Download IBM SPSS Categories PDF

TitleIBM SPSS Categories
TagsCategorical Variable Regression Analysis Principal Component Analysis Correlation And Dependence Level Of Measurement
File Size654.3 KB
Total Pages64
Table of Contents
                            Contents
Chapter 1. Introduction to Optimal Scaling Procedures for Categorical Data
	What Is Optimal Scaling?
	Why Use Optimal Scaling?
	Optimal Scaling Level and Measurement Level
		Selecting the Optimal Scaling Level
		Transformation Plots
		Category Codes
	Which Procedure Is Best for Your Application?
		Categorical Regression
		Categorical Principal Components Analysis
		Nonlinear Canonical Correlation Analysis
		Correspondence Analysis
		Multiple Correspondence Analysis
		Multidimensional Scaling
		Multidimensional Unfolding
	Aspect Ratio in Optimal Scaling Charts
Chapter 2. Categorical Regression (CATREG)
	Define Scale in Categorical Regression
	Categorical Regression Discretization
	Categorical Regression Missing Values
	Categorical Regression Options
	Categorical Regression Regularization
	Categorical Regression Output
	Categorical Regression Save
	Categorical Regression Transformation Plots
	CATREG Command Additional Features
Chapter 3. Categorical Principal Components Analysis (CATPCA)
	Define Scale and Weight in CATPCA
	Categorical Principal Components Analysis Discretization
	Categorical Principal Components Analysis Missing Values
	Categorical Principal Components Analysis Options
	Categorical Principal Components Analysis Output
	Categorical Principal Components Analysis Save
	Categorical Principal Components Analysis Object Plots
	Categorical Principal Components Analysis Category Plots
	Categorical Principal Components Analysis Loading Plots
	CATPCA Command Additional Features
Chapter 4. Nonlinear Canonical Correlation Analysis (OVERALS)
	Define Range and Scale
	Define Range
	Nonlinear Canonical Correlation Analysis Options
	OVERALS Command Additional Features
Chapter 5. Correspondence Analysis
	Define Row Range in Correspondence Analysis
	Define Column Range in Correspondence Analysis
	Correspondence Analysis Model
	Correspondence Analysis Statistics
	Correspondence Analysis Plots
	CORRESPONDENCE Command Additional Features
Chapter 6. Multiple Correspondence Analysis
	Define Variable Weight in Multiple Correspondence Analysis
	Multiple Correspondence Analysis Discretization
	Multiple Correspondence Analysis Missing Values
	Multiple Correspondence Analysis Options
	Multiple Correspondence Analysis Output
	Multiple Correspondence Analysis Save
	Multiple Correspondence Analysis Object Plots
	Multiple Correspondence Analysis Variable Plots
	MULTIPLE CORRESPONDENCE Command Additional Features
Chapter 7. Multidimensional Scaling (PROXSCAL)
	Proximities in Matrices across Columns
	Proximities in Columns
	Proximities in One Column
	Create Proximities from Data
	Create Measure from Data
	Define a Multidimensional Scaling Model
	Multidimensional Scaling Restrictions
	Multidimensional Scaling Options
	Multidimensional Scaling Plots, Version 1
	Multidimensional Scaling Plots, Version 2
	Multidimensional Scaling Output
	PROXSCAL Command Additional Features
Chapter 8. Multidimensional Unfolding (PREFSCAL)
	Define a Multidimensional Unfolding Model
	Multidimensional Unfolding Restrictions
	Multidimensional Unfolding Options
	Multidimensional Unfolding Plots
	Multidimensional Unfolding Output
	PREFSCAL Command Additional Features
Notices
	Trademarks
Index
	A
	B
	C
	D
	E
	F
	G
	I
	J
	L
	M
	N
	O
	P
	R
	S
	T
	V
	W
                        
Document Text Contents
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Note
Before using this information and the product it supports, read the information in “Notices” on page 53.

Product Information

This edition applies to version 22, release 0, modification 0 of IBM SPSS Statistics and to all subsequent releases and
modifications until otherwise indicated in new editions.

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