tag:crantastic.org,2005:/authors/1248Latest activity for Yasuyuki Okumura2012-01-10T23:17:05Zcrantastic.orgtag:crantastic.org,2005:TimelineEvent/188442012-01-10T23:17:05Z2012-01-10T23:17:05Zrpsychi was upgraded to version 0.8<a href="/packages/rpsychi">rpsychi</a> was <span class="action">upgraded</span> to version <a href="/packages/rpsychi/versions/16533">0.8</a><br /><h3>Package description:</h3><p>The rpsychi offers a number of functions for psychiatry, psychiatric nursing, clinical psychology. Functions are primarily for statistical significance testing using published work. For example, you can conduct a factorial analysis of variance (ANOVA), which requires only the mean, standard deviation, and sample size for each cell, rather than the individual data. This package covers fundamental statistical tests such as t-test, chi-square test, analysis of variance, and multiple regression analysis. With some exceptions, you can obtain effect size and its confidence interval. These functions help you to obtain effect size from published work, and then to conduct a priori power analysis or meta-analysis, even if a researcher do not report effect size in a published work.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/174562011-11-12T16:30:41Z2011-11-12T16:30:41Zrpsychi was upgraded to version 0.7<a href="/packages/rpsychi">rpsychi</a> was <span class="action">upgraded</span> to version <a href="/packages/rpsychi/versions/15592">0.7</a><br /><h3>Package description:</h3><p>The rpsychi offers a number of functions for psychiatry, psychiatric nursing, clinical psychology. Functions are primarily for statistical significance testing using published work. For example, you can conduct a factorial analysis of variance (ANOVA), which requires only the mean, standard deviation, and sample size for each cell, rather than the individual data. This package covers fundamental statistical tests such as t-test, chi-square test, analysis of variance, and multiple regression analysis. With some exceptions, you can obtain effect size and its confidence interval. These functions help you to obtain effect size from published work, and then to conduct a priori power analysis or meta-analysis, even if a researcher do not report effect size in a published work.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/171982011-11-03T07:10:43Z2011-11-03T07:10:43Zrpsychi was upgraded to version 0.6<a href="/packages/rpsychi">rpsychi</a> was <span class="action">upgraded</span> to version <a href="/packages/rpsychi/versions/15342">0.6</a><br /><h3>Package description:</h3><p>The rpsychi offers a number of functions for psychiatry, psychiatric nursing, clinical psychology. Functions are primarily for statistical significance testing using published work. For example, you can conduct a factorial analysis of variance (ANOVA), which requires only the mean, standard deviation, and sample size for each cell, rather than the individual data. This package covers fundamental statistical tests such as t-test, chi-square test, analysis of variance, and multiple regression analysis. With some exceptions, you can obtain effect size and its confidence interval. These functions help you to obtain effect size from published work, and then to conduct a priori power analysis or meta-analysis, even if a researcher do not report effect size in a published work.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/159422011-09-07T13:30:34Z2011-09-07T13:30:34Zrpsychi was upgraded to version 0.4<a href="/packages/rpsychi">rpsychi</a> was <span class="action">upgraded</span> to version <a href="/packages/rpsychi/versions/14186">0.4</a><br /><h3>Package description:</h3><p>The rpsychi offers a number of functions for psychiatry, psychiatric nursing, clinical psychology. Functions are primarily for statistical significance testing using published work. For example, you can conduct a factorial analysis of variance (ANOVA), which requires only the mean, standard deviation, and sample size for each cell, rather than the individual data. This package covers fundamental statistical tests such as t-test, chi-square test, analysis of variance, and multiple regression analysis. With some exceptions, you can obtain effect size and its confidence interval. These functions help you to obtain effect size from published work, and then to conduct a priori power analysis or meta-analysis, even if a researcher do not report effect size in a published work.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/159052011-09-06T09:10:31Z2011-09-06T09:10:31Zrpsychi was upgraded to version 0.3<a href="/packages/rpsychi">rpsychi</a> was <span class="action">upgraded</span> to version <a href="/packages/rpsychi/versions/14151">0.3</a><br /><h3>Package description:</h3><p>The rpsychi offers a number of functions for psychiatry, psychiatric nursing, clinical psychology. Functions are primarily for statistical significance testing using published work. For example, you can conduct a factorial analysis of variance (ANOVA), which requires only the mean, standard deviation, and sample size for each cell, rather than the individual data. This package covers fundamental statistical tests such as t-test, chi-square test, analysis of variance, and multiple regression analysis. With some exceptions, you can obtain effect size and its confidence interval. These functions help you to obtain effect size from published work, and then to conduct a priori power analysis or meta-analysis, even if a researcher do not report effect size in a published work.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/45662010-02-14T18:55:59Z2010-02-14T18:55:59Zrpsychi was released<a href="/packages/rpsychi">rpsychi</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>The rpsychi offers a number of functions for psychiatry, psychiatric nursing, clinical psychology. Functions are primarily for statistical significance testing using published work. For example, you can conduct a factorial analysis of variance (ANOVA), which requires only the mean, standard deviation, and sample size for each cell, rather than the individual data. This package covers fundamental statistical tests such as t-test, chi-square test, analysis of variance, and multiple regression analysis. With some exceptions, you can obtain effect size and its confidence interval. These functions help you to obtain effect size from published work, and then to conduct a priori power analysis or meta-analysis, even if a researcher do not report effect size in a published work.</p>crantastic.org