optiscale-package {optiscale} | R Documentation |
Optimal Scaling of a Data Vector
Description
This package provides tools to perform an optimal scaling analysis on a data vector. The main result of the optimal scaling is a vector of scores which are a least-squares approximation to a vector of quantitative values, subject to measurement constraints based upon a vector of qualitative data values. See Young (1981) for details.
Details
Package: | optiscale |
Type: | Package |
Version: | 1.2.2 |
Date: | 2021-02-02 |
License: | GPL-2 |
LazyLoad: | yes |
The function that performs the optimal scaling is opscale()
.
It produces an object of class "opscale".
Generic methods are defined for print
, summary
, and
plot
(graphing optimally-scaled values versus
original data values).
Author(s)
William G. Jacoby
Maintainer: William G. Jacoby <wm.g.jacoby@gmail.com>
References
Young, Forrest W. (1981) “Quantitative Analysis of Qualitative Data.” Psychometrika 46: 357-388.
See Also
opscale,plot.opscale, print.opscale,
summary.opscale
Examples
### x1 is vector of qualitative data
### x2 is vector of quantitative values
x1 <- c(1,1,1,1,2,2,2,3,3,3,3,3,3)
x2 <- c(3,2,2,2,1,2,3,4,5,2,6,6,4)
### Optimal scaling, specifying that x1
### is ordinal-discrete
op.scaled <- opscale(x.qual=x1, x.quant=x2,
level=2, process=1)
print(op.scaled)
summary(op.scaled)