VCA

Variance Component Analysis

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.

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Description file content

Package
VCA
Version
1.4.0
Date
2019-07-10
Title
Variance Component Analysis
Author
Andre Schuetzenmeister [aut, cre], Florian Dufey [aut]
Maintainer
Andre Schuetzenmeister
Depends
R (>= 3.0.0)
Imports
stats, graphics, grDevices, lme4, Matrix, methods, numDeriv
Suggests
VFP, STB
Description
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.
License
GPL (>= 3)
RoxygenNote
6.0.1
NeedsCompilation
yes
Packaged
2019-07-10 16:00:34 UTC; schueta6
Repository
CRAN
Date/Publication
2019-07-10 16:32:42 UTC

install.packages('VCA')

1.4.0

7 days ago

Andre Schuetzenmeister

GPL (>= 3)

Depends on

R (>= 3.0.0)

Imports

stats, graphics, grDevices, lme4, Matrix, methods, numDeriv

Suggests

VFP, STB

Discussions