Sorting Data

Collection and Analysis

A. P. M. Coxon

• Publisher: SAGE Publications, Inc
• Year: 1999
• Print ISBN: 9780803972377
• eBook ISBN: 9781452215273
• Edition: 1
• Topic: Social Sciences
• Subtopic: Social Science Research & Methodology
• Index: Social Sciences

The method of sorting is a flexible, easily-used (and enjoyable) technique well suited to exploring and mapping conceptual domains, to the study of subjective or folk-classifications, and to comparing existing classifications one with another. Originating in linguistics and psychology, sorting methods (also known as "own categories", and "pile-sorting") have diffused to a wide range of other social sciences.

This book provides the first systematic introduction to the method of sorting and draws material from new and widely-scattered sources. It covers the collection and analysis of data, using free-sorting as the main focus, but includes other variants. Methods are provided for describing and comparing sortings, drawing on recent developments in partition theory and combinational analysis and for measuring their similarity. Appropriate methods are presented for the representation of both individual sortings and of the objects themselves: multidimensional scaling, correspondence analysis, and clustering techniques. Applications and available software are covered.

Table of contents

• Cover
• Contents
• Series Editor's Introduction
• Chapter 1 - Introduction
• 1.1. Measurement, Data, and Sorting
• 1.2. Examples of Sorting
• Chapter 2 - Collecting Free-Sorting Data
• 2.1. Specifying the Domain
• 2.1.1. Methods for Eliciting Contents of Domains
• 2.1.2. Operational Feasibility: How Many Objects?
• 2.2. The Criterion
• 2.3. The Pretest
• 2.4. Instructions and Administration of the Task
• 2.5. Data-Recording
• 2.6. Variants of Free-Sorting
• 2.6.1. Variations Based on Objects
• 2.6.2. Variations Based on the Categories
• 2.7. Three Special Cases of Sorting: Q Methodology, Multiple Sorts, and Hierarchies
• 2.7.1. Q Methodology
• 2.7.2. Multiple Sorts
• 2.7.3. Hierarchy Construction
• 2.8. An Example
• Chapter 3 - Describing and Comparing Sortings
• 3.1. Properties of Single Sortings
• 3.1.1. The Height Measure
• 3.2. Comparing Individuals' Sortings (Pairwise)
• 3.2.1. The Intersection Matrix
• 3.2.2. Pairwise Proximity Measures Between Subjects' Sortings
• 3.2.2.1. Pairbonds Dissimilarity Measure
• 3.2.2.2. Rand Index
• 3.2.2.3. "APPROX": Dissimilarity Measure
• 3.3. Comparing Objects (Co-Occurrence)
• 3.3.1. Taking Account of Differential Category Size: Burton's Measures
• 3.3.2. Dissociation Between Categories: Rosenberg's Measure
• 3.3.3. Multiple Co-Occurrences
• 3.4. An Example
• Chapter 4 - Analyzing Sorting Data
• 4.1. Representing Sortings
• 4.1.1. Observations and Data
• 4.1.2. Models
• 4.1.2.1. Spatial Models
• 4.1.2.2. Discrete Models
• 4.1.2.3. Clustering
• 4.1.2.4. Discrete Representations: Trees
• 4.1.3. Transformations
• 4.2. Two-Way Analysis
• 4.2.1. Two-Way, One-Mode Data: Comparing the Objects
• 4.2.2. Two-Way, One-Mode Data: Comparing Individuals' Sortings
• 4.2.3. Two-Way, Two-Mode Data: Objects and Categories
• 4.2.3.1. Takane's MDSORT Model
• 4.2.3.2. Homogeneity Analysis
• 4.2.3.3. Multidimensional Scalogram Analysis
• 4.3. Three-Way Analysis of Sortings
• 4.3.1. Three-Way, Two-Mode Data: Takane's IDSORT Model
• 4.3.2. Other Models
• 4.3.2.1. Symmetrical INDSCAL
• 4.3.2.2. Procrustean Analysis
• 4.3.2.3. Three-Way Additive Clustering
• 4.4. Applications
• 4.5. Summary
• About the Author
• Acknowledgments