Description Usage Arguments Value Note Author(s) Examples
View source: R/formula2index.R
These functions will convert a formula object to a binary index and vice versa.
1 2 3 | formula2index(big.X, formula, data)
index2formula(index, maximal.mod)
|
big.X |
The design matrix under the maximal model. |
formula |
An object of class |
data |
An object of class |
maximal.mod |
An object of class |
index |
A binary vector, of the same length as the number of log-linear parameters in the maximal model, indicating which parameters are present in the model to be converted to a formula. |
The function formula2index
will produce a binary vector of the same length as the number of log-linear
parameters in the maximal model, indicating which parameters are present in the model represented by the
argument formula
.
The function index2formula
will produce an object of class "formula"
: a symbolic description of the model given by
the argument index
.
This function will not typically be called by the user.
Antony M. Overstall A.M.Overstall@soton.ac.uk.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | data(ScotPWID)
## Load the ScotPWID data
maximal.mod<-glm(y~(S1+S2+S3+S4+Region+Gender+Age)^2,family=poisson,contrasts=list(
S1="contr.sum",S2="contr.sum",S3="contr.sum",S4="contr.sum",
Region="contr.sum",Gender="contr.sum",Age="contr.sum"),data=ScotPWID,x=TRUE)
## Fit the maximal model containing all two-way interactions.
big.X<-maximal.mod$x
## Set the design matrix under the maximal model
index<-formula2index(big.X=big.X,
formula=~S1+S2+S3+S4+Region+Gender+Age+S1:S2+S1:Age+S2:Gender+S3:S4+S4:Age,
data=ScotPWID)
## Find the index under the model with the following interactions:
## S1:S2
## S1:Age
## S2:Gender
## S3:S4
## S4:Age
index
## Print index
# [1] 1 1 1 1 1 1 1 1 1 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0
index2formula(index=index,maximal.mod=maximal.mod)
## Go back to formula
#y ~ S1 + S2 + S3 + S4 + Region + Gender + Age + S1:S2 + S1:Age +
# S2:Gender + S3:S4 + S4:Age
|
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