model.design: Extract a design matrix and specials from a model.frame

Description

Extract design matrix and data specials from a model.frame

Usage

model.design(
  terms,
  data,
  xlev = NULL,
  dropIntercept = FALSE,
  maxOrder = 1,
  unspecialsDesign = TRUE,
  specialsFactor = FALSE,
  specialsDesign = FALSE
)

Value

A list which contains - the design matrix with the levels of the variables stored in attribute 'levels' - separate data.frames which contain the values of the special variables.

Arguments

terms: terms object as obtained either with function terms or strip.terms.
data: A data set in which terms are defined.
xlev: a named list of character vectors giving the full set of levels to be assumed for the factors. Can have less elements, in which case the other levels are learned from the data.
dropIntercept: If TRUE drop intercept term from the design matrix
maxOrder: An error is produced if special variables are involved in interaction terms of order higher than max.order.
unspecialsDesign: A logical value: if TRUE apply model.matrix to unspecial covariates. If FALSE extract unspecial covariates from data.
specialsFactor: A character vector containing special variables which should be coerced into a single factor. If TRUE all specials are treated in this way, if FALSE none of the specials is treated in this way.
specialsDesign: A character vector containing special variables which should be transformed into a design matrix via model.matrix. If TRUE all specials are treated in this way.

Author

Thomas A. Gerds <tag@biostat.ku.dk>

Details

The function separates special terms from the unspecial terms and returns a list of design matrices, one for unspecial terms and one for each special. Some special specials cannot or should not be evaluated in data. E.g., y~a+dummy(x)+strata(v) the function strata can and should be evaluated, but in order to have model.frame also evaluate dummy(x) one would be to define and export the function dummy. Still the term dummy(x) can be used to identify a special treatment of the variable x. To deal with this case, one can specify stripSpecials="dummy". In addition, the data should include variables strata(z) and x, not dummy(x). See examples. The function untangle.specials of the survival function does a similar job.

Examples

Run this code

# specials that are evaluated. here ID needs to be defined 
set.seed(8)
d <- data.frame(y=rnorm(5),x=factor(c("a","b","b","a","c")),z=c(2,2,7,7,7),v=sample(letters)[1:5])
d$z <- factor(d$z,levels=c(1:8))
ID <- function(x)x
f <- formula(y~x+ID(z))
t <- terms(f,special="ID",data=d)
mda <- model.design(terms(t),data=d,specialsFactor=TRUE)
mda$ID
mda$design
## 
mdb <- model.design(terms(t),data=d,specialsFactor=TRUE,unspecialsDesign=FALSE)
mdb$ID
mdb$design

# set x-levels
attr(mdb$ID,"levels")
attr(model.design(terms(t),data=d,xlev=list("ID(z)"=1:10),
     specialsFactor=TRUE)$ID,"levels")

# special specials (avoid define function SP)
f <- formula(y~x+SP(z)+factor(v))
t <- terms(f,specials="SP",data=d)
st <- strip.terms(t,specials="SP",arguments=NULL)
md2a <- model.design(st,data=d,specialsFactor=TRUE,specialsDesign="SP")
md2a$SP
md2b <- model.design(st,data=d,specialsFactor=TRUE,specialsDesign=FALSE)
md2b$SP

# special function with argument
f2 <- formula(y~x+treat(z,power=2)+treat(v,power=-1))
t2 <- terms(f2,special="treat")
st2 <- strip.terms(t2,specials="treat",arguments=list("treat"=list("power")))
model.design(st2,data=d,specialsFactor=FALSE)
model.design(st2,data=d,specialsFactor=TRUE)
model.design(st2,data=d,specialsDesign=TRUE)

library(survival)
data(pbc)
t3 <- terms(Surv(time,status!=0)~factor(edema)*age+strata(I(log(bili)>1))+strata(sex),
            specials=c("strata","cluster"))
st3 <- strip.terms(t3,specials=c("strata"),arguments=NULL)
md3 <- model.design(terms=st3,data=pbc[1:4,])
md3$strata
md3$cluster

f4 <- Surv(time,status)~age+const(factor(edema))+strata(sex,test=0)+prop(bili,power=1)+tp(albumin)
t4 <- terms(f4,specials=c("prop","timevar","strata","tp","const"))
st4 <- strip.terms(t4,
                   specials=c("prop","timevar"),
                   unspecials="prop",
                   alias.names=list("timevar"="strata","prop"=c("const","tp")),
                   arguments=list("prop"=list("power"=0),"timevar"=list("test"=0)))
formula(st4)
md4 <- model.design(st4,data=pbc[1:4,],specialsDesign=TRUE)
md4$prop
md4$timevar

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