annotations: Adding Annotations to Objects

In memisc: Tools for Management of Survey Data and the Presentation of Analysis Results

Description

Annotations, that is, objects of class "annotation", are character vectors with all their elements named. Only one method is defined for this subclass of character vectors, a method for show, that shows the annotation in a nicely formatted way. Annotations of an object can be obtained via the function annotation(x) and can be set via annotation(x)<-value.

Elements of an annotation with names "description" and "wording" have a special meaning. The first kind can be obtained and set via description(x) and description(x)<-value, the second kind can be obtained via wording(x) and wording(x)<-value. "description" elements are used in way the "variable labels" are used in SPSS and Stata. "wording" elements of annotation objects are meant to contain the question wording of a questionnaire item represented by an "item" objects. These elements of annotations are treated in a special way in the output of the coodbook function.

Usage

annotation(x)
## S4 method for signature 'ANY'
annotation(x)
## S4 method for signature 'item'
annotation(x)
## S4 method for signature 'data.set'
annotation(x)
annotation(x)<-value
## S4 replacement method for signature 'ANY,character'
annotation(x)<-value
## S4 replacement method for signature 'item,annotation'
annotation(x)<-value
## S4 replacement method for signature 'vector,annotation'
annotation(x)<-value

description(x)
description(x)<-value

wording(x)
wording(x)<-value

## S4 method for signature 'data.set'
description(x)
## S4 method for signature 'importer'
description(x)

Arguments

x	an object
value	a character or annotation object

Value

annotation(x) returns an object of class "annotation", which is a named character. description(x) and wording(x) each usually return a character string. If description(x) is applied to a data.set or an importer object, however, a character vector is returned, which is named after the variables in the data set or the external file.

Examples

vote <- sample(c(1,2,3,8,9,97,99),size=30,replace=TRUE)
labels(vote) <- c(Conservatives         =  1,
                    Labour                =  2,
                    "Liberal Democrats"   =  3,
                    "Don't know"          =  8,
                    "Answer refused"      =  9,
                    "Not applicable"      = 97,
                    "Not asked in survey" = 99
                    )
missing.values(vote) <- c(97,99)
description(vote) <- "Vote intention"
wording(vote) <- "If a general election would take place next tuesday,
                    the candidate of which party would you vote for?"
annotation(vote)
annotation(vote)["Remark"] <- "This is not a real questionnaire item, of course ..."
codebook(vote)

Example output

Loading required package: lattice
Loading required package: MASS

Attaching package: 'memisc'

The following objects are masked from 'package:stats':

    contr.sum, contr.treatment, contrasts

The following object is masked from 'package:base':

    as.array

description:
     Vote intention

wording:
     If a general election would take place next tuesday, the candidate of
     which party would you vote for?

================================================================================

   vote 'Vote intention'

   "If a general election would take place next tuesday, the candidate of which
   party would you vote for?"

--------------------------------------------------------------------------------

   Storage mode: double
   Measurement: nominal
   Missing values: 97, 99

            Values and labels    N    Percent 
                                              
    1   'Conservatives'          4   22.2 13.3
    2   'Labour'                 4   22.2 13.3
    3   'Liberal Democrats'      3   16.7 10.0
    8   'Don't know'             2   11.1  6.7
    9   'Answer refused'         5   27.8 16.7
   97 M 'Not applicable'         6        20.0
   99 M 'Not asked in survey'    6        20.0

   Remark:

       This is not a real questionnaire item, of course ...

memisc documentation built on May 2, 2019, 5:45 p.m.