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VCA (version 1.5.1)

Variance Component Analysis

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.

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Version

Install

install.packages('VCA')

Monthly Downloads

1,041

Version

1.5.1

License

GPL (>= 3)

Maintainer

Andre Schuetzenmeister

Last Published

March 7th, 2024

Functions in VCA (1.5.1)

Orthodont dataset from R-package 'nlme'

Moore-Penrose Generalized Inverse of a Matrix

Multi-Site Data for Estimating Reproducibility Precision

Multi-Lot Reproducibility Data.

Compute the Trace of a Matrix

Solve System of Linear Equations using Inverse of Cholesky-Root

Standard 'as.matrix' Method for 'VCA' S3-Objects

ANOVA-Type Estimation of Variance Components for Random Models

(V)ariance (C)omponent (A)nalysis.

Simulated Data for Variance Component Analysis.

ANOVA-Type Estimation of Mixed Models

Inferential Statistics for VCA-Results

Build a Nested List.

Satterthwaite Approximation for Total Degrees of Freedom and for Single Variance Components

Check Random Model for Given Dataset.

as.matrix.VCAinference

Standard 'as.matrix' Method for 'VCAinference' S3-Objects

Automatically Scale Data Calling these Functions: 'anovaVCA', 'anovaMM', 'remlVCA' or 'remlMM'

Check for Availability of Intel's Math Kernel Library

Simulated Repeated Measurements Data.

dataEP05A3_MS_2

Simulated Data of a CLSI EP05-A3 3/5/5 Multi-Site Experiment

Simulated Data of 5/3 Experiment.

Simulated Data of a CLSI EP05-A2 20/2/2 Experiment

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

Check Tow Formula Terms for Potential Problems.

Dataset Generating Error in Function 'chol2inv'

Simulated Data of 5/3 Experiment.

Giesbrecht & Burns Approximation of the Variance-Covariance Matrix of Variance Components

Extract Degrees of Freedom from Linear Hypotheses of Fixed Effects or LS Means

Convert Objects to Detailed Error Message.

Extract Fixed Effects from 'VCA' Object

Generic Method for Extracting Fixed Effects from a Fitted Model

Simulated Data of a CLSI EP05-A2 20/2/2 Experiment

Extract Fixed Effects from 'VCA' Object

Degrees of Freedom for Testing Linear Contrasts of Fixed Effects and Least Square Means

Add Legend to Margin.

Extract Confidence Intervals from VCA-Objects.

Simulated Data of 5/3 Experiment.

dataEP05A3_MS_3

Simulated Data of a CLSI EP05-A3 3/5/5 Multi-Site Experiment

Simulated Repeated Measurements Data.

Derive VCA-Summary Table from an Object Fitted via Function lmer

Check Whether Design Is Balanced Or Not

Fit Linear Mixed Model by ANOVA or REML

Determine V-Matrix for a 'VCA' Object

Fit Variance Component Model by ANOVA or REML

load_if_installed

Load 'RevoUtilsMath'-package if available

Simulated Repeated Measurements Data.

Construct Linear Contrast Matrix for Hypothesis Tests

ANOVA Sum of Squares via Sweeping

Intermediate Precision for remlVCA-fitted objects of class 'VCA'

print.VCAinference

Standard Print Method for Objects of Class 'VCAinference'

Standard Printing Method for Objects of Class 'VCA'

Construct Variance-Covariance Matrix of Random Effects for Models Fitted by Function 'lmer'

model.frame.VCA

Extract the Model Frame from a 'VCA' Object

Overparameterized Design Matrices

Wrap Function-Calls to Execute Additional Checks.

Derive and Compute Matrices for Objects Fitted by Function 'lmer'

model.matrix.VCA

Model Matrix of a Fitted VCA-Object

Extract Random Effects from 'VCA' Object

Fit Linear Mixed Models via REML

Standard 'plot' Method for 'VCA' S3-Objects.

Real-World Data

Re-Order Data.Frame

Plot Random Variates of a Mixed Model ('VCA' Object).

Predictions from a Model Fitted by fitLMM

Perform (V)ariance (C)omponent (A)nalysis via REML-Estimation

Extract a Specific Matrix from a 'VCA' Object

Contrast Matrix for LS Means

sleepstudy dataset from R-package 'lme4'

Scale Response Variable to Ensure Robust Numerical Calculations

Least Squares Means of Fixed Effects

Extract Residuals of a 'VCA' Object

Re-Scale results of 'VCA' or 'VCAinference'

Summarize Outcome of a Variance Component Analysis.

Generic Method for Extracting Random Effects from a Fitted Model

Calculate Variance-Covariance Matrix of Variance Components of 'VCA' objects

Variability Chart for Hierarchical Models.

Perform t-Tests for Linear Contrasts on LS Means

Perform t-Tests for Linear Contrasts on Fixed Effects

Solve Mixed Model Equations

Bottom-Up Step-Wise VCA-Analysis of the Complete Dataset

Calculate Variance-Covariance Matrix and Standard Errors of Fixed Effects for an 'VCA' Object

Calculate Variance-Covariance Matrix of Fixed Effects for an 'VCA' Object

Variance-Covariance Matrix of Fixed Effects as Function of Covariance Parameter Estimates

Calling F90-implementation of the SWEEP-Operator

Inermediate Precision Data from CLSI EP05-A3

Huge Dataset with Three Variables

Reproducibility Example Dataset from CLSI EP05-A3

Dataset for Unit-Testing of LS Means