Pattern Recognition Approach to Data Interpretation

I Philosophical Considerations and Computer Packages.- I.1. Philosophical Considerations.- Data Considerations.- Pattern Recognition Approach.- Pattern Recognition Questions.- Pattern Recognition Nomenclature.- Variable Coding.- Categorization of Data.- Considerations to Keep in Mind.- Programs to Be Discussed.- Possible Approaches.- I.2. Biomedical Computer Program (BMDP).- Program Groups.- BMDP Control Language.- I.3. Statistical Package for the Social Sciences (SPSS).- Package Structure.- SPSS Programs.- SPSS Control Language.- I.4. ARTHUR.- ARTHUR Control Language.- ARTHUR Programs.- I.5. CLUSTAN.- CLUSTAN Format.- I.6. SAS.- SAS Programming.- Procedures Available.- II Pattern Recognition Approach to Data Analysis.- II.1. Preliminary Data Examination.- Step II.1a. Computer Compatibility.- Step II.1b. Eliminating Format Errors.- Step II.1c. Data Listing.- Step II.1d. Variable Distributions.- Step II.1e. Identifying Unique Cases.- Step II.1f. Variable Distributions After Elimination.- Step II.1g. Introductory Statistics.- Standard Scores.- II.2. Data Stratification.- t-Tests.- Step II.2a. Comparison of Two Groups.- Analysis of Variance.- Step II.2b. Comparisons of All Groups Simultaneously.- Multiple Way Analysis of Variance.- Step II.2c. Variable Subgroups.- CHI-Square Test.- Other Similar Programs.- II.3. Inter Variable Relationships.- Correlation Coefficients.- Step II.3a. Calculation of Correlation Coefficients.- Correlation Results.- Step II.3b. Bivariate Plots.- Partial Correlations.- Step II.3c. Partial Correlations.- Step II.3d. Clustering of Variables.- Results of the Clustering.- Canonical Correlations.- Step II.3e. Application of Canonical Correlations.- Regression Analysis.- Step II.3f. Regression Analysis.- Stepwise Regression.- Summary.- PLS-2.- Nonparametric Statistics.- II.4. Unsupervised Learning Techniques.- Cluster Analysis.- Data Set Considered.- Step II.4a. Minimal Spanning Tree.- Drawing of the Tree.- Cluster Definition.- Minimal Spanning Tree Results.- Step II.4b. Hierarchical Clustering.- Description of the Dendrogram.- Other Hierarchical Clustering Programs.- Step II.4c. Nonlinear Mapping.- Summary.- Step II.4d. CLUSTAN.- Hierarchical Techniques in CLUSTAN.- Other Clustering Techniques.- Summary.- II.5. Supervised Learning Techniques.- Step II.5a. k-Nearest Neighbors.- Testing Supervised Results.- Step II.5b. Discriminant Analysis.- Results from Discriminant Analysis.- Other Discriminant Programs.- Comparison of Discriminant Programs.- II.6. Variable Reduction.- Tools from Previous Steps.- Step II.6a. Selection of Variables.- Principal Component and Factor Analysis.- Step II.6b. Principal Component Analysis.- Classical Factor Analysis.- Data Considerations.- Factor Choices.- Step II.6c. Classical Factor Analysis.- Factor Rotations.- Underlying Variable Factor Analysis.- II.7. Data Manipulations.- SPSS Capabilities.- BMDP and ARTHUR Alterations.- III Implementation.- III.1. Typical SPSS Runs.- Card Deck.- Data Format Statement.- Missing Data.- Statistical Procedures.- Category Definitions.- File Saving.- III.2. Typical ARTHUR Runs.- Input Card.- Task Definition Cards.- Test Data.- III.3. Typical BMDP Runs.- Card Deck.- Variable Information.- Data Grouping.- III.4. Spss Implementations.- Cancorr.- Condescriptive.- Crosstabs.- Discriminant.- Factor.- Frequencies.- Nonpar CORR.- Partial CORR.- Pearson CORR.- Regression.- Scattergram.- T-Test.- III.5. ARTHUR Implementations.- Correl.- Distance.- Hier.- Karlov.- KNN.- Multi.- NLM.- Plane.- Scale.- Select.- Tree.- Varvar.- Weight.- III.6. BMDP Programs.- BMDP1D.- BMDP2D.- BMDP3D.- BMDP4D.- BMDP5D.- BMDP6D.- BMDP1M.- BMDP2M.- BMDP4M.- BMDP6M.- BMDP7M.- BMDP1R.- BMDP2R.- BMDP4R.- BMDP6R.- BMDP3S.- IV Natural Science Applications.- Biological Applications.- Medical Applications.- Geological and Earth Science Applications.- Environmental Applications.- Physics Applications.- Chemical Applications.- Summary.- References.- Appendix I. Pattern Recognition Definitions and Reference Books.- Appendix II. The Multivariate Normal Distribution.- Appendix III. Data Base Description.- Appendix IV. Indices of BMDP, SPSS, and ARTHUR Packages.- Appendix V. Programs, Manuals, and Reference Information.- Appendix VI. Summary of Analyses and Program Cross-Reference for Chapter II.- Appendix VII. Nonparametric Statistics.- Appendix VIII. Missing Values.- Appendix IX. Standard Scores And Weightings.- Computer Program Index.