Multiple regression and beyond:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boston ; Munich [u.a.]
Pearson/Allyn and Bacon
2006
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references (p. 511-516) and indexes. - Formerly CIP |
| Beschreibung: | XVI, 534 S. Ill., graph. Darst. 24cm |
| ISBN: | 0205326447 |
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| 300 | |a XVI, 534 S. |b Ill., graph. Darst. |c 24cm | ||
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| 500 | |a Includes bibliographical references (p. 511-516) and indexes. - Formerly CIP | ||
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Datensatz im Suchindex
| _version_ | 1804149736356184064 |
|---|---|
| adam_text | Titel: Multiple regression and beyond
Autor: Keith, Timothy
Jahr: 2006
CONTENTS
¦ ¦ ¦ ¦ ¦
Preface xiii
PARTI MULTIPLE REGRESSION
CHAPTER ONE
Introduction and Simple (Bivariate) Regression 1
SIMPLE (BIVARIATE) REGRESSION 2
Example: Homework and Math Achievement 2
REGRESSION IN PERSPECTIVE 13
Relation of Regression to Other Statistical Methods 13
Explaining Variance 15
Advantages of Multiple Regression 16
OTHER ISSUES 17
Prediction versus Explanation 17
Causality 18
REVIEW OF SOME BASICS 19
Variance and Standard Deviation 19
Correlation and Covariance 19
WORKING WITH EXTANT DATA SETS 20
SUMMARY 22
EXERCISES 23
NOTES 23
CHAPTER TWO
Multiple Regression: Introduction 25
A NEW EXAMPLE: REGRESSING GRADES ON
HOMEWORK AND PARENT EDUCATION 26
The Data 26
The Regression 26
HI
IV CONTENTS
QUESTIONS 33
Controlling for ... 33
b versus 6 34
Comparison across Samples 37
DIRECT CALCULATION OF 15 AND R2 39
SUMMARY 41
EXERCISES 41
NOTES 42
CHAPTER THREE
Multiple Regression: More Detail 43
WHY R2 *r2 + r2 43
PREDICTED SCORES AND RESIDUALS 46
Regression Line 49
LEAST SQUARES 51
REGRESSION EQUATION = CREATING A COMPOSITE? 52
ASSUMPTIONS OF REGRESSION AND REGRESSION DIAGNOSTICS 54
SUMMARY 54
EXERCISES 55
NOTE 55
CHAPTER FOUR
Three and More Independent Variables
and Related Issues 56
THREE PREDICTOR VARIABLES 56
Regression Results 58
Interpretation 60
RULES OF THUMB: MAGNITUDE OF EFFECTS 61
FOUR INDEPENDENT VARIABLES 62
Another Control Variable 62
Regression Results 63
Trouble in Paradise 64
CONTENTS
COMMON CAUSES AND INDIRECT EFFECTS 66
THE IMPORTANCE OF «2? 68
PREDICTION AND EXPLANATION 69
SUMMARY 71
EXERCISES 72
NOTES 73
CHAPTER FTVE
Three Types of Multiple Regression 74
SIMULTANEOUS MULTIPLE REGRESSION 76
The Analysis 76
Purpose 76
What to Interpret 77
Strengths and Weaknesses 78
SEQUENTIAL MULTIPLE REGRESSION 78
The Analysis 78
Comparison to Simultaneous Regression 80
Problems with R2 as a Measure of Effect 84
Other Uses of Sequential Regression 85
Interpretation 90
Summary: Sequential Regression 90
STEPWISE MULTIPLE REGRESSION 92
The Analysis 92
Danger: Stepwise Regression Is Inappropriate for Explanation 94
A Predictive Approach 95
Cross-Validation 96
Adjusted R1 97
Additional Dangers 97
Alternatives to Stepwise Regression 98
Summary: Stepwise Regression 98
THE PURPOSE OF THE RESEARCH 99
Explanation 99
Prediction 101
COMBINING METHODS 101
SUMMARY 102
EXERCISES 103
NOTES 104
VI CONTENTS
CHAPTER SIX
Analysis of Categorical Variables 105
DUMMY VARIABLES 106
Simple Categorical Variables 106
More Complex Categorical Variables 107
False Memory and Sexual Abuse 108
OTHER METHODS OF CODING CATEGORICAL VARIABLES 114
Effect Coding 114
Criterion Scaling 116
UNEQUAL GROUP SIZES 118
Family Structure and Substance Use 118
ADDITIONAL METHODS AND ISSUES 125
SUMMARY 125
EXERCISES 127
NOTES 127
CHAPTERSEVEN
Categorical and Continuous Variables 129
SEX, ACHIEVEMENT, AND SELF-ESTEEM 130
INTERACTIONS 132
Testing Interactions in MR 133
Interpretation 135
A STATISTICALLY SIGNIFICANT INTERACTION 137
Does Achievement Affect Self-Esteem? It Depends 138
Understanding an Interaction 138
Extensions and Other Examples 140
Testing Interactions in MR: Summary 141
SPECIFIC TYPES OF INTERACTIONS BETWEEN CATEGORICAL AND CONTINUOUS
VARIABLES 141
Test (and Other) Bias 142
Aptitude-Treatment Interactions 151
ANCOVA 155
CAVEATS AND ADDITIONAL INFORMATION 156
Effects of Categorical Subject Variables 156
Interactions and Cross Products 157
Further Probing of Statistically Significant Interactions 157
SUMMARY 158
CONTENTS Vll
EXERCISES 159
NOTES 160
CHAPTER EIGHT
Continuous Variables: Interactions and Curves 161
INTERACTIONS BETWEEN CONTINUOUS VARIABLES 161
Effects of TV Time on Achievement 161
MODERATION, MEDIATION, AND COMMON CAUSE 168
Moderation 168
Mediation 168
Common Cause 169
CURVILINEAR REGRESSION 170
Curvilinear Effects of Homework on GPA 171
SUMMARY 178
EXERCISES 178
NOTE 179
CHAPTER NINE
Multiple Regression: Summary, Further
Study, and Problems 180
SUMMARY 180
Standard Multiple Regression 180
Explanation and Prediction 182
Three Types of Multiple Regression 183
Categorical Variables in MR 184
Categorical and Continuous Variables, Interactions, and Curves 185
ASSUMPTIONS AND REGRESSION DIAGNOSTICS 186
Assumptions Underlying Regression 186
Regression Diagnostics 187
Diagnosing Data Problems 193
TOPICS FOR ADDITIONAL STUDY 202
Sample Size and Power 202
Related Methods 205
PROBLEMS WITH MR? 207
EXERCISES 211
NOTE 211
V1I1 CONTENTS
PART II BEYOND MULTIPLE REGRESSION 212
CHAPTER TEN
Path Modeling: Structural Equation Modeling
with Measured Variables 212
INTRODUCTION TO PATH ANALYSIS 213
A Simple Model 213
Cautions 218
Jargon and Notation 220
A MORE COMPLEX EXAMPLE 223
Steps for Conducting Path Analysis 223
Interpretation: Direct Effects 226
Indirect and Total Effects 228
SUMMARY 233
EXERCISES 235
NOTES 236
CHAPTER ELEVEN
Path Analysis: Dangers and Assumptions 238
ASSUMPTIONS 238
THE DANGER OF COMMON CAUSES 240
A Research Example 241
Common Causes, Not All Causes 243
INTERVENING (MEDIATING) VARIABLES 245
OTHER POSSIBLE DANGERS 247
Paths in the Wrong Direction 247
Unreliability and Invalidity 249
DEALING WITH DANGER 249
REVIEW: STEPS IN A PATH ANALYSIS 250
SUMMARY 251
EXERCISES 252
NOTES 253
CONTENTS IX
CHAPTER TWELVE
Analyzing Path Models Using SEM Programs 254
SEM PROGRAMS 254
Amos 255
REANALYSIS OF THE PARENT INVOLVEMENT PATH MODEL 256
Estimating the Parent Involvement Model via Amos 256
ADVANTAGES OF SEM PROGRAMS 260
Overidentified Models 260
Comparing Competing Models 270
MORE COMPLEX MODELS 274
Equivalent and Nonequivalent Models 274
Nonrecursive Models 280
Longitudinal Models 281
ADVICE: MR VERSUS SEM PROGRAMS 283
SUMMARY 284
EXERCISES 286
NOTES 288
CHAPTER THIRTEEN
Error: The Scourge of Research 289
EFFECTS OF UNRELIABILITY 290
The Importance of Reliability 290
Effects of Unreliability on Path Results 291
EFFECTS OF INVALIDITY 295
The Meaning and Importance of Validity 295
Accounting for Invalidity 296
LATENT VARIABLE SEM AND ERRORS OF MEASUREMENT 298
The Latent SEM Model 300
SUMMARY 303
EXERCISES 304
NOTES 304
CONTENTS
CHAPTER FOURTEEN
Confirmatory Factor Analysis 305
FACTOR ANALYSIS OR THE MEASUREMENT MODEL 305
AN EXAMPLE WITH THE DAS 306
Structure of the DAS 306
The Initial Model 307
Standardized Results: The Initial Model 308
Testing a Standardized Model 312
TESTING COMPETING MODELS 314
A Three-Factor, No-Memory Model 314
A Three-Factor Combined Nonverbal Model 316
HIERARCHICAL MODELS 318
Model Justification and Setup 318
Hierarchical Model Results 319
MODEL FIT AND MODEL MODIFICATION 321
Modification Indexes 322
Standardized Residuals 324
Adding Model Constraints and z Values 325
Cautions 325
ADDITIONAL USES OF CFA 325
SUMMARY 328
EXERCISES 330
CHAPTER FIFTEEN
Putting It All Together: Introduction to Latent Variable SEM 331
PUTTING THE PIECES TOGETHER 332
AN EXAMPLE: EFFECTS OF PEER REJECTION 333
Overview, Data, and Model 333
Results: The Initial Model 337
COMPETING MODELS 341
Other Possible Models 343
MODEL MODIFICATIONS 344
SUMMARY 346
EXERCISES 348
CONTENTS XI
CHAPTER SIXTEEN
Latent Variable Models: More Advanced Topics 350
SINGLE INDICATORS AND CORRELATED ERRORS 350
A Latent Variable Homework Model 350
Competing Models 360
Model Modifications 362
MULTISAMPLE MODELS 362
A Multisample Homework Model across Ethnic Groups 363
REPLICATION AND CROSS-VALIDATION 374
Using One Sample to Set Constraints in Another 374
DANGERS, REVISITED 377
Omitted Common Causes 378
Path in the Wrong Direction 380
Incomplete Knowledge 380
SUMMARY 381
EXERCISES 383
NOTES 384
CHAPTER SEVENTEEN
Summary: Path Analysis, CFA, and SEM 385
SUMMARY 385
Path Analysis 385
Error 389
Confirmatory Factor Analysis 390
Latent Variable SEM 391
ISSUES INCOMPLETELY OR NOT COVERED 394
Maximum Likelihood Estimation 394
Missing Values 394
Sample Size, Number of Parameters, and Power 395
Differences across Programs 396
Longitudinal Models 396
Causality and the Veracity of Models 396
ADDITIONAL RESOURCES 397
Introductory Texts 397
More Advanced Resources 397
Books about Specific SEM Programs 398
Reporting SEM Results 398
Cautions 398
XII CONTENTS
APPENDIX A
Data Files 400
APPENDIX B
Sample Statistical Programs and Multiple
Regression Output 433
APPENDIX C
Sample Output from SEM Programs 452
APPENDIX D
Partial and Semipartial Correlation 482
APPENDIX E
Review of Basic Statistics Concepts 491
References 511
Name Index 517
Subject Index 520
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| spelling | Keith, Timothy 1952- Verfasser (DE-588)1029420718 aut Multiple regression and beyond Timothy Z. Keith Boston ; Munich [u.a.] Pearson/Allyn and Bacon 2006 XVI, 534 S. Ill., graph. Darst. 24cm txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references (p. 511-516) and indexes. - Formerly CIP Regression analysis Multiple Regression (DE-588)4170720-5 gnd rswk-swf Multiple Regression (DE-588)4170720-5 s DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025454426&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Keith, Timothy 1952- Multiple regression and beyond Regression analysis Multiple Regression (DE-588)4170720-5 gnd |
| subject_GND | (DE-588)4170720-5 |
| title | Multiple regression and beyond |
| title_auth | Multiple regression and beyond |
| title_exact_search | Multiple regression and beyond |
| title_full | Multiple regression and beyond Timothy Z. Keith |
| title_fullStr | Multiple regression and beyond Timothy Z. Keith |
| title_full_unstemmed | Multiple regression and beyond Timothy Z. Keith |
| title_short | Multiple regression and beyond |
| title_sort | multiple regression and beyond |
| topic | Regression analysis Multiple Regression (DE-588)4170720-5 gnd |
| topic_facet | Regression analysis Multiple Regression |
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