# measurement

0th

Percentile

##### Levels of Measurement of Survey Items

The measurement level of a "item" object, which is one of "nominal", "ordinal", "interval", "ratio", determines what happens to it, if it or the data.set containing it is coerced into a data.frame. If the level of measurement level is "nominal", the it will be converted into an (unordered) factor, if the level of measurement is "ordinal", the item will be converted into an ordered vector. If the measurement is "interval" or "ratio", the item will be converted into a numerical vector.

Keywords
manip
##### Usage
# S4 method for item
measurement(x)
# S4 method for item
measurement(x) <- value
# S4 method for data.set
measurement(x)
# S4 method for data.set
measurement(x) <- value
is.nominal(x)
is.ordinal(x)
is.interval(x)
is.ratio(x)
set_measurement(x,…)
##### Arguments
x

an object, usually of class "item".

value

for the item method, a character string; either "nominal", "ordinal", "interval", or "ratio"; for the data.set method, a list of character vectors with variable names, where the names of the list corresponds to a measurement level and and the list elements indicates the variables to which the measurement levels are assigned.

vectors of variable names, either symbols or character strings, tagged with the intended measurement level.

##### Value

The item method of measurement(x) returns a character string, the data.set method returns a named character vector, where the name of each element is a variable name and each

is.nominal, is.ordinal, is.interval, is.ratio return a logical value.

##### References

Stevens, Stanley S. 1946. "On the theory of scales of measurement." Science 103: 677-680.

data.set, item

##### Aliases
• measurement
• measurement,ANY-method
• measurement,item-method
• measurement,data.set-method
• measurement<-
• measurement<-,item-method
• measurement<-,data.set-method
• set_measurement
• is.nominal
• is.ordinal
• is.interval
• is.ratio
##### Examples
# NOT RUN {
vote <- sample(c(1,2,3,8,9),size=30,replace=TRUE)
labels(vote) <- c(Conservatives         =  1,
Labour                =  2,
"Liberal Democrats"   =  3,
"Don't know"          =  8,
)
missing.values(vote) <- c(8,9)
as.data.frame(vote)[[1]]
measurement(vote) <- "interval"
as.data.frame(vote)[[1]]
group <- sample(c(1,2),size=30,replace=TRUE)
labels(group) <- c(A=1,B=2)
DataS <- data.set(group,vote)
measurement(DataS)
measurement(DataS) <- list(interval=c("group","vote"))