Package: VCA 1.5.2

Andre Schuetzenmeister

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.

Authors:Andre Schuetzenmeister [aut, cre], Florian Dufey [aut]

VCA_1.5.2.tar.gz
VCA_1.5.2.tar.gz(r-4.7-arm64)VCA_1.5.2.tar.gz(r-4.7-x86_64)VCA_1.5.2.tar.gz(r-4.6-arm64)VCA_1.5.2.tar.gz(r-4.6-x86_64)
VCA_1.5.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
VCA/json (API)

# Install 'VCA' in R:

install.packages('VCA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

openblas– Optimized BLAS
fortran– Runtime library for GNU Fortran applications

Datasets:

CA19_9 - Reproducibility Example Dataset from CLSI EP05-A3
chol2invData - Dataset Generating Error in Function 'chol2inv'
dataEP05A2_1 - Simulated Data of a CLSI EP05-A2 20/2/2 Experiment
dataEP05A2_2 - Simulated Data of a CLSI EP05-A2 20/2/2 Experiment
dataEP05A2_3 - Simulated Data of a CLSI EP05-A2 20/2/2 Experiment
dataEP05A3_MS_1 - Simulated Data of a CLSI EP05-A3 3/5/5 Multi-Site Experiment
dataEP05A3_MS_2 - Simulated Data of a CLSI EP05-A3 3/5/5 Multi-Site Experiment
dataEP05A3_MS_3 - Simulated Data of a CLSI EP05-A3 3/5/5 Multi-Site Experiment
dataRS0003_1 - Simulated Repeated Measurements Data.
dataRS0003_2 - Simulated Repeated Measurements Data.
dataRS0003_3 - Simulated Repeated Measurements Data.
dataRS0005_1 - Simulated Data of 5/3 Experiment.
dataRS0005_2 - Simulated Data of 5/3 Experiment.
dataRS0005_3 - Simulated Data of 5/3 Experiment.
Glucose - Inermediate Precision Data from CLSI EP05-A3
HugeData - Huge Dataset with Three Variables
LSMeans_Data - Dataset for Unit-Testing of LS Means
LSMeans_Data - Dataset for Unit-Testing of LS Means
MLrepro - Multi-Lot Reproducibility Data.
Orthodont - Orthodont dataset from R-package 'nlme'
realData - Real-World Data
ReproData1 - Multi-Site Data for Estimating Reproducibility Precision
sleepstudy - Sleepstudy dataset from R-package 'lme4'
VCAdata1 - Simulated Data for Variance Component Analysis.

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblas fortran

5.85 score 2 stars 5 packages 180 scripts 1.3k downloads 32 mentions 48 exports 15 dependencies

Last updated from:59e700c78d. Checks:6 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	234
linux-devel-x86_64	OK	274
source / vignettes	OK	232
linux-release-arm64	OK	212
linux-release-x86_64	OK	274
wasm-release	OK	155

Exports:anovaMM anovaVCA as.matrix.VCA as.matrix.VCAinference coef.VCA fitLMM fitVCA fixef fixef.VCA getCI getDF getIP.remlVCA getL getMat getMM getV isBalanced legend.m lmerSummary lsmeans model.frame.VCA model.matrix.VCA MPinv orderData plot.VCA plotRandVar predict.VCA print.VCA print.VCAinference protectedCall ranef ranef.VCA remlMM remlVCA reScale residuals.VCA Scale scaleData solveMME stepwiseVCA summarize.VCA summarize.VCAinference test.fixef test.lsmeans varPlot VCAinference vcov.VCA vcovVC

Dependencies:boot lattice lme4 MASS Matrix minqa nlme nloptr numDeriv rbibutils Rcpp RcppEigen Rdpack reformulas rlang

R-Package VCA for Variance Component Analysis

Rendered fromVCA_package_vignette.Rmdusingknitr::rmarkdown

Last update: 2024-01-19
Started: 2019-12-17

Help page	Topics
(V)ariance (C)omponent (A)nalysis.	VCA-package VCA
ANOVA-Type Estimation of Mixed Models	anovaMM
ANOVA-Type Estimation of Variance Components for Random Models	anovaVCA
Standard 'as.matrix' Method for 'VCA' S3-Objects	as.matrix.VCA
Standard 'as.matrix' Method for 'VCAinference' S3-Objects	as.matrix.VCAinference
Build a Nested List.	buildList
Reproducibility Example Dataset from CLSI EP05-A3	CA19_9
Check for Availability of Intel's Math Kernel Library	check4MKL
Check Random Model for Given Dataset.	checkData
Check Tow Formula Terms for Potential Problems.	checkVars
Dataset Generating Error in Function 'chol2inv'	chol2invData
Extract Fixed Effects from 'VCA' Object	coef.VCA
Combine Variance Components and Adjust Degrees of Freedom.	combineVC
Simulated Data of a CLSI EP05-A2 20/2/2 Experiment	dataEP05A2_1
Simulated Data of a CLSI EP05-A2 20/2/2 Experiment	dataEP05A2_2
Simulated Data of a CLSI EP05-A2 20/2/2 Experiment	dataEP05A2_3
Simulated Data of a CLSI EP05-A3 3/5/5 Multi-Site Experiment	dataEP05A3_MS_1
Simulated Data of a CLSI EP05-A3 3/5/5 Multi-Site Experiment	dataEP05A3_MS_2
Simulated Data of a CLSI EP05-A3 3/5/5 Multi-Site Experiment	dataEP05A3_MS_3
Simulated Repeated Measurements Data.	dataRS0003_1
Simulated Repeated Measurements Data.	dataRS0003_2
Simulated Repeated Measurements Data.	dataRS0003_3
Simulated Data of 5/3 Experiment.	dataRS0005_1
Simulated Data of 5/3 Experiment.	dataRS0005_2
Simulated Data of 5/3 Experiment.	dataRS0005_3
Variance-Covariance Matrix of Fixed Effects as Function of Covariance Parameter Estimates	DfSattHelper
Convert Objects to Detailed Error Message.	errorMessage
Fit Linear Mixed Model by ANOVA or REML	fitLMM
Fit Variance Component Model by ANOVA or REML	fitVCA
Generic Method for Extracting Fixed Effects from a Fitted Model	fixef
Extract Fixed Effects from 'VCA' Object	fixef.VCA
Calling F90-implementation of the SWEEP-Operator	Fsweep
Extract Confidence Intervals from VCA-Objects.	getCI
Degrees of Freedom for Testing Linear Contrasts of Fixed Effects and Least Square Means	getDDFM
Extract Degrees of Freedom from Linear Hypotheses of Fixed Effects or LS Means	getDF
Giesbrecht & Burns Approximation of the Variance-Covariance Matrix of Variance Components	getGB
Intermediate Precision for remlVCA-fitted objects of class 'VCA'	getIP.remlVCA
Construct Linear Contrast Matrix for Hypothesis Tests	getL
Extract a Specific Matrix from a 'VCA' Object	getMat
Overparameterized Design Matrices	getMM
ANOVA Sum of Squares via Sweeping	getSSQsweep
Determine V-Matrix for a 'VCA' Object	getV
Inermediate Precision Data from CLSI EP05-A3	Glucose
Huge Dataset with Three Variables	HugeData
Check Whether Design Is Balanced Or Not	isBalanced
Add Legend to Margin.	legend.m
Construct Variance-Covariance Matrix of Random Effects for Models Fitted by Function 'lmer'	lmerG
Derive and Compute Matrices for Objects Fitted by Function 'lmer'	lmerMatrices
Derive VCA-Summary Table from an Object Fitted via Function 'lmer'	lmerSummary
Load 'RevoUtilsMath'-package if available	load_if_installed
Least Squares Means of Fixed Effects	lsmeans
Dataset for Unit-Testing of LS Means	LSMeans_Data
Contrast Matrix for LS Means	lsmMat
Multi-Lot Reproducibility Data.	MLrepro
Extract the Model Frame from a 'VCA' Object	model.frame.VCA
Model Matrix of a Fitted VCA-Object	model.matrix.VCA
Moore-Penrose Generalized Inverse of a Matrix	MPinv
Re-Order Data.Frame	orderData
Orthodont dataset from R-package 'nlme'	Orthodont
Standard 'plot' Method for 'VCA' S3-Objects.	plot.VCA
Plot Random Variates of a Mixed Model ('VCA' Object).	plotRandVar
Predictions from a Model Fitted by 'fitLMM'	predict.VCA
Standard Printing Method for Objects of Class 'VCA'	print.VCA
Standard Print Method for Objects of Class 'VCAinference'	print.VCAinference
Wrap Function-Calls to Execute Additional Checks.	protectedCall
Generic Method for Extracting Random Effects from a Fitted Model	ranef
Extract Random Effects from 'VCA' Object	ranef.VCA
Real-World Data	realData
Fit Linear Mixed Models via REML	remlMM
Perform (V)ariance (C)omponent (A)nalysis via REML-Estimation	remlVCA
Multi-Site Data for Estimating Reproducibility Precision	ReproData1
Re-Scale results of 'VCA' or 'VCAinference'	reScale
Extract Residuals of a 'VCA' Object	resid residuals.VCA
Satterthwaite Approximation for Total Degrees of Freedom and for Single Variance Components	SattDF
Automatically Scale Data Calling these Functions: 'anovaVCA', 'anovaMM', 'remlVCA' or 'remlMM'	Scale
Scale Response Variable to Ensure Robust Numerical Calculations	scaleData
sleepstudy dataset from R-package 'lme4'	sleepstudy
Solve System of Linear Equations using Inverse of Cholesky-Root	Solve
Solve Mixed Model Equations	solveMME
Bottom-Up Step-Wise VCA-Analysis of the Complete Dataset	stepwiseVCA
Summarize Outcome of a Variance Component Analysis.	summarize.VCA summarize.VCAinference
Perform t-Tests for Linear Contrasts on Fixed Effects	test.fixef
Perform t-Tests for Linear Contrasts on LS Means	test.lsmeans
Compute the Trace of a Matrix	Trace
Variability Chart for Hierarchical Models.	varPlot
Simulated Data for Variance Component Analysis.	VCAdata1
Inferential Statistics for VCA-Results	VCAinference
Calculate Variance-Covariance Matrix of Fixed Effects for an 'VCA' Object	vcov.VCA
Calculate Variance-Covariance Matrix and Standard Errors of Fixed Effects for an 'VCA' Object	vcovFixed
Calculate Variance-Covariance Matrix of Variance Components of 'VCA' objects	vcovVC

Package: VCA 1.5.2

VCA: Variance Component Analysis

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