Value Filters
Value filters, that is objects that inherit from class "value.filter", are a mechanism to distinguish between valid codes of a survey item and codes that are considered to be missing, such as the codes for answers like "don't know" or "answer refused".
Value filters are optional slot values of "item" objects.
They determine which codes of "item" objects are
replaced by NA when they are coerced into
a vector or a factor.
There are three (sub)classes of value filters:
"missing.values", which specify individual
missing values and/or a range of missing values;
"valid.values", which specify individual
valid values (that is, all other values of the
item are considered as missing);
"valid.range", which specify a range of
valid values (that is, all values outside the range
are considered as missing).
Value filters of class "missing.values" correspond
to missing-values declarations in SPSS files,
imported by spss.fixed.file,
spss.portable.file, or
spss.system.file.
Value filters also can be updated using the +
and - operators.
value.filter(x) missing.values(x) missing.values(x)<-value valid.values(x) valid.values(x)<-value valid.range(x) valid.range(x)<-value is.valid(x) nvalid(x) is.missing(x) include.missings(x,mark="*")
x,value |
objects of the appropriate class. |
mark |
a character string, used to pasted
to value labels of |
value.filter(x), missing.values(x), valid.values(x), and valid.range(x),
return the value filter associated with x, an
object of class "value.filter", that is, of class
"missing.values", "valid.values", or "valid.range", respectively.
is.missing(x) returns a logical vector indicating for
each element of x whether it is a missing value or not.
is.valid(x) returns a logical vector indicating for
each element of x whether it is a valid value or not.
nvalid(x) returns the number of elements of x
that are valid.
For convenience, is.missing(x) and is.valid(x) also work
for atomic vectors and factors, where they are equivalent to
is.na(x) and !is.na(x). For atomic vectors and factors,
nvalid(x) returns the number of elements of x for
which !is.na(x) is TRUE.
include.missings(x,...) returns a copy of x
that has all values declared as valid.
x <- rep(c(1:4,8,9),2,length=60)
labels(x) <- c(
a=1,
b=2,
c=3,
d=4,
dk=8,
refused=9
)
missing.values(x) <- 9
missing.values(x)
missing.values(x) <- missing.values(x) + 8
missing.values(x)
missing.values(x) <- NULL
missing.values(x)
missing.values(x) <- list(range=c(8,Inf))
missing.values(x)
valid.values(x)
print(x)
is.missing(x)
is.valid(x)
as.factor(x)
as.factor(include.missings(x))
as.integer(x)
as.integer(include.missings(x))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.