Cluster Analysis: 2014 Edition (Statistical Associates Blue Book Series 24)
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Cluster Analysis: 2014 Edition (Statistical Associates Blue Book Series 24)
CLUSTER ANALYSIS Overview
An illustrated tutorial and introduction to cluster analysis using SPSS, SAS, SAS Enterprise Miner, and Stata for examples. Suitable for introductory graduate-level study.
The 2014 edition is a major update to the 2012 edition. Among the new features are these:
Was 89 pages, now book length (207 pages total) Had 58 figures, now has over 170 illustrations Now covers Stata as well as SPSS and SAS Totally revised sections on hierarchical, k-means, and two-step clustering New coverage of nearest neighbor analysis New coverage of oblique principal components cluster analysis New coverage of nonparametric density cluster analysis New coverage of Kohonen self-organizing map (SOM) clustering Links to all datasets used in the text.
Below is the unformatted partial table of contents.
Table of Contents CLUSTER ANALYSIS 1 Overview10 Data examples in this volume10 Key Concepts and Terms12 Terminology12 Distances (proximities)12 Cluster formation12 Cluster validity12 Types of cluster analysis14 Types of cluster analysis by software package14 Disjoint clustering15 Hierarchical clustering15 Overlapping clustering16 Fuzzy clustering16 Hierarchical cluster analysis in SPSS16 SPSS Input for hierarchical clustering16 Example16 The main "Hierarchical Cluster Analysis" dialog17 Statistics button18 Plots button19 Methods button20 SPSS output for hierarchical cluster analysis21 Proximity table21 Cluster membership table22 Agglomeration Schedule22 Dendogram24 Icicle plots27 Summary measures28 Hierarchical cluster analysis in SAS29 SAS input for hierarchical cluster analysis29 Example29 Data setup29 SAS syntax30 SAS output for hierarchical cluster analysis31 Simple statistics table31 Eigenvalues of the covariance matrix table31 Root mean square coefficients32 Cluster history table33 Dendogram34 Icicle Plots36 Cluster membership table36 Saving data to file37 Hierarchical cluster analysis in Stata38 Stata input for hierarchical cluster analysis38 Stata output for hierarchical cluster analysis40 Agglomeration coefficients40 Dendogram41 Saving cluster membership values42 Cluster membership table43 K-means cluster analysis44 Overview44 Example45 K-means cluster analysis in SPSS45 SPSS input45 Main K-means dialog45 The Iterate button47 The Save button48 The Options button49 SPSS Output for K-Means cluster analysis50 The Anova table50 Number of cases in each cluster51 Getting different clusters52 Cluster membership table52 K-Means cluster analysis in SAS53 Overview53 Example54 SAS input for k-means cluster analysis54 SAS output for k-means cluster analysis55 The "Statistics for Variables" table55 Criteria for determining k57 The "Cluster Summary" table60 Cluster membership and distance values61 Crosstabulation tables61 Cluster separation plots62 K-Means cluster analysis in Stata64 Example64 Stata input for k-means cluster analysis64 The main kmeans clustering command64 Obtaining descriptive statistics65 Obtaining distance information65 Obtaining cluster separation plots65 Comparing kmeans and kmedian solutions66 Stata output for k-means cluster analysis66 Cluster membership assignments66 Descriptive statistics67 Distance coefficients69 Cluster separation plots70 Comparing kmeans and kmedians solutions71 Two-step cluster analysis in SPSS72 Overview72 Cluster feature tree (CF tree)73 Proximity73 Example74 SPSS input for two-step clustering74 The main two-step clustering dialog74 Options button dialog75 Output button dialog78 SPSS output for two-step clustering79 Autoclustering table79 Cluster distribution table81 Centroids (cluster profiles) table81 Model summary82 The "Cluster Quality" graph82 The "Cluster Sizes" pie chart82 The "Predictor Importance" chart83