tag:crantastic.org,2005:/authors/6854Latest activity for John Ruscio2019-09-07T08:23:12Zcrantastic.orgtag:crantastic.org,2005:TimelineEvent/924422019-09-07T08:23:12Z2019-09-07T08:23:12ZRProbSup was upgraded to version 2.1<a href="/packages/RProbSup">RProbSup</a> was <span class="action">upgraded</span> to version <a href="/packages/RProbSup/versions/87906">2.1</a><br /><h3>Package description:</h3><p>The A() function calculates the A statistic, a nonparametric measure of effect size for two independent groups thats also known as the probability of superiority (Ruscio, 2008), along with its standard error and a confidence interval constructed using bootstrap methods (Ruscio & Mullen, 2012). Optional arguments can be specified to calculate variants of the A statistic developed for other research designs (e.g., related samples, more than two independent groups or related samples; Ruscio & Gera, 2013). <DOI: 10.1037/1082-989X.13.1.19>. <DOI: 10.1080/00273171.2012.658329>. <DOI: 10.1080/00273171.2012.738184>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/838282019-01-19T15:42:45Z2019-01-19T15:42:45ZRProbSup was upgraded to version 2.0<a href="/packages/RProbSup">RProbSup</a> was <span class="action">upgraded</span> to version <a href="/packages/RProbSup/versions/79693">2.0</a><br /><h3>Package description:</h3><p>The A() function calculates the A statistic, a nonparametric measure of effect size for two independent groups thats also known as the probability of superiority (Ruscio, 2008), along with its standard error and a confidence interval constructed using bootstrap methods (Ruscio & Mullen, 2012). Optional arguments can be specified to calculate variants of the A statistic developed for other research designs (e.g., related samples, more than two independent groups or related samples; Ruscio & Gera, 2013). <DOI: 10.1037/1082-989X.13.1.19>. <DOI: 10.1080/00273171.2012.658329>. <DOI: 10.1080/00273171.2012.738184>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/823112018-12-03T09:42:42Z2018-12-03T09:42:42ZRProbSup was released<a href="/packages/RProbSup">RProbSup</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>The A() function calculates the A statistic, a nonparametric measure of effect size for two independent groups thats also known as the probability of superiority (Ruscio, 2008), along with its standard error and a confidence interval constructed using bootstrap methods (Ruscio & Mullen, 2012). Optional arguments can be specified to calculate variants of the A statistic developed for other research designs (e.g., related samples, more than two independent groups or related samples; Ruscio & Gera, 2013). <DOI: 10.1037/1082-989X.13.1.19>. <DOI: 10.1080/00273171.2012.658329>. <DOI: 10.1080/00273171.2012.738184>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/817332018-11-14T15:22:38Z2018-11-14T15:22:38ZRGenData was released<a href="/packages/RGenData">RGenData</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>The GenDataSample() and GenDataPopulation() functions create, respectively, a sample or population of multivariate nonnormal data using methods described in Ruscio and Kaczetow (2008). Both of these functions call a FactorAnalysis() function to reproduce a correlation matrix. The EFACompData() function allows users to determine how many factors to retain in an exploratory factor analysis of an empirical data set using a method described in Ruscio and Roche (2012). The latter function uses populations of comparison data created by calling the GenDataPopulation() function. <DOI: 10.1080/00273170802285693>. <DOI: 10.1037/a0025697>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/812532018-10-31T13:02:26Z2018-10-31T13:02:26ZRImpact was released<a href="/packages/RImpact">RImpact</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>The metrics() function calculates measures of scholarly impact. These include conventional measures, such as the number of publications and the total citations to all publications, as well as modern and robust metrics based on the vector of citations associated with each publication, such as the h index and many of its variants or rivals. These methods are described in Ruscio et al. (2012) <DOI: 10.1080/15366367.2012.711147>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/662812017-09-09T20:42:01Z2017-09-09T20:42:01ZRTaxometrics was upgraded to version 2.3<a href="/packages/RTaxometrics">RTaxometrics</a> was <span class="action">upgraded</span> to version <a href="/packages/RTaxometrics/versions/63401">2.3</a><br /><h3>Package description:</h3><p>We provide functions to perform taxometric analyses. This package contains 44 functions, but only 5 should be called directly by users. CheckData() should be run prior to any taxometric analysis to ensure that the data are appropriate for taxometric analysis. RunTaxometrics() performs taxometric analyses for a sample of data. RunCCFIProfile() performs a series of taxometric analyses to generate a CCFI profile. CreateData() generates a sample of categorical or dimensional data. ClassifyCases() assigns cases to groups using the base-rate classification method.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/640582017-06-30T18:02:14Z2017-06-30T18:02:14ZRTaxometrics was upgraded to version 2.2<a href="/packages/RTaxometrics">RTaxometrics</a> was <span class="action">upgraded</span> to version <a href="/packages/RTaxometrics/versions/61281">2.2</a><br /><h3>Package description:</h3><p>We provide functions to perform taxometric analyses. This package contains 42 functions, but only 5 should be called directly by users. CheckData() should be run prior to any taxometric analysis to ensure that the data are appropriate for taxometric analysis. RunTaxometrics() performs taxometric analyses for a sample of data. RunCCFIProfile() performs a series of taxometric analyses to generate a CCFI profile. CreateData() generates a sample of categorical or dimensional data. ClassifyCases() assigns cases to groups using the base-rate classification method.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/639932017-06-29T05:42:03Z2017-06-29T05:42:03ZRTaxometrics was upgraded to version 2.1<a href="/packages/RTaxometrics">RTaxometrics</a> was <span class="action">upgraded</span> to version <a href="/packages/RTaxometrics/versions/61225">2.1</a><br /><h3>Package description:</h3><p>We provide functions to perform taxometric analyses. This package contains 42 functions, but only 5 should be called directly by users. CheckData() should be run prior to any taxometric analysis to ensure that the data are appropriate for taxometric analysis. RunTaxometrics() performs taxometric analyses for a sample of data. RunCCFIProfile() performs a series of taxometric analyses to generate a CCFI profile. CreateData() generates a sample of categorical or dimensional data. ClassifyCases() assigns cases to groups using the base-rate classification method.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/630582017-05-30T15:41:47Z2017-05-30T15:41:47ZRTaxometrics was released<a href="/packages/RTaxometrics">RTaxometrics</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>We provide functions to perform taxometric analyses. This package contains 44 functions, but only 5 should be called directly by users. CheckData() should be run prior to any taxometric analysis to ensure that the data are appropriate for taxometric analysis. RunTaxometrics() performs taxometric analyses for a sample of data. RunCCFIProfile() performs a series of taxometric analyses to generate a CCFI profile. CreateData() generates a sample of categorical or dimensional data. ClassifyCases() assigns cases to groups using the base-rate classification method.</p>crantastic.org