| transform.Lexis {Epi} | R Documentation |
Modify a Lexis object.
## S3 method for class 'Lexis' transform( `_data`, ...) ## S3 method for class 'Lexis' Relevel( x, states, print = TRUE, ... ) ## S3 method for class 'Lexis' levels( x ) ## S3 method for class 'Lexis' factorize( x, states, print = TRUE, ... ) ## S3 method for class 'stacked.Lexis' transform( `_data`, ...)
_data |
an object of class |
x |
an object of class |
states |
Names of the factor levels (states) for |
print |
Should a conversion between old and new levels be printed? |
... |
Additional arguments to be passed to
|
The transform method for Lexis objects works exactly as the
method for data frames, but keeps the Lexis attributes.
factorize transforms the variables
lex.Cst and lex.Xst to factors with identical set of
levels, optionally with names given in states, and optionally
collapsing states.
Relevel is merely an alias for
factorize, since the function does the same as
Relevel, but for both the factors lex.Cst and
lex.Xst. A default sideeffect is to produce a table of old
states versus new states if states is a list. Unlike
Relevel for factors, Relevel.Lexis does not accept a
matrix as a second argument - the number of levels of lex.Cst
is rarely (if ever) large.
Note that if states is an integer vector, the levels of
lex.Cst and lex.Xst are permuted. If states is a
list of numbers or strings, the levels of lex.Cst and
lex.Xst will be permuted. But if states is a character
vector it must have length nlevels(lex.Cst), and the result
will be a renaming of the levels.
If states is NULL, as when for example the argument is
not passed to the function, the returned object have levels of
lex.Cst, lex.Xst (and for stacked.Lexis objects
lex.Tr) shaved down to the actually occurring values; that is,
empty levels are discarded.
A transformed Lexis object.
The function levels returns the names of the states (levels of
the factors lex.Cst and lex.Xst.
Martyn Plummer, Bendix Carstensen
Lexis,
merge.Lexis,
subset.Lexis,
subset.stacked.Lexis,
Relevel,
transient,
absorbing
data( nickel )
nic <- Lexis( data = nickel,
id = id,
entry = list(age=agein),
exit = list(age=ageout,cal=ageout+dob,tfh=ageout-age1st),
## Lung cancer deaths are coded 2 and other deaths are coded 1
exit.status = ( (icd > 0) + (icd %in% c(162,163)) ) )
str( nic )
levels( nic )
nit <- transform( nic, cumex = exposure*(agein-age1st) )
str( nit )
## It is still a Lexis object!
summary( nic )
nix <- factorize.Lexis( nic, c("Alive","Lung","Dead"))
niw <- factorize.Lexis( nix, c("Alive","Pulm","Mort"))
niz <- factorize.Lexis( niw, states=list("Alive",c("Pulm","Mort")), coll=" \n& ")
boxes( niw, boxpos=TRUE )
par( new=TRUE )
boxes( niz, boxpos=TRUE )
siw <- stack( niw )
str( siw )