirnov) and visualizing the result of each in designated plotting functions. Sources: Andrea Frick, Marie-Terese Baechtiger & Ulf-Dietrich Reips (2001) <https://www.researchgate.net/publication/223956222_Financial_incentives_personal_information_and_drop-out_in_online_studies>; Ulf-Dietrich Reips (2002) "Standards for Internet-Based Experimenting" <doi:10.1027//1618-3169.49.4.243>.

Annika Tave Overlander

dropR

Dropout Analysis by Condition

Matthias Bannert

Ulf-Dietrich Reips

compute_stats function

<dl><dt>df</dt>
<dd>data.frame containing variable <code>do_idx</code> from <code>add_dropout_idx()</code></dd>
<dt>by_cond</dt>
<dd>character name of condition variable in the data, defaults to 'None' to output total statistics.</dd>
<dt>no_of_vars</dt>
<dd>numeric number of variables that contain questions</dd></dl>

Arguments

Compute Dropout Statistics — compute_stats

<dl>

<dt>df</dt>
<dd>data.frame containing variable <code>do_idx</code> from <code>add_dropout_idx()</code></dd>


<dt>by_cond</dt>
<dd>character name of condition variable in the data, defaults to 'None' to output total statistics.</dd>


<dt>no_of_vars</dt>
<dd>numeric number of variables that contain questions</dd>

</dl>

compute_stats: Compute Dropout Statistics

Description

Usage

Value

Arguments

Examples