| factors {lessR} | R Documentation | 
Create Factor Variables Across a Sequential Range or Vector of Variables
Description
Creates factors for many variables. Specify a range from a given start variable and end variable.  Applies only to variables in a data frame, d by default, and outputs the entire data frame including the factor transformation.
Usage
factors(x, levels, labels=NULL, data=d, ordered=FALSE,
          new=FALSE, suffix="_f", var_labels=FALSE, ...)
Arguments
x | 
 Name of variable(s) to convert to a factor. List a single variable or a vector  | 
levels | 
 Levels for which to define the factor.  | 
labels | 
 Value labels to assign to the levels. If not present then assumes the character version of the levels.  | 
data | 
 The data frame of interest.  | 
ordered | 
 If   | 
new | 
 If   | 
suffix | 
 The appended suffix to newly created variables from 
the original variable names when   | 
var_labels | 
 Just create new variable labels for newly created factor variables, without doing a factor conversion, presumably after a previous run with factors converted to new factor variables.  | 
... | 
 Other parameter values_  | 
Details
Returns the entire data frame if applied to one or more variables in a data frame, including the new factors.
Author(s)
David W. Gerbing (Portland State University; gerbing@pdx.edu)
Examples
# get the data, variables Gender plus m01 through m20, 20 Mach IV items
# coded as integers from 0 to 5 on 6-pt Likert scales
d <- rd("Mach4", quiet=TRUE)
# single variable converted to a factor
d <- factors(Gender, 0:1, c("Male", "Female"))
# Define the labels
LikertCats <- c("Strongly Disagree", "Disagree", "Slightly Disagree",
                "Slightly Agree", "Agree", "Strongly Agree")
# Convert the integer responses to factors for the 20 Mach IV items
d <- factors(m01:m20, levels=0:5, labels=LikertCats)
# read the data again and this time also the variable labels
d <- rd("Mach4", quiet=TRUE)
l <- rd("Mach4_lbl")
# convert specified variables to factors according to the given vector
#   of three variables only
# leave the original variables unmodified, create new variables
d <- factors(c(m06, m07, m20), levels=0:5, labels=LikertCats, new=TRUE)
# now copy the variable labels from the original integer variables to the 
#   newly created factor variables
l <- factors(c(m06, m07, m20), var_labels=TRUE)