VCA (version 1.5.1)

getMM: Overparameterized Design Matrices

Description

Function getMM constructs overparameterized design matrices from a model formula and a data.frame.

Usage

getMM(form, Data, keep.order = TRUE)

Arguments

form

(formula) with or without response specifying the model to be fit

Data

(data.frame) with the data

keep.order

(logical) TRUE = terms in 'form' should keep their positions, otherwise main effects come first and all interactions will be put into increasing order

Author

Andre Schuetzenmeister

Details

This function constructs the overparameterized design matrix for a given dataset 'Data' according to the model formula 'form'. Each combination of factor-levels and or numeric variables is identified and accounted for by a separate column. See examples for differences compared to function 'model.matrix' (stats). This type of design matrix is used e.g. in constructing A-matrices of quadratic forms in \(y\) expressing ANOVA sums of squares as such. This is key functionality of functions anovaVCA and anovaMM used e.g. in constructing the coefficient matrix \(C\) whose inverse is used in solving for ANOVA Type-1 based variance components..

Examples

if (FALSE) {
# load example data (CLSI EP05-A2 Within-Lab Precision Experiment)
data(dataEP05A2_3)
tmpData <- dataEP05A2_3[1:10,] 

# check out the differences
getMM(~day+day:run, tmpData)
model.matrix(~day+day:run, tmpData)

# adapt factor variables in 'tmpData'
tmpData$day <- factor(tmpData$day)

# check out the differences now
getMM(~day+day:run, tmpData)
model.matrix(~day+day:run, tmpData)

# numeric covariate 'cov'
tmpData2 <- dataEP05A2_3[1:10,] 
tmpData2$cov <- 10+rnorm(10,,3)
model.matrix(~day*cov, tmpData2)
}