Package: VCA 1.5.1

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_1.5.1.tar.gz
VCA_1.5.1.tar.gz(r-4.5-noble)VCA_1.5.1.tar.gz(r-4.4-noble)
VCA_1.5.1.tgz(r-4.4-emscripten)VCA_1.5.1.tgz(r-4.3-emscripten)
VCA.pdf |VCA.html
VCA/json (API)

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

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • fortran– Runtime library for GNU Fortran applications
Datasets:
  • CA19_9 - Reproducibility Example Dataset from CLSI EP05-A3
  • Glucose - Inermediate Precision Data from CLSI EP05-A3
  • HugeData - Huge Dataset with Three Variables
  • LSMeans_Data - Dataset for Unit-Testing of LS Means
  • MLrepro - Multi-Lot Reproducibility Data.
  • Orthodont - Orthodont dataset from R-package 'nlme'
  • ReproData1 - Multi-Site Data for Estimating Reproducibility Precision
  • VCAdata1 - Simulated Data for Variance Component Analysis.
  • 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.
  • realData - Real-World Data
  • sleepstudy - Sleepstudy dataset from R-package 'lme4'

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

fortranopenblas

5.90 score 2 stars 4 packages 167 scripts 928 downloads 32 mentions 48 exports 11 dependencies

Last updated 10 months agofrom:6ba209256c. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 03 2024
R-4.5-linux-x86_64NOTEDec 03 2024

Exports:anovaMManovaVCAas.matrix.VCAas.matrix.VCAinferencecoef.VCAfitLMMfitVCAfixeffixef.VCAgetCIgetDFgetIP.remlVCAgetLgetMatgetMMgetVisBalancedlegend.mlmerSummarylsmeansmodel.frame.VCAmodel.matrix.VCAMPinvorderDataplot.VCAplotRandVarpredict.VCAprint.VCAprint.VCAinferenceprotectedCallranefranef.VCAremlMMremlVCAreScaleresiduals.VCAScalescaleDatasolveMMEstepwiseVCAsummarize.VCAsummarize.VCAinferencetest.fixeftest.lsmeansvarPlotVCAinferencevcov.VCAvcovVC

Dependencies:bootlatticelme4MASSMatrixminqanlmenloptrnumDerivRcppRcppEigen

R-Package VCA for Variance Component Analysis

Rendered fromVCA_package_vignette.Rmdusingknitr::rmarkdownon Dec 03 2024.

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

Readme and manuals

Help Manual

Help pageTopics
(V)ariance (C)omponent (A)nalysis.VCA-package VCA
ANOVA-Type Estimation of Mixed ModelsanovaMM
ANOVA-Type Estimation of Variance Components for Random ModelsanovaVCA
Standard 'as.matrix' Method for 'VCA' S3-Objectsas.matrix.VCA
Standard 'as.matrix' Method for 'VCAinference' S3-Objectsas.matrix.VCAinference
Build a Nested List.buildList
Reproducibility Example Dataset from CLSI EP05-A3CA19_9
Check for Availability of Intel's Math Kernel Librarycheck4MKL
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' Objectcoef.VCA
Simulated Data of a CLSI EP05-A2 20/2/2 ExperimentdataEP05A2_1
Simulated Data of a CLSI EP05-A2 20/2/2 ExperimentdataEP05A2_2
Simulated Data of a CLSI EP05-A2 20/2/2 ExperimentdataEP05A2_3
Simulated Data of a CLSI EP05-A3 3/5/5 Multi-Site ExperimentdataEP05A3_MS_1
Simulated Data of a CLSI EP05-A3 3/5/5 Multi-Site ExperimentdataEP05A3_MS_2
Simulated Data of a CLSI EP05-A3 3/5/5 Multi-Site ExperimentdataEP05A3_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 EstimatesDfSattHelper
Convert Objects to Detailed Error Message.errorMessage
Fit Linear Mixed Model by ANOVA or REMLfitLMM
Fit Variance Component Model by ANOVA or REMLfitVCA
Generic Method for Extracting Fixed Effects from a Fitted Modelfixef
Extract Fixed Effects from 'VCA' Objectfixef.VCA
Calling F90-implementation of the SWEEP-OperatorFsweep
Extract Confidence Intervals from VCA-Objects.getCI
Degrees of Freedom for Testing Linear Contrasts of Fixed Effects and Least Square MeansgetDDFM
Extract Degrees of Freedom from Linear Hypotheses of Fixed Effects or LS MeansgetDF
Giesbrecht & Burns Approximation of the Variance-Covariance Matrix of Variance ComponentsgetGB
Intermediate Precision for remlVCA-fitted objects of class 'VCA'getIP.remlVCA
Construct Linear Contrast Matrix for Hypothesis TestsgetL
Extract a Specific Matrix from a 'VCA' ObjectgetMat
Overparameterized Design MatricesgetMM
ANOVA Sum of Squares via SweepinggetSSQsweep
Determine V-Matrix for a 'VCA' ObjectgetV
Inermediate Precision Data from CLSI EP05-A3Glucose
Huge Dataset with Three VariablesHugeData
Check Whether Design Is Balanced Or NotisBalanced
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 availableload_if_installed
Least Squares Means of Fixed Effectslsmeans
Dataset for Unit-Testing of LS MeansLSMeans_Data
Contrast Matrix for LS MeanslsmMat
Multi-Lot Reproducibility Data.MLrepro
Extract the Model Frame from a 'VCA' Objectmodel.frame.VCA
Model Matrix of a Fitted VCA-Objectmodel.matrix.VCA
Moore-Penrose Generalized Inverse of a MatrixMPinv
Re-Order Data.FrameorderData
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 Modelranef
Extract Random Effects from 'VCA' Objectranef.VCA
Real-World DatarealData
Fit Linear Mixed Models via REMLremlMM
Perform (V)ariance (C)omponent (A)nalysis via REML-EstimationremlVCA
Multi-Site Data for Estimating Reproducibility PrecisionReproData1
Re-Scale results of 'VCA' or 'VCAinference'reScale
Extract Residuals of a 'VCA' Objectresid residuals.VCA
Satterthwaite Approximation for Total Degrees of Freedom and for Single Variance ComponentsSattDF
Automatically Scale Data Calling these Functions: 'anovaVCA', 'anovaMM', 'remlVCA' or 'remlMM'Scale
Scale Response Variable to Ensure Robust Numerical CalculationsscaleData
sleepstudy dataset from R-package 'lme4'sleepstudy
Solve System of Linear Equations using Inverse of Cholesky-RootSolve
Solve Mixed Model EquationssolveMME
Bottom-Up Step-Wise VCA-Analysis of the Complete DatasetstepwiseVCA
Summarize Outcome of a Variance Component Analysis.summarize.VCA summarize.VCAinference
Perform t-Tests for Linear Contrasts on Fixed Effectstest.fixef
Perform t-Tests for Linear Contrasts on LS Meanstest.lsmeans
Compute the Trace of a MatrixTrace
Variability Chart for Hierarchical Models.varPlot
Simulated Data for Variance Component Analysis.VCAdata1
Inferential Statistics for VCA-ResultsVCAinference
Calculate Variance-Covariance Matrix of Fixed Effects for an 'VCA' Objectvcov.VCA
Calculate Variance-Covariance Matrix and Standard Errors of Fixed Effects for an 'VCA' ObjectvcovFixed
Calculate Variance-Covariance Matrix of Variance Components of 'VCA' objectsvcovVC