Item Details

Statistical Data Analysis Using Your Personal Computer

Ira H. Bernstein, Nancy A. Rowe
Format
Book
Published
Thousand Oaks [Calif.] : Sage Publications, c2001.
Language
English
ISBN
0761917802, 0761917810 (pbk.)
Contents
  • What Is Needed for Effective Behavioral Science Research 4
  • Structure of This Book 13
  • 2. Hardware and Software Needs 15
  • General Goals of Statistical Analysis 16
  • Computer Hardware 19
  • General-Purpose Software 24
  • Statistical Programs 33
  • Basic Appearance of SAS and SPSS 36
  • 3. Univariate Computer Simulations 57
  • Uniform Random Number Generation 58
  • Distributions Derived From Uniform Random Number Generation 76
  • 4. Basic Correlational Simulations 95
  • Simulating a Correlation Within Sampling Error 95
  • Correlation Matrices 120
  • Profiles 130
  • 5. Multivariate Correlational Simulations 137
  • Multiple Regression 137
  • Analysis of Variance and Analysis of Covariance 140
  • Creating Within, Between, and Total Correlation Matrices 160
  • Canonical Correlation 177
  • 6. Simulations With Categorical Data 185
  • Logistic Functions 185
  • Psychometric Functions, Item Operating Characteristics (Trace Lines), and Dose-Response Curves 188
  • Thurstone's "Law" of Comparative Judgment and Signal Detection Theory 213
  • Constructing a Similarity Matrix 216
  • Classification and Signal Detection Analysis 217
  • 7. Exploratory Factor Analysis 231
  • A Unifactor Structure 232
  • Multifactor Structures Using Data With Independent Clusters 246
  • Multifactor Structures Using Data With Related Clusters 253
  • Calculating Factor Scores 258
  • Exploratory Maximum Likelihood Factor Analysis 262
  • 8. Confirmatory Factor Analysis and Related Procedures 269
  • Confirmatory Factor Analysis 269
  • Multidimensional Scaling 286
  • 9. Regression, Canonical Correlation, and Covariance Structure Analysis 295
  • Ordinary Linear Regression 296
  • Analysis of Variance 326
  • Analysis of Covariance 338
  • Canonical Correlation Analysis 340
  • Covariance Structure Analysis 348
  • 10. Discriminant Analysis, Classification, and Multivariate Analysis of Variance 359
  • Discriminant Analysis 359
  • Classification Analysis 373
  • Multivariate Analysis of Variance 376
  • 11. Analysis of Categorical Data 383
  • Categorical Models 383
  • Factor Analysis of Categorical Data 408
  • Item Response Theory Applications 413
  • Appendix Eigenanalysis of a Gramian Matrix 423
  • Principles Underlying Eigenanalysis 423.
Description
ix, 446 p. : ill. ; 23 cm.
Notes
Includes bibliographical references (p. 433-436) and indexes.
Technical Details
  • Access in Virgo Classic

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    t| What Is Needed for Effective Behavioral Science Research g| 4 -- t| Structure of This Book g| 13 -- g| 2. t| Hardware and Software Needs g| 15 -- t| General Goals of Statistical Analysis g| 16 -- t| Computer Hardware g| 19 -- t| General-Purpose Software g| 24 -- t| Statistical Programs g| 33 -- t| Basic Appearance of SAS and SPSS g| 36 -- g| 3. t| Univariate Computer Simulations g| 57 -- t| Uniform Random Number Generation g| 58 -- t| Distributions Derived From Uniform Random Number Generation g| 76 -- g| 4. t| Basic Correlational Simulations g| 95 -- t| Simulating a Correlation Within Sampling Error g| 95 -- t| Correlation Matrices g| 120 -- t| Profiles g| 130 -- g| 5. t| Multivariate Correlational Simulations g| 137 -- t| Multiple Regression g| 137 -- t| Analysis of Variance and Analysis of Covariance g| 140 -- t| Creating Within, Between, and Total Correlation Matrices g| 160 -- t| Canonical Correlation g| 177 -- g| 6. t| Simulations With Categorical Data g| 185 -- t| Logistic Functions g| 185 -- t| Psychometric Functions, Item Operating Characteristics (Trace Lines), and Dose-Response Curves g| 188 -- t| Thurstone's "Law" of Comparative Judgment and Signal Detection Theory g| 213 -- t| Constructing a Similarity Matrix g| 216 -- t| Classification and Signal Detection Analysis g| 217 -- g| 7. t| Exploratory Factor Analysis g| 231 -- t| A Unifactor Structure g| 232 -- t| Multifactor Structures Using Data With Independent Clusters g| 246 -- t| Multifactor Structures Using Data With Related Clusters g| 253 -- t| Calculating Factor Scores g| 258 -- t| Exploratory Maximum Likelihood Factor Analysis g| 262 -- g| 8. t| Confirmatory Factor Analysis and Related Procedures g| 269 -- t| Confirmatory Factor Analysis g| 269 -- t| Multidimensional Scaling g| 286 -- g| 9. t| Regression, Canonical Correlation, and Covariance Structure Analysis g| 295 -- t| Ordinary Linear Regression g| 296 -- t| Analysis of Variance g| 326 -- t| Analysis of Covariance g| 338 -- t| Canonical Correlation Analysis g| 340 -- t| Covariance Structure Analysis g| 348 -- g| 10. t| Discriminant Analysis, Classification, and Multivariate Analysis of Variance g| 359 -- t| Discriminant Analysis g| 359 -- t| Classification Analysis g| 373 -- t| Multivariate Analysis of Variance g| 376 -- g| 11. t| Analysis of Categorical Data g| 383 -- t| Categorical Models g| 383 -- t| Factor Analysis of Categorical Data g| 408 -- t| Item Response Theory Applications g| 413 -- g| Appendix t| Eigenanalysis of a Gramian Matrix g| 423 -- t| Principles Underlying Eigenanalysis g| 423.
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    a| Statistics x| Data processing.
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