tag:crantastic.org,2005:/authors/4395Latest activity for Andre Schuetzenmeister2019-12-17T21:43:58Zcrantastic.orgtag:crantastic.org,2005:TimelineEvent/963302019-12-17T21:43:58Z2019-12-17T21:43:58ZVFP was upgraded to version 1.2<a href="/packages/VFP">VFP</a> was <span class="action">upgraded</span> to version <a href="/packages/VFP/versions/91578">1.2</a><br /><h3>Package description:</h3><p>Variance function estimation for models proposed by W. Sadler in his variance function program ('VFP', <http://www.aacb.asn.au/resources/useful-tools/variance-function-program-v14>). Here, the idea is to fit multiple variance functions to a data set and consequently assess which function reflects the relationship 'Var ~ Mean' best. For 'in-vitro diagnostic' ('IVD') assays modeling this relationship is of great importance when individual test-results are used for defining follow-up treatment of patients.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/963122019-12-17T16:43:49Z2019-12-17T16:43:49ZVCA was upgraded to version 1.4.2<a href="/packages/VCA">VCA</a> was <span class="action">upgraded</span> to version <a href="/packages/VCA/versions/91560">1.4.2</a><br /><h3>Package description:</h3><p>ANOVA and REML estimation of linear mixed models is implemented, once following Searle et al. (1991, ANOVA for unbalanced data), once making use of the 'lme4' package. The primary objective of this package is to perform a variance component analysis (VCA) according to CLSI EP05-A3 guideline "Evaluation of Precision of Quantitative Measurement Procedures" (2014). There are plotting methods for visualization of an experimental design, plotting random effects and residuals. For ANOVA type estimation two methods for computing ANOVA mean squares are implemented (SWEEP and quadratic forms). The covariance matrix of variance components can be derived, which is used in estimating confidence intervals. Linear hypotheses of fixed effects and LS means can be computed. LS means can be computed at specific values of covariables and with custom weighting schemes for factor variables. See ?VCA for a more comprehensive description of the features.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/947982019-11-14T23:04:27Z2019-11-14T23:04:27ZVCA was upgraded to version 1.4.1<a href="/packages/VCA">VCA</a> was <span class="action">upgraded</span> to version <a href="/packages/VCA/versions/90117">1.4.1</a><br /><h3>Package description:</h3><p>ANOVA and REML estimation of linear mixed models is implemented, once following Searle et al. (1991, ANOVA for unbalanced data), once making use of the 'lme4' package. The primary objective of this package is to perform a variance component analysis (VCA) according to CLSI EP05-A3 guideline "Evaluation of Precision of Quantitative Measurement Procedures" (2014). There are plotting methods for visualization of an experimental design, plotting random effects and residuals. For ANOVA type estimation two methods for computing ANOVA mean squares are implemented (SWEEP and quadratic forms). The covariance matrix of variance components can be derived, which is used in estimating confidence intervals. Linear hypotheses of fixed effects and LS means can be computed. LS means can be computed at specific values of covariables and with custom weighting schemes for factor variables. See ?VCA for a more comprehensive description of the features.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/944782019-11-06T19:23:53Z2019-11-06T19:23:53ZVFP was upgraded to version 1.1<a href="/packages/VFP">VFP</a> was <span class="action">upgraded</span> to version <a href="/packages/VFP/versions/89827">1.1</a><br /><h3>Package description:</h3><p>Variance function estimation for models proposed by W. Sadler in his variance function program ('VFP', <http://www.aacb.asn.au/resources/useful-tools/variance-function-program-v14>). Here, the idea is to fit multiple variance functions to a data set and consequently assess which function reflects the relationship 'Var ~ Mean' best. For 'in-vitro diagnostic' ('IVD') assays modeling this relationship is of great importance when individual test-results are used for defining follow-up treatment of patients.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/905242019-07-10T16:43:50Z2019-07-10T16:43:50ZVCA was upgraded to version 1.4.0<a href="/packages/VCA">VCA</a> was <span class="action">upgraded</span> to version <a href="/packages/VCA/versions/86058">1.4.0</a><br /><h3>Package description:</h3><p>ANOVA and REML estimation of linear mixed models is implemented, once following Searle et al. (1991, ANOVA for unbalanced data), once making use of the 'lme4' package. The primary objective of this package is to perform a variance component analysis (VCA) according to CLSI EP05-A3 guideline "Evaluation of Precision of Quantitative Measurement Procedures" (2014). There are plotting methods for visualization of an experimental design, plotting random effects and residuals. For ANOVA type estimation two methods for computing ANOVA mean squares are implemented (SWEEP and quadratic forms). The covariance matrix of variance components can be derived, which is used in estimating confidence intervals. Linear hypotheses of fixed effects and LS means can be computed. LS means can be computed at specific values of covariables and with custom weighting schemes for factor variables. See ?VCA for a more comprehensive description of the features.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/784182018-08-10T17:01:53Z2018-08-10T17:01:53ZVFP was released<a href="/packages/VFP">VFP</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>Variance function estimation for models proposed by W. Sadler in his variance function program ('VFP', <http://www.aacb.asn.au/resources/useful-tools/variance-function-program-v14>). Here, the idea is to fit multiple variance functions to a data set and consequently assess which function reflects the relationship 'Var ~ Mean' best. For 'in-vitro diagnostic' ('IVD') assays modeling this relationship is of great importance when individual test-results are used for defining follow-up treatment of patients.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/777032018-07-18T12:42:58Z2018-07-18T12:42:58ZVCA was upgraded to version 1.3.4<a href="/packages/VCA">VCA</a> was <span class="action">upgraded</span> to version <a href="/packages/VCA/versions/74077">1.3.4</a><br /><h3>Package description:</h3><p>ANOVA and REML estimation of linear mixed models is implemented, once following Searle et al. (1991, ANOVA for unbalanced data), once making use of the 'lme4' package. The primary objective of this package is to perform a variance component analysis (VCA) according to CLSI EP05-A3 guideline "Evaluation of Precision of Quantitative Measurement Procedures" (2014). There are plotting methods for visualization of an experimental design, plotting random effects and residuals. For ANOVA type estimation two methods for computing ANOVA mean squares are implemented (SWEEP and quadratic forms). The covariance matrix of variance components can be derived, which is used in estimating confidence intervals. Linear hypotheses of fixed effects and LS means can be computed. LS means can be computed at specific values of covariables and with custom weighting schemes for factor variables. See ?VCA for a more comprehensive description of the features.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/644792017-07-12T13:22:04Z2017-07-12T13:22:04ZVCA was upgraded to version 1.3.3<a href="/packages/VCA">VCA</a> was <span class="action">upgraded</span> to version <a href="/packages/VCA/versions/61674">1.3.3</a><br /><h3>Package description:</h3><p>ANOVA and REML estimation of linear mixed models is implemented, once following Searle et al. (1991, ANOVA for unbalanced data), once making use of the 'lme4' package. The primary objective of this package is to perform a variance component analysis (VCA) according to CLSI EP05-A3 guideline "Evaluation of Precision of Quantitative Measurement Procedures" (2014). There are plotting methods for visualization of an experimental design, plotting random effects and residuals. For ANOVA type estimation two methods for computing ANOVA mean squares are implemented (SWEEP and quadratic forms). The covariance matrix of variance components can be derived, which is used in estimating confidence intervals. Linear hypotheses of fixed effects and LS means can be computed. LS means can be computed at specific values of covariables and with custom weighting schemes for factor variables. See ?VCA for a more comprehensive description of the features.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/532312016-07-25T18:41:42Z2016-07-25T18:41:42ZVCA was upgraded to version 1.3.2<a href="/packages/VCA">VCA</a> was <span class="action">upgraded</span> to version <a href="/packages/VCA/versions/51336">1.3.2</a><br /><h3>Package description:</h3><p>ANOVA and REML estimation of linear mixed models is implemented, once following Searle et al. (1991, ANOVA for unbalanced data), once making use of the 'lme4' package. The primary objective of this package is to perform a variance component analysis (VCA) according to CLSI EP05-A3 guideline "Evaluation of Precision of Quantitative Measurement Procedures" (2014). There are plotting methods for visualization of an experimental design, plotting random effects and residuals. For ANOVA type estimation two methods for computing ANOVA mean squares are implemented (SWEEP and quadratic forms). The covariance matrix of variance components can be derived, which is used in estimating confidence intervals. Linear hypotheses of fixed effects and LS means can be computed. LS means can be computed at specific values of covariables and with custom weighting schemes for factor variables. See ?VCA for a more comprehensive description of the features.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/527332016-07-08T08:01:27Z2016-07-08T08:01:27ZSTB was upgraded to version 0.6.3.1<a href="/packages/STB">STB</a> was <span class="action">upgraded</span> to version <a href="/packages/STB/versions/50893">0.6.3.1</a><br /><h3>Package description:</h3><p>Provides an implementation of simultaneous tolerance bounds (STB), useful for checking whether a numeric vector fits to a hypothetical null-distribution or not. Furthermore, there are functions for computing STB (bands, intervals) for random variates of linear mixed models fitted with package 'VCA'. All kinds of, possibly transformed (studentized, standardized, Pearson-type transformed) random variates (residuals, random effects), can be assessed employing STB-methodology.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/525382016-06-30T16:41:30Z2016-06-30T16:41:30ZSTB was upgraded to version 0.6.3<a href="/packages/STB">STB</a> was <span class="action">upgraded</span> to version <a href="/packages/STB/versions/50704">0.6.3</a><br /><h3>Package description:</h3><p>Provides an implementation of simultaneous tolerance bounds (STB), useful for checking whether a numeric vector fits to a hypothetical null-distribution or not. Furthermore, there are functions for computing STB (bands, intervals) for random variates of linear mixed models fitted with package 'VCA'. All kinds of, possibly transformed (studentized, standardized, Pearson-type transformed) random variates (residuals, random effects), can be assessed employing STB-methodology.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/521282016-06-17T19:41:28Z2016-06-17T19:41:28ZSTB was released<a href="/packages/STB">STB</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>Provides an implementation of simultaneous tolerance bounds (STB), useful for checking whether a numeric vector fits to a hypothetical null-distribution or not. Furthermore, there are functions for computing STB (bands, intervals) for random variates of linear mixed models fitted with package 'VCA'. All kinds of, possibly transformed (studentized, standardized, Pearson-type transformed) random variates (residuals, random effects), can be assessed employing STB-methodology.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/501072016-04-04T12:01:31Z2016-04-04T12:01:31ZVCA was upgraded to version 1.3.1<a href="/packages/VCA">VCA</a> was <span class="action">upgraded</span> to version <a href="/packages/VCA/versions/48465">1.3.1</a><br /><h3>Package description:</h3><p>ANOVA and REML estimation of linear mixed models is implemented, once following Searle et al. (1991, ANOVA for unbalanced data), once making use of the 'lme4' package. The primary objective of this package is to a perform variance component analysis (VCA) according to CLSI EP05-A3 guideline "Evaluation of Precision of Quantitative Measurement Procedures" (2014). There are plotting methods for visualization of an experimental design, plotting random effects and residuals. For ANOVA type estimation two methods for computing ANOVA mean squares are implemented (SWEEP and quadratic forms). The covariance matrix of variance components can be derived, which is used in estimating confidence intervals. Linear hypotheses of fixed effects and LS means can be computed. LS means can be computed at specific values of covariables and with custom weighting schemes for factor variables. See ?VCA for a more comprehensive description of the features.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/497482016-03-23T23:01:31Z2016-03-23T23:01:31ZVCA was upgraded to version 1.3<a href="/packages/VCA">VCA</a> was <span class="action">upgraded</span> to version <a href="/packages/VCA/versions/48107">1.3</a><br /><h3>Package description:</h3><p>ANOVA-type estimation (prediction) of random effects in linear mixed models is implemented, following Searle et al. (1991, ANOVA for unbalanced data). For better performance the SWEEP-Operator is implemented for generating the ANOVA Type-1 error sum of squares. Restricted Maximum Likelihood (REML) estimation is also available making use of the 'lme4' package. The primary objective of this package is to perform Variance Component Analyses (VCA). This is a special type of analysis frequently used in verifying the precision performance of diagnostics. The Satterthwaite approximation of the total degrees of freedom and for individual variance components is implemented for models fitted by ANOVA as well as for models fitted by REML. These are used in the Chi-Squared tests against a claimed value, and in the respective confidence intervals. Satterthwaite's approximation of denominator degrees of freedom in t-/F-tests of fixed effects are also available. For models fitted by (REML) the variance-covariance matrix of the variance components is approximated by the method pointed out in Giesbrecht & Burns (1985), which is required for applying the Satterthwaite approximation of the degrees of freedom. For models fitted by ANOVA the method pointed out in Searle et al. (1991) employing quadratic forms generating ANOVA sum of squares is also available. There are several functions for extracting, random effects, fixed effects, variance-covariance matrices of random and fixed effects. Residuals (marginal, conditional) can be extracted as raw, standardized and studentized residuals. Additionally, plotting methods for residuals and random effects and a variability chart are available. The latter is useful for visualizing the variability in sub-classes emerging from the experimental design.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/423572015-07-20T16:32:49Z2015-07-20T16:32:49ZVCA was upgraded to version 1.2<a href="/packages/VCA">VCA</a> was <span class="action">upgraded</span> to version <a href="/packages/VCA/versions/42156">1.2</a><br /><h3>Package description:</h3><p>ANOVA-type estimation (prediction) of random effects in linear mixed models is implemented, following Searle et al. 1991 (ANOVA for unbalanced data). For better performance the SWEEP-Operator is now implemented for generating the ANOVA Type-1 error sum of squares. The primary objective of this package is to perform Variance Component Analyses (VCA). This is a special type of analysis frequently used in verifying the precision performance of diagnostics. The Satterthwaite approximation of the total degrees of freedom and for individual variance components is implemented. These are used in the Chi-Squared tests against a claimed value, and in the respective confidence intervals. Satterthwaite's approximation of denominator degrees of freedom in t-/F-tests of fixed effects are also available. There are several functions for extracting, random effects, fixed effects, variance-covariance matrices of random and fixed effects. Residuals (marginal, conditional) can be extracted as raw, standardized and studentized residuals. Additionally, plotting methods for residuals and random effects and a variability chart are available. The latter is useful for visualizing the variability in sub-classes emerging from the experimental design.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/403662015-04-27T07:12:02Z2015-04-27T07:12:02ZVCA was upgraded to version 1.1.1<a href="/packages/VCA">VCA</a> was <span class="action">upgraded</span> to version <a href="/packages/VCA/versions/40167">1.1.1</a><br /><h3>Package description:</h3><p>ANOVA-type estimation (prediction) of random effects and variance components in linear mixed models, is implemented. Random models, a sub-set of mixed models, can be fit applying a Variance Component Analysis (VCA). This is a special type of analysis frequently used in verifying the precision performance of diagnostics. The Satterthwaite approximation of the total degrees of freedom is implemented. There are several functions for extracting, random effects, fixed effects, variance-covariance matrices of random and fixed effects. Residuals can be extracted as raw, standardized and studentized residuals. Additionally, a variability chart is implemented for visualizing the variability in sub-classes emerging from an experimental design ('varPlot').</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/396132015-03-16T09:51:58Z2015-03-16T09:51:58ZVCA was released<a href="/packages/VCA">VCA</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>ANOVA and REML estimation of linear mixed models is implemented, once following Searle et al. (1991, ANOVA for unbalanced data), once making use of the 'lme4' package. The primary objective of this package is to perform a variance component analysis (VCA) according to CLSI EP05-A3 guideline "Evaluation of Precision of Quantitative Measurement Procedures" (2014). There are plotting methods for visualization of an experimental design, plotting random effects and residuals. For ANOVA type estimation two methods for computing ANOVA mean squares are implemented (SWEEP and quadratic forms). The covariance matrix of variance components can be derived, which is used in estimating confidence intervals. Linear hypotheses of fixed effects and LS means can be computed. LS means can be computed at specific values of covariables and with custom weighting schemes for factor variables. See ?VCA for a more comprehensive description of the features.</p>crantastic.org