tag:crantastic.org,2005:/authors/106Latest activity for Alexis Dinno2018-10-14T23:42:01Zcrantastic.orgtag:crantastic.org,2005:TimelineEvent/804732018-10-14T23:42:01Z2018-10-14T23:42:01Zparan was upgraded to version 1.5.2<a href="/packages/paran">paran</a> was <span class="action">upgraded</span> to version <a href="/packages/paran/versions/76783">1.5.2</a><br /><h3>Package description:</h3><p>An implementation of Horn's technique for numerically and graphically evaluating the components or factors retained in a principle components analysis (PCA) or common factor analysis (FA). Horn's method contrasts eigenvalues produced through a PCA or FA on a number of random data sets of uncorrelated variables with the same number of variables and observations as the experimental or observational data set to produce eigenvalues for components or factors that are adjusted for the sample error-induced inflation. Components with adjusted eigenvalues greater than one are retained. paran may also be used to conduct parallel analysis following Glorfeld's (1995) suggestions to reduce the likelihood of over-retention.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/706142018-01-20T00:21:35Z2018-01-20T00:21:35ZLoopAnalyst was upgraded to version 1.2-6<a href="/packages/LoopAnalyst">LoopAnalyst</a> was <span class="action">upgraded</span> to version <a href="/packages/LoopAnalyst/versions/67442">1.2-6</a><br /><h3>Package description:</h3><p>Loop analysis makes qualitative predictions of variable change in a system of causally interdependent variables, where "qualitative" means sign only (i.e. increases, decreases, non change, and ambiguous). This implementation includes output support for graphs in .dot file format for use with visualization software such as 'graphviz' (<http://graphviz.org>). 'LoopAnalyst' provides tools for the construction and output of community matrices, computation and output of community effect matrices, tables of correlations, adjoint, absolute feedback, weighted feedback and weighted prediction matrices, change in life expectancy matrices, and feedback, path and loop enumeration tools.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/678762017-10-30T20:20:31Z2017-10-30T20:20:31Zconover.test was upgraded to version 1.1.5<a href="/packages/conover-test">conover.test</a> was <span class="action">upgraded</span> to version <a href="/packages/conover-test/versions/64922">1.1.5</a><br /><h3>Package description:</h3><p>Computes the Conover-Iman test (1979) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. conover.test makes k(k-1)/2 multiple pairwise comparisons based on Conover-Iman t-test-statistic of the rank differences. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Conover-Iman test may be understood as a test for median difference. conover.test accounts for tied ranks. The Conover-Iman test is strictly valid if and only if the corresponding Kruskal-Wallis null hypothesis is rejected.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/677892017-10-27T16:20:41Z2017-10-27T16:20:41Zdunn.test was upgraded to version 1.3.5<a href="/packages/dunn-test">dunn.test</a> was <span class="action">upgraded</span> to version <a href="/packages/dunn-test/versions/64840">1.3.5</a><br /><h3>Package description:</h3><p>Computes Dunn's test (1964) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. 'dunn.test' makes k(k-1)/2 multiple pairwise comparisons based on Dunn's z-test-statistic approximations to the actual rank statistics. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Dunn's test may be understood as a test for median difference. 'dunn.test' accounts for tied ranks.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/611112017-04-04T22:20:23Z2017-04-04T22:20:23Zconover.test was upgraded to version 1.1.4<a href="/packages/conover-test">conover.test</a> was <span class="action">upgraded</span> to version <a href="/packages/conover-test/versions/58488">1.1.4</a><br /><h3>Package description:</h3><p>Computes the Conover-Iman test (1979) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. conover.test makes k(k-1)/2 multiple pairwise comparisons based on Conover-Iman t-test-statistic of the rank differences. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Conover-Iman test may be understood as a test for median difference. conover.test accounts for tied ranks. The Conover-Iman test is strictly valid if and only if the corresponding Kruskal-Wallis null hypothesis is rejected.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/610192017-04-02T21:00:38Z2017-04-02T21:00:38Zdunn.test was upgraded to version 1.3.4<a href="/packages/dunn-test">dunn.test</a> was <span class="action">upgraded</span> to version <a href="/packages/dunn-test/versions/58405">1.3.4</a><br /><h3>Package description:</h3><p>Computes Dunn's test (1964) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. 'dunn.test' makes k(k-1)/2 multiple pairwise comparisons based on Dunn's z-test-statistic approximations to the actual rank statistics. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Dunn's test may be understood as a test for median difference. 'dunn.test' accounts for tied ranks.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/610182017-04-02T21:00:28Z2017-04-02T21:00:28Zconover.test was upgraded to version 1.1.3<a href="/packages/conover-test">conover.test</a> was <span class="action">upgraded</span> to version <a href="/packages/conover-test/versions/58404">1.1.3</a><br /><h3>Package description:</h3><p>Computes the Conover-Iman test (1979) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. conover.test makes k(k-1)/2 multiple pairwise comparisons based on Conover-Iman t-test-statistic of the rank differences. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Conover-Iman test may be understood as a test for median difference. conover.test accounts for tied ranks. The Conover-Iman test is strictly valid if and only if the corresponding Kruskal-Wallis null hypothesis is rejected.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/593292017-02-09T06:20:35Z2017-02-09T06:20:35Zdunn.test was upgraded to version 1.3.3<a href="/packages/dunn-test">dunn.test</a> was <span class="action">upgraded</span> to version <a href="/packages/dunn-test/versions/56782">1.3.3</a><br /><h3>Package description:</h3><p>Computes Dunn's test (1964) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. 'dunn.test' makes k(k-1)/2 multiple pairwise comparisons based on Dunn's z-test-statistic approximations to the actual rank statistics. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Dunn's test may be understood as a test for median difference. 'dunn.test' accounts for tied ranks.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/593282017-02-09T06:20:27Z2017-02-09T06:20:27Zconover.test was upgraded to version 1.1.2<a href="/packages/conover-test">conover.test</a> was <span class="action">upgraded</span> to version <a href="/packages/conover-test/versions/56781">1.1.2</a><br /><h3>Package description:</h3><p>Computes the Conover-Iman test (1979) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. conover.test makes k(k-1)/2 multiple pairwise comparisons based on Conover-Iman t-test-statistic of the rank differences. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Conover-Iman test may be understood as a test for median difference. conover.test accounts for tied ranks. The Conover-Iman test is strictly valid if and only if the corresponding Kruskal-Wallis null hypothesis is rejected.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/590702017-02-01T00:15:29Z2017-02-01T00:15:29Zcrantastic_production tagged paran with Psychometrics<a href="/users/146">crantastic_production</a> <span class="action">tagged</span> <a href="/packages/paran">paran</a> with <a href="/task_views/Psychometrics">Psychometrics</a>crantastic_productiontag:crantastic.org,2005:TimelineEvent/463412016-01-06T22:30:50Z2016-01-06T22:30:50Zdunn.test was upgraded to version 1.3.2<a href="/packages/dunn-test">dunn.test</a> was <span class="action">upgraded</span> to version <a href="/packages/dunn-test/versions/46112">1.3.2</a><br /><h3>Package description:</h3><p>Computes Dunn's test (1964) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. 'dunn.test' makes k(k-1)/2 multiple pairwise comparisons based on Dunn's z-test-statistic approximations to the actual rank statistics. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Dunn's test may be understood as a test for median difference. 'dunn.test' accounts for tied ranks.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/463392016-01-06T22:30:39Z2016-01-06T22:30:39Zconover.test was upgraded to version 1.1.1<a href="/packages/conover-test">conover.test</a> was <span class="action">upgraded</span> to version <a href="/packages/conover-test/versions/46110">1.1.1</a><br /><h3>Package description:</h3><p>Computes the Conover-Iman test (1979) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. conover.test makes k(k-1)/2 multiple pairwise comparisons based on Conover-Iman t-test-statistic of the rank differences. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Conover-Iman test may be understood as a test for median difference. conover.test accounts for tied ranks. The Conover-Iman test is strictly valid if and only if the corresponding Kruskal-Wallis null hypothesis is rejected.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/442472015-10-08T18:30:54Z2015-10-08T18:30:54Zdunn.test was upgraded to version 1.3.1<a href="/packages/dunn-test">dunn.test</a> was <span class="action">upgraded</span> to version <a href="/packages/dunn-test/versions/44039">1.3.1</a><br /><h3>Package description:</h3><p>Computes Dunn's test (1964) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. 'dunn.test' makes k(k-1)/2 multiple pairwise comparisons based on Dunn's z-test-statistic approximations to the actual rank statistics. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Dunn's test may be understood as a test for median difference. 'dunn.test' accounts for tied ranks.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/439562015-09-26T07:30:41Z2015-09-26T07:30:41Zconover.test was released<a href="/packages/conover-test">conover.test</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>Computes the Conover-Iman test (1979) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. conover.test makes k(k-1)/2 multiple pairwise comparisons based on Conover-Iman t-test-statistic of the rank differences. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Conover-Iman test may be understood as a test for median difference. conover.test accounts for tied ranks. The Conover-Iman test is strictly valid if and only if the corresponding Kruskal-Wallis null hypothesis is rejected.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/439152015-09-24T22:50:54Z2015-09-24T22:50:54Zdunn.test was upgraded to version 1.3.0<a href="/packages/dunn-test">dunn.test</a> was <span class="action">upgraded</span> to version <a href="/packages/dunn-test/versions/43707">1.3.0</a><br /><h3>Package description:</h3><p>Computes Dunn's test (1964) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. 'dunn.test' makes k(k-1)/2 multiple pairwise comparisons based on Dunn's z-test-statistic approximations to the actual rank statistics. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Dunn's test may be understood as a test for median difference. 'dunn.test' accounts for tied ranks.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/420042015-07-08T08:31:30Z2015-07-08T08:31:30ZLoopAnalyst was upgraded to version 1.2-4<a href="/packages/LoopAnalyst">LoopAnalyst</a> was <span class="action">upgraded</span> to version <a href="/packages/LoopAnalyst/versions/41804">1.2-4</a><br /><h3>Package description:</h3><p>Loop analysis makes qualitative predictions of variable change in a system of causally interdependent variables, where "qualitative" means sign only (i.e. increases, decreases, non change, and ambiguous). This implementation includes output support for graphs in .dot file format for use with visualization software such as graphviz (graphviz.org). 'LoopAnalyst' provides tools for the construction and output of community matrices, computation and output of community effect matrices, tables of correlations, adjoint, absolute feedback, weighted feedback and weighted prediction matrices, change in life expectancy matrices, and feedback, path and loop enumeration tools.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/404252015-04-29T00:10:46Z2015-04-29T00:10:46Zdunn.test was upgraded to version 1.2.4<a href="/packages/dunn-test">dunn.test</a> was <span class="action">upgraded</span> to version <a href="/packages/dunn-test/versions/40226">1.2.4</a><br /><h3>Package description:</h3><p>Computes Dunn's test (1964) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. 'dunn.test' makes k(k-1)/2 multiple pairwise comparisons based on Dunn's z-test-statistic approximations to the actual rank statistics. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Dunn's test may be understood as a test for median difference. 'dunn.test' accounts for tied ranks.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/392272015-02-25T07:30:46Z2015-02-25T07:30:46Zdunn.test was upgraded to version 1.2.3<a href="/packages/dunn-test">dunn.test</a> was <span class="action">upgraded</span> to version <a href="/packages/dunn-test/versions/39052">1.2.3</a><br /><h3>Package description:</h3><p>Computes Dunn's test (1964) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. dunn.test makes k(k-1)/2 multiple pairwise comparisons based on Dunn's z-test-statistic approximations to the actual rank statistics. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Dunn's test may be understood as a test for median difference. dunn.test accounts for tied ranks.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/366472014-08-24T23:10:44Z2014-08-24T23:10:44Zdunn.test was released<a href="/packages/dunn-test">dunn.test</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>Computes Dunn's test (1964) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. 'dunn.test' makes k(k-1)/2 multiple pairwise comparisons based on Dunn's z-test-statistic approximations to the actual rank statistics. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Dunn's test may be understood as a test for median difference. 'dunn.test' accounts for tied ranks.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/341392013-07-10T08:10:39Z2013-07-10T08:10:39ZLoopAnalyst was upgraded to version 1.2-3<a href="/packages/LoopAnalyst">LoopAnalyst</a> was <span class="action">upgraded</span> to version <a href="/packages/LoopAnalyst/versions/29190">1.2-3</a><br /><h3>Package description:</h3><p>Loop analysis makes qualitative predictions of variable change in a system of causally interdependent variables, where "qualitative" means sign only (i.e. increases, decreases, non change, and ambiguous). This implementation includes output support for graphs in .dot file format for use with visualization software such as graphviz (graphviz.org). Loop Analyst provides tools for the construction and output of community matrices, computation and output of community effect matrices, tables of correlations, adjoint, absolute feedback, weighted feedback and weighted prediction matrices, change in life expectancy matrices, and feedback, path and loop enumeration tools.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/252382012-09-10T06:51:32Z2012-09-10T06:51:32Zparan was upgraded to version 1.5.1<a href="/packages/paran">paran</a> was <span class="action">upgraded</span> to version <a href="/packages/paran/versions/21209">1.5.1</a><br /><h3>Package description:</h3><p>paran is an implementation of Horn's technique for numerically and graphically evaluating the components or factors retained in a principle components analysis (PCA) or common factor analysis (FA). Horn's method contrasts eigenvalues produced through a PCA or FA on a number of random data sets of uncorrelated variables with the same number of variables and observations as the experimental or observational data set to produce eigenvalues for components or factors that are adjusted for the sample error-induced inflation. Components with adjusted eigenvalues greater than one are retained. paran may also be used to conduct parallel analysis following Glorfeld's (1995) suggestions to reduce the likelihood of over-retention.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/73822010-07-16T10:50:25Z2010-07-16T10:50:25Zparan was upgraded to version 1.4.3<a href="/packages/paran">paran</a> was <span class="action">upgraded</span> to version <a href="/packages/paran/versions/7830">1.4.3</a><br /><h3>Package description:</h3><p>paran is an implementation of Horn's technique for numerically and graphically evaluating the components or factors retained in a principle components analysis (PCA) or common factor analysis (FA). Horn's method contrasts eigenvalues produced through a PCA or FA on a number of random data sets of uncorrelated variables with the same number of variables and observations as the experimental or observational data set to produce eigenvalues for components or factors that are adjusted for the sample error-induced inflation. Components with adjusted eigenvalues greater than one are retained. paran may also be used to conduct parallel analysis following Glorfeld's (1995) suggestions to reduce the likelihood of over-retention.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/21882009-10-13T17:49:30Z2009-10-13T17:49:30Zparan was upgraded to version 1.4.2<a href="/packages/paran">paran</a> was <span class="action">upgraded</span> to version <a href="/packages/paran/versions/5153">1.4.2</a><br /><h3>Package description:</h3><p>paran is an implementation of Horn's technique for numerically and graphically evaluating the components or factors retained in a principle components analysis (PCA) or common factor analysis (FA). Horn's method contrasts eigenvalues produced through a PCA or FA on a number of random data sets of uncorrelated variables with the same number of variables and observations as the experimental or observational data set to produce eigenvalues for components or factors that are adjusted for the sample error-induced inflation. Components with adjusted eigenvalues greater than one are retained. paran may also be used to conduct parallel analysis following Glorfeld's (1995) suggestions to reduce the likelihood of over-retention.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/21672009-10-13T08:49:30Z2009-10-13T08:49:30ZLoopAnalyst was upgraded to version 1.2-2<a href="/packages/LoopAnalyst">LoopAnalyst</a> was <span class="action">upgraded</span> to version <a href="/packages/LoopAnalyst/versions/5134">1.2-2</a><br /><h3>Package description:</h3><p>Loop analysis makes qualitative predictions of variable change in a system of causally interdependent variabless, where "qualitative" means sign only (i.e. increases, decreases, non change, and ambiguous). This implementation includes output support for graphs in .dot file format for use with visualization software such as graphviz (graphviz.org). Loop Analyst provides tools for the construction and output of community matrices, computation and output of community effect matrices, tables of correlations, adjoint, absolute feedback, weighted feedback and weighted prediction matrices, change in life expectancy matrices, and feedback, path and loop enumeration tools.</p>crantastic.org