tag:crantastic.org,2005:/packages/sjstatsLatest activity for sjstats2018-05-02T21:22:58Zcrantastic.orgtag:crantastic.org,2005:TimelineEvent/745092018-05-02T21:22:58Z2018-05-02T21:22:58Zsjstats was upgraded to version 0.14.3<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/71124">0.14.3</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/730902018-03-27T22:42:22Z2018-03-27T22:42:22Zsjstats was upgraded to version 0.14.2-3<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/69772">0.14.2-3</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/730072018-03-25T23:22:32Z2018-03-25T23:22:32Zsjstats was upgraded to version 0.14.2-2<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/69692">0.14.2-2</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/729852018-03-25T15:22:44Z2018-03-25T15:22:44Zsjstats was upgraded to version 0.14.2<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/69670">0.14.2</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/712132018-02-04T15:42:51Z2018-02-04T15:42:51Zsjstats was upgraded to version 0.14.1<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/68009">0.14.1</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/703782018-01-14T16:02:12Z2018-01-14T16:02:12Zsjstats was upgraded to version 0.14.0<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/67227">0.14.0</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/687752017-11-23T01:02:10Z2017-11-23T01:02:10Zsjstats was upgraded to version 0.13.0<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/65755">0.13.0</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/684882017-11-16T16:07:13Z2017-11-16T16:07:13Zcvptfs uses sjstats<a href="/users/2260">cvptfs</a> <span class="action">uses</span> <a href="/packages/sjstats">sjstats</a>cvptfstag:crantastic.org,2005:TimelineEvent/674242017-10-17T03:22:00Z2017-10-17T03:22:00Zsjstats was upgraded to version 0.12.0<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/64485">0.12.0</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/668822017-09-28T22:22:08Z2017-09-28T22:22:08Zsjstats was upgraded to version 0.11.2<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/63979">0.11.2</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/664812017-09-16T19:02:14Z2017-09-16T19:02:14Zsjstats was upgraded to version 0.11.1<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/63596">0.11.1</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/656722017-08-21T10:03:28Z2017-08-21T10:03:28Zsjstats was upgraded to version 0.11.0<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/62800">0.11.0</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/648252017-07-23T23:41:55Z2017-07-23T23:41:55Zsjstats was upgraded to version 0.10.3<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/62002">0.10.3</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/639292017-06-27T11:01:57Z2017-06-27T11:01:57Zsjstats was upgraded to version 0.10.2<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/61161">0.10.2</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/635282017-06-14T23:02:19Z2017-06-14T23:02:19Zsjstats was upgraded to version 0.10.1<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/60760">0.10.1</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/613452017-04-11T11:01:49Z2017-04-11T11:01:49Zsjstats was upgraded to version 0.10.0<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/58675">0.10.0</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/601712017-03-13T18:13:44Z2017-03-13T18:13:44Zsjstats was upgraded to version 0.9.0<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/57606">0.9.0</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/591732017-02-03T13:41:51Z2017-02-03T13:41:51Zsjstats was upgraded to version 0.8.0<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/56626">0.8.0</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/578232016-12-18T18:41:32Z2016-12-18T18:41:32Zsjstats was upgraded to version 0.7.1<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/55368">0.7.1</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/575192016-12-08T19:41:49Z2016-12-08T19:41:49Zsjstats was upgraded to version 0.7.0<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/55070">0.7.0</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/563492016-10-31T16:21:43Z2016-10-31T16:21:43Zsjstats was upgraded to version 0.6.0<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/54029">0.6.0</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/553412016-09-26T12:41:31Z2016-09-26T12:41:31Zsjstats was upgraded to version 0.5.0<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/53119">0.5.0</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/543902016-08-26T14:01:29Z2016-08-26T14:01:29Zsjstats was upgraded to version 0.4.0<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/52200">0.4.0</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/534212016-07-30T07:41:29Z2016-07-30T07:41:29Zsjstats was upgraded to version 0.3.0<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/51502">0.3.0</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/521872016-06-20T15:41:27Z2016-06-20T15:41:27Zsjstats was upgraded to version 0.2.0<a href="/packages/sjstats">sjstats</a> was <span class="action">upgraded</span> to version <a href="/packages/sjstats/versions/50407">0.2.0</a><br /><h3>Package description:</h3><p>Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.</p>crantastic.org