dualScale (version 0.9.1)

summary.ds: Summarizing Dual Scaling Analysis

Description

This generic function is used to produce results of several aaplications of dsFC and dsMC.

Usage

"summary"(object,...)

Arguments

object

Dual scaling object from dsMC or dsFC.

...

Arguments to be passed to methods

Value

For Ordinary Dual Scaling (dsMC)

IniDat

Initial Data

ItONa

Item options labels

N.Comp

Total number of Components

N.Item

Total number of items

N.Op

Number of options of each item

N.Ss

Total number of subjects

SubNa

Subject labels

Tot.Op

Total number of options

Inf_O

Distribution of information over components

ItemStat_O

Item statistics

Out_O

Results obtained

Rij_O

Inter item correlation

Norm.Op_O

Normed option weights

Norm.Su_O

Normed subjects scores

Proj.Op_O

Projected option weights

Proj.Su_O

Projected subjects scores

For Force Classification Dual Scaling (dsFC). (NOTE: '_B' and '_C' values also available).

IniDat

Initial data

CramerV

Cramer's coefficient V

CritItem

The criterion item for forced classification

ItONa

Item options labels

Match

Match-missmatch tables

N.Comp

Total number of components

N.Item

Total number of items

NSs

Total number of subjects

NOpt

Number of options of each item

Predict

Petcentage of correct classification

SubNa

Subject labels

Tot.Op

Total number of options

Inf_A

Distribution of information over components

ItemStat_A

Item statistics

Out_A

Results obtained by forced classification in the criterion subspace

Rij_A

Inter item correlation

Norm.Op_A

Normed option weights

Norm.Su_A

Normed subject scores

Proj.Op_A

Projected option weights

Proj.Su_A

Projected subject scores

Out_B

Results obtained by ignoring the criterion item

Out_C

Results obtained in subspace complimentary to the criterion item

Details

Available results available from different applications.

References

Nishisato S (2007). Multidimensional Nonlinear Descriptive Analysis. Chapman & Hall/CRC.

See Also

dsFC, dsMC, print.ds, plot.ds

Examples

  data(singapore)
	ole<-dsMC(singapore)
	summary(ole)
	ole$IniDa