VCA: Variance Component Analysis
Version 1.3.3

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.

Getting started

Package details

AuthorAndre Schuetzenmeister [aut, cre], Florian Dufey [ctb]
Date of publication2017-07-12 12:52:42 UTC
MaintainerAndre Schuetzenmeister <[email protected]>
LicenseGPL (>= 3)
Version1.3.3
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("VCA")

Try the VCA package in your browser

Any scripts or data that you put into this service are public.

VCA documentation built on July 12, 2017, 5:02 p.m.