optiscale-package

Optimal Scaling of a Data Vector

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. package

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)