model_terms_clme {CLME}

Create model matrices for clme

Description

Parses formulas to creates model matrices for clme.

Usage

model_terms_clme(formula, data)

Arguments

formula

a formula defining a linear fixed or mixed effects model. The constrained effect(s) must come before any unconstrained covariates on the right-hand side of the expression. The first ncon terms will be assumed to be constrained.

data

data frame containing the variables in the model.

Value

A list with the elements:

Y	response variable
X1	design matrix for constrained effect
X2	design matrix for covariates
P1	number of constrained coefficients
U	matrix of random effects
formula	the final formula call (automatically removes intercept)
dframe	the dataframe containing the variables in the model
REidx	an element to define random effect variance components
REnames	an element to define random effect variance components

Note

The first term on the right-hand side of the formula should be the fixed effect with constrained coefficients. Random effects are represented with a vertical bar, so for example the random effect U would be included by Y ~ X1 + (1|U).

The intercept is removed automatically. This is done to ensure that parameter estimates are of the means of interest, rather than being expressed as a mean with offsets.

See Also

CLME-package clme

Examples

data( rat.blood )
model_terms_clme( mcv ~ time + temp + sex + (1|id) , data = rat.blood )