<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>kinleyid.r-universe.dev</title><link>https://kinleyid.r-universe.dev</link><description>Recent package updates in kinleyid</description><generator>R-universe</generator><image><url>https://github.com/kinleyid.png</url><title>R packages by kinleyid</title><link>https://kinleyid.r-universe.dev</link></image><lastBuildDate>Sun, 15 Mar 2026 03:14:24 GMT</lastBuildDate><item><title>[kinleyid] tempodisco 2.2.0</title><author>isaac.kinley@gmail.com (Isaac Kinley)</author><description>Tools for working with temporal discounting data, designed
for behavioural researchers to simplify data cleaning/scoring
and model fitting. The package implements widely used methods
such as computing indifference points from adjusting amount
task (Frye et al., 2016, &lt;doi:10.3791/53584&gt;), testing for
non-systematic discounting per the criteria of Johnson &amp; Bickel
(2008, &lt;doi:10.1037/1064-1297.16.3.264&gt;), scoring
questionnaires according to the methods of Kirby et al. (1999,
&lt;doi:10.1037//0096-3445.128.1.78&gt;) and Wileyto et al (2004,
&lt;doi:10.3758/BF03195548&gt;), Bayesian model selection using a
range of discount functions (Franck et al., 2015,
&lt;doi:10.1002/jeab.128&gt;), drift diffusion models of discounting
(Peters &amp; D'Esposito, 2020,
&lt;doi:10.1371/journal.pcbi.1007615&gt;), and model-agnostic
measures of discounting such as area under the curve (Myerson
et al., 2001, &lt;doi:10.1901/jeab.2001.76-235&gt;) and ED50 (Yoon &amp;
Higgins, 2008, &lt;doi:10.1016/j.drugalcdep.2007.12.011&gt;).</description><link>https://github.com/r-universe/kinleyid/actions/runs/29228807933</link><pubDate>Sun, 15 Mar 2026 03:14:24 GMT</pubDate><r:package>tempodisco</r:package><r:version>2.2.0</r:version><r:status>success</r:status><r:repository>https://kinleyid.r-universe.dev</r:repository><r:upstream>https://github.com/kinleyid/tempodisco</r:upstream><r:article><r:source>analyzing-study.Rmd</r:source><r:filename>analyzing-study.html</r:filename><r:title>Analyzing data from multiple participants</r:title><r:created>2024-09-03 00:03:16</r:created><r:modified>2024-11-20 05:19:52</r:modified></r:article><r:article><r:source>all-discount-functions.Rmd</r:source><r:filename>all-discount-functions.html</r:filename><r:title>Available discount functions</r:title><r:created>2026-03-04 02:40:24</r:created><r:modified>2026-03-04 02:40:24</r:modified></r:article><r:article><r:source>choice-rules.Rmd</r:source><r:filename>choice-rules.html</r:filename><r:title>Choice rules</r:title><r:created>2025-03-01 17:02:01</r:created><r:modified>2025-04-03 15:24:58</r:modified></r:article><r:article><r:source>comparing-models.Rmd</r:source><r:filename>comparing-models.html</r:filename><r:title>Comparing discounting across different discount functions</r:title><r:created>2024-09-02 14:28:10</r:created><r:modified>2024-11-20 05:19:52</r:modified></r:article><r:article><r:source>area-under-curve.Rmd</r:source><r:filename>area-under-curve.html</r:filename><r:title>Computing area under the curve (AUC)</r:title><r:created>2024-11-20 05:19:52</r:created><r:modified>2024-11-20 05:19:52</r:modified></r:article><r:article><r:source>custom-discount-functions.Rmd</r:source><r:filename>custom-discount-functions.html</r:filename><r:title>Creating custom discount functions</r:title><r:created>2024-09-02 14:28:10</r:created><r:modified>2024-09-02 17:57:03</r:modified></r:article><r:article><r:source>drift-diffusion-models.Rmd</r:source><r:filename>drift-diffusion-models.html</r:filename><r:title>Drift diffusion models</r:title><r:created>2024-11-08 00:53:46</r:created><r:modified>2025-04-30 17:19:45</r:modified></r:article><r:article><r:source>tempodisco.Rmd</r:source><r:filename>tempodisco.html</r:filename><r:title>Getting started</r:title><r:created>2024-11-20 13:38:21</r:created><r:modified>2024-11-20 13:38:21</r:modified></r:article><r:article><r:source>nonsystematic-discounting.Rmd</r:source><r:filename>nonsystematic-discounting.html</r:filename><r:title>Indentifying non-systematic discounting</r:title><r:created>2024-09-02 14:28:10</r:created><r:modified>2024-09-04 13:17:39</r:modified></r:article><r:article><r:source>modeling-binary-choice-data.Rmd</r:source><r:filename>modeling-binary-choice-data.html</r:filename><r:title>Modeling binary choice data</r:title><r:created>2024-09-02 14:28:10</r:created><r:modified>2026-03-04 01:15:07</r:modified></r:article><r:article><r:source>visualizing-models.Rmd</r:source><r:filename>visualizing-models.html</r:filename><r:title>Visualizing models</r:title><r:created>2024-09-02 14:28:10</r:created><r:modified>2025-04-30 15:58:26</r:modified></r:article><r:article><r:source>adjusting-amounts.Rmd</r:source><r:filename>adjusting-amounts.html</r:filename><r:title>Working with data from an adjusting amount procedure</r:title><r:created>2024-09-02 14:28:10</r:created><r:modified>2024-09-02 17:57:03</r:modified></r:article></item></channel></rss>