ABSTRACT

Quantification of categorical, or non-numerical, data is a problem that scientists face across a wide range of disciplines. Exploring data analysis in various areas of research, such as the social sciences and biology, Multidimensional Nonlinear Descriptive Analysis presents methods for analyzing categorical data that are not necessarily sam

chapter 1|4 pages

PART I: Background

chapter 1|20 pages

Motivation

chapter 3|18 pages

Historical Overview

chapter 4|16 pages

Conceptual Preliminaries

chapter 5|16 pages

Technical Preliminaries

chapter 2|4 pages

PART II: Analysis of Incidence Data

chapter 6|14 pages

Contingency Tables

chapter 7|26 pages

Multiple-Choice Data

chapter 8|10 pages

Sorting Data

chapter 9|22 pages

Forced Classification of Incidence Data

chapter 3|4 pages

PART III: Analysis of Dominance Data

chapter 10|18 pages

Paired Comparison Data

chapter 11|18 pages

Rank-Order Data

chapter 12|12 pages

Successive Categories Data

chapter 4|4 pages

PART IV: Beyond the Basics

chapter 13|14 pages

Further Topics of Interest

chapter 14|30 pages

Further Perspectives