Donald J. Treiman, PhD, is Distinguished Professor, Department of Sociology, University of California, Los Angeles. He was also, until recently, director of the California Center for Population Research.

• Tables, Figures, Exhibits, and Boxes xiPreface xxiiiThe Author xxviiIntroduction xxix1 CROSS-TABULATIONS 1What This Chapter Is About 1Introduction to the Book via a Concrete Example 2Cross-Tabulations 8What This Chapter Has Shown 192 MORE ON TABLES 21What This Chapter Is About 21The Logic of Elaboration 22Suppressor Variables 25Additive and Interaction Effects 26Direct Standardization 28A Final Note on Statistical Controls Versus Experiments 43What This Chapter Has Shown 453 STILL MORE ON TABLES 47What This Chapter Is About 47Reorganizing Tables to Extract New Information 48When to Percentage a Table "Backwards" 50Cross-Tabulations in Which the Dependent Variable Is Represented by a Mean 52Index of Dissimilarity 58Writing About Cross-Tabulations 61What This Chapter Has Shown 634 ON THE MANIPULATION OF DATA BY COMPUTER 65What This Chapter Is About 65Introduction 66How Data Files Are Organized 67Transforming Data 72What This Chapter Has Shown 80Appendix 4.A Doing Analysis Using Stata 80Tips on Doing Analysis Using Stata 80Some Particularly Useful Stata 10.0 Commands 845 INTRODUCTION TO CORRELATION AND REGRESSION (ORDINARY LEAST SQUARES) 87What This Chapter Is About 87Introduction 88Quantifying the Size of a Relationship: Regression Analysis 89Assessing the Strength of a Relationship: Correlation Analysis 91The Relationship Between Correlation and Regression Coeffi cients 94Factors Affecting the Size of Correlation (and Regression) Coeffi cients 94Correlation Ratios 99What This Chapter Has Shown 1026 INTRODUCTION TO MULTIPLE CORRELATION AND REGRESSION (ORDINARY LEAST SQUARES) 103What This Chapter Is About 103Introduction 104A Worked Example: The Determinants of Literacy in China 113Dummy Variables 120A Strategy for Comparisons Across Groups 124A Bayesian Alternative for Comparing Models 133Independent Validation 135What This Chapter Has Shown 1367 MULTIPLE REGRESSION TRICKS: TECHNIQUES FOR HANDLING SPECIAL ANALYTIC PROBLEMS 139What This Chapter Is About 139Nonlinear Transformations 140Testing the Equality of Coeffi cients 147Trend Analysis: Testing the Assumption of Linearity 149Linear Splines 152Expressing Coeffi cients as Deviations from the Grand Mean (Multiple Classifi cation Analysis) 164Other Ways of Representing Dummy Variables 166Decomposing the Difference Between Two Means 172What This Chapter Has Shown 1798 MULTIPLE IMPUTATION OF MISSING DATA 181What This Chapter Is About 181Introduction 182A Worked Example: The Effect of Cultural Capital on Educational Attainment in Russia 187What This Chapter Has Shown 1949 SAMPLE DESIGN AND SURVEY ESTIMATION 195What This Chapter Is About 195Survey Samples 196Conclusion 223What This Chapter Has Shown 22410 REGRESSION DIAGNOSTICS 225What This Chapter Is About 225Introduction 226A Worked Example: Societal Differences in Status Attainment 229Robust Regression 237Bootstrapping and Standard Errors 238What This Chapter Has Shown 24011 SCALE CONSTRUCTION 241What This Chapter Is About 241Introduction 242Validity 242Reliability 243Scale Construction 246Errors-in-Variables Regression 258What This Chapter Has Shown 26112 LOG-LINEAR ANALYSIS 263What This Chapter Is About 263Introduction 264Choosing a Preferred Model 265Parsimonious Models 277A Bibliographic Note 294What This Chapter Has Shown 295Appendix 12.A Derivation of the Effect Parameters 295Appendix 12.B Introduction to Maximum Likelihood Estimation 297Mean of a Normal Distribution 298Log-Linear Parameters 29913 BINOMIAL LOGISTIC REGRESSION 301What This Chapter Is About 301Introduction 302Relation to Log-Linear Analysis 303A Worked Logistic Regression Example:Predicting Prevalence of Armed Threats 304A Second Worked Example: Schooling Progression Ratios in Japan 314A Third Worked Example (Discrete-Time Hazard-Rate Models): Age at First Marriage 318A Fourth Worked Example (Case-Control Models):Who Was Appointed to a Nomenklatura Position in Russia? 327What This Chapter Has Shown 329Appendix 13.A Some Algebra for Logs and Exponents 330Appendix 13.B Introduction to Probit Analysis 33014 MULTINOMIAL AND ORDINAL LOGISTIC REGRESSION AND TOBIT REGRESSION 335What This Chapter Is About 335Multinomial Logit Analysis 336Ordinal Logistic Regression 342Tobit Regression (and Allied Procedures) for Censored Dependent Variables 353Other Models for the Analysis of Limited Dependent Variables 360What This Chapter Has Shown 36115 IMPROVING CAUSAL INFERENCE: FIXED EFFECTS AND RANDOM EFFECTS MODELING 363What This Chapter Is About 363Introduction 364Fixed Effects Models for Continuous Variables 365Random Effects Models for Continuous Variables 371A Worked Example: The Determinants of Income in China 372Fixed Effects Models for Binary Outcomes 375A Bibliographic Note 380What This Chapter Has Shown 38016 FINAL THOUGHTS AND FUTURE DIRECTIONS: RESEARCH DESIGN AND INTERPRETATION ISSUES 381What this Chapter is About 381Research Design Issues 382The Importance of Probability Sampling 397A Final Note: Good Professional Practice 400What This Chapter Has Shown 405Appendix A: Data Descriptions and Download Locations for the Data Used in This Book 407Appendix B: Survey Estimation with the General Social Survey 411References 417Index 431

Donald J. Treiman, PhD, is Distinguished Professor, Department of Sociology, University of California, Los Angeles. He was also, until recently, director of the California Center for Population Research.

• Tables, Figures, Exhibits, and Boxes xiPreface xxiiiThe Author xxviiIntroduction xxix1 CROSS-TABULATIONS 1What This Chapter Is About 1Introduction to the Book via a Concrete Example 2Cross-Tabulations 8What This Chapter Has Shown 192 MORE ON TABLES 21What This Chapter Is About 21The Logic of Elaboration 22Suppressor Variables 25Additive and Interaction Effects 26Direct Standardization 28A Final Note on Statistical Controls Versus Experiments 43What This Chapter Has Shown 453 STILL MORE ON TABLES 47What This Chapter Is About 47Reorganizing Tables to Extract New Information 48When to Percentage a Table "Backwards" 50Cross-Tabulations in Which the Dependent Variable Is Represented by a Mean 52Index of Dissimilarity 58Writing About Cross-Tabulations 61What This Chapter Has Shown 634 ON THE MANIPULATION OF DATA BY COMPUTER 65What This Chapter Is About 65Introduction 66How Data Files Are Organized 67Transforming Data 72What This Chapter Has Shown 80Appendix 4.A Doing Analysis Using Stata 80Tips on Doing Analysis Using Stata 80Some Particularly Useful Stata 10.0 Commands 845 INTRODUCTION TO CORRELATION AND REGRESSION (ORDINARY LEAST SQUARES) 87What This Chapter Is About 87Introduction 88Quantifying the Size of a Relationship: Regression Analysis 89Assessing the Strength of a Relationship: Correlation Analysis 91The Relationship Between Correlation and Regression Coeffi cients 94Factors Affecting the Size of Correlation (and Regression) Coeffi cients 94Correlation Ratios 99What This Chapter Has Shown 1026 INTRODUCTION TO MULTIPLE CORRELATION AND REGRESSION (ORDINARY LEAST SQUARES) 103What This Chapter Is About 103Introduction 104A Worked Example: The Determinants of Literacy in China 113Dummy Variables 120A Strategy for Comparisons Across Groups 124A Bayesian Alternative for Comparing Models 133Independent Validation 135What This Chapter Has Shown 1367 MULTIPLE REGRESSION TRICKS: TECHNIQUES FOR HANDLING SPECIAL ANALYTIC PROBLEMS 139What This Chapter Is About 139Nonlinear Transformations 140Testing the Equality of Coeffi cients 147Trend Analysis: Testing the Assumption of Linearity 149Linear Splines 152Expressing Coeffi cients as Deviations from the Grand Mean (Multiple Classifi cation Analysis) 164Other Ways of Representing Dummy Variables 166Decomposing the Difference Between Two Means 172What This Chapter Has Shown 1798 MULTIPLE IMPUTATION OF MISSING DATA 181What This Chapter Is About 181Introduction 182A Worked Example: The Effect of Cultural Capital on Educational Attainment in Russia 187What This Chapter Has Shown 1949 SAMPLE DESIGN AND SURVEY ESTIMATION 195What This Chapter Is About 195Survey Samples 196Conclusion 223What This Chapter Has Shown 22410 REGRESSION DIAGNOSTICS 225What This Chapter Is About 225Introduction 226A Worked Example: Societal Differences in Status Attainment 229Robust Regression 237Bootstrapping and Standard Errors 238What This Chapter Has Shown 24011 SCALE CONSTRUCTION 241What This Chapter Is About 241Introduction 242Validity 242Reliability 243Scale Construction 246Errors-in-Variables Regression 258What This Chapter Has Shown 26112 LOG-LINEAR ANALYSIS 263What This Chapter Is About 263Introduction 264Choosing a Preferred Model 265Parsimonious Models 277A Bibliographic Note 294What This Chapter Has Shown 295Appendix 12.A Derivation of the Effect Parameters 295Appendix 12.B Introduction to Maximum Likelihood Estimation 297Mean of a Normal Distribution 298Log-Linear Parameters 29913 BINOMIAL LOGISTIC REGRESSION 301What This Chapter Is About 301Introduction 302Relation to Log-Linear Analysis 303A Worked Logistic Regression Example:Predicting Prevalence of Armed Threats 304A Second Worked Example: Schooling Progression Ratios in Japan 314A Third Worked Example (Discrete-Time Hazard-Rate Models): Age at First Marriage 318A Fourth Worked Example (Case-Control Models):Who Was Appointed to a Nomenklatura Position in Russia? 327What This Chapter Has Shown 329Appendix 13.A Some Algebra for Logs and Exponents 330Appendix 13.B Introduction to Probit Analysis 33014 MULTINOMIAL AND ORDINAL LOGISTIC REGRESSION AND TOBIT REGRESSION 335What This Chapter Is About 335Multinomial Logit Analysis 336Ordinal Logistic Regression 342Tobit Regression (and Allied Procedures) for Censored Dependent Variables 353Other Models for the Analysis of Limited Dependent Variables 360What This Chapter Has Shown 36115 IMPROVING CAUSAL INFERENCE: FIXED EFFECTS AND RANDOM EFFECTS MODELING 363What This Chapter Is About 363Introduction 364Fixed Effects Models for Continuous Variables 365Random Effects Models for Continuous Variables 371A Worked Example: The Determinants of Income in China 372Fixed Effects Models for Binary Outcomes 375A Bibliographic Note 380What This Chapter Has Shown 38016 FINAL THOUGHTS AND FUTURE DIRECTIONS: RESEARCH DESIGN AND INTERPRETATION ISSUES 381What this Chapter is About 381Research Design Issues 382The Importance of Probability Sampling 397A Final Note: Good Professional Practice 400What This Chapter Has Shown 405Appendix A: Data Descriptions and Download Locations for the Data Used in This Book 407Appendix B: Survey Estimation with the General Social Survey 411References 417Index 431

Donald J. Treiman, PhD, is Distinguished Professor, Department of Sociology, University of California, Los Angeles. He was also, until recently, director of the California Center for Population Research.

• Tables, Figures, Exhibits, and Boxes xiPreface xxiiiThe Author xxviiIntroduction xxix1 CROSS-TABULATIONS 1What This Chapter Is About 1Introduction to the Book via a Concrete Example 2Cross-Tabulations 8What This Chapter Has Shown 192 MORE ON TABLES 21What This Chapter Is About 21The Logic of Elaboration 22Suppressor Variables 25Additive and Interaction Effects 26Direct Standardization 28A Final Note on Statistical Controls Versus Experiments 43What This Chapter Has Shown 453 STILL MORE ON TABLES 47What This Chapter Is About 47Reorganizing Tables to Extract New Information 48When to Percentage a Table "Backwards" 50Cross-Tabulations in Which the Dependent Variable Is Represented by a Mean 52Index of Dissimilarity 58Writing About Cross-Tabulations 61What This Chapter Has Shown 634 ON THE MANIPULATION OF DATA BY COMPUTER 65What This Chapter Is About 65Introduction 66How Data Files Are Organized 67Transforming Data 72What This Chapter Has Shown 80Appendix 4.A Doing Analysis Using Stata 80Tips on Doing Analysis Using Stata 80Some Particularly Useful Stata 10.0 Commands 845 INTRODUCTION TO CORRELATION AND REGRESSION (ORDINARY LEAST SQUARES) 87What This Chapter Is About 87Introduction 88Quantifying the Size of a Relationship: Regression Analysis 89Assessing the Strength of a Relationship: Correlation Analysis 91The Relationship Between Correlation and Regression Coeffi cients 94Factors Affecting the Size of Correlation (and Regression) Coeffi cients 94Correlation Ratios 99What This Chapter Has Shown 1026 INTRODUCTION TO MULTIPLE CORRELATION AND REGRESSION (ORDINARY LEAST SQUARES) 103What This Chapter Is About 103Introduction 104A Worked Example: The Determinants of Literacy in China 113Dummy Variables 120A Strategy for Comparisons Across Groups 124A Bayesian Alternative for Comparing Models 133Independent Validation 135What This Chapter Has Shown 1367 MULTIPLE REGRESSION TRICKS: TECHNIQUES FOR HANDLING SPECIAL ANALYTIC PROBLEMS 139What This Chapter Is About 139Nonlinear Transformations 140Testing the Equality of Coeffi cients 147Trend Analysis: Testing the Assumption of Linearity 149Linear Splines 152Expressing Coeffi cients as Deviations from the Grand Mean (Multiple Classifi cation Analysis) 164Other Ways of Representing Dummy Variables 166Decomposing the Difference Between Two Means 172What This Chapter Has Shown 1798 MULTIPLE IMPUTATION OF MISSING DATA 181What This Chapter Is About 181Introduction 182A Worked Example: The Effect of Cultural Capital on Educational Attainment in Russia 187What This Chapter Has Shown 1949 SAMPLE DESIGN AND SURVEY ESTIMATION 195What This Chapter Is About 195Survey Samples 196Conclusion 223What This Chapter Has Shown 22410 REGRESSION DIAGNOSTICS 225What This Chapter Is About 225Introduction 226A Worked Example: Societal Differences in Status Attainment 229Robust Regression 237Bootstrapping and Standard Errors 238What This Chapter Has Shown 24011 SCALE CONSTRUCTION 241What This Chapter Is About 241Introduction 242Validity 242Reliability 243Scale Construction 246Errors-in-Variables Regression 258What This Chapter Has Shown 26112 LOG-LINEAR ANALYSIS 263What This Chapter Is About 263Introduction 264Choosing a Preferred Model 265Parsimonious Models 277A Bibliographic Note 294What This Chapter Has Shown 295Appendix 12.A Derivation of the Effect Parameters 295Appendix 12.B Introduction to Maximum Likelihood Estimation 297Mean of a Normal Distribution 298Log-Linear Parameters 29913 BINOMIAL LOGISTIC REGRESSION 301What This Chapter Is About 301Introduction 302Relation to Log-Linear Analysis 303A Worked Logistic Regression Example:Predicting Prevalence of Armed Threats 304A Second Worked Example: Schooling Progression Ratios in Japan 314A Third Worked Example (Discrete-Time Hazard-Rate Models): Age at First Marriage 318A Fourth Worked Example (Case-Control Models):Who Was Appointed to a Nomenklatura Position in Russia? 327What This Chapter Has Shown 329Appendix 13.A Some Algebra for Logs and Exponents 330Appendix 13.B Introduction to Probit Analysis 33014 MULTINOMIAL AND ORDINAL LOGISTIC REGRESSION AND TOBIT REGRESSION 335What This Chapter Is About 335Multinomial Logit Analysis 336Ordinal Logistic Regression 342Tobit Regression (and Allied Procedures) for Censored Dependent Variables 353Other Models for the Analysis of Limited Dependent Variables 360What This Chapter Has Shown 36115 IMPROVING CAUSAL INFERENCE: FIXED EFFECTS AND RANDOM EFFECTS MODELING 363What This Chapter Is About 363Introduction 364Fixed Effects Models for Continuous Variables 365Random Effects Models for Continuous Variables 371A Worked Example: The Determinants of Income in China 372Fixed Effects Models for Binary Outcomes 375A Bibliographic Note 380What This Chapter Has Shown 38016 FINAL THOUGHTS AND FUTURE DIRECTIONS: RESEARCH DESIGN AND INTERPRETATION ISSUES 381What this Chapter is About 381Research Design Issues 382The Importance of Probability Sampling 397A Final Note: Good Professional Practice 400What This Chapter Has Shown 405Appendix A: Data Descriptions and Download Locations for the Data Used in This Book 407Appendix B: Survey Estimation with the General Social Survey 411References 417Index 431