TY - BOOK AU - Babones,Salvatore TI - Fundamentals of regression modeling T2 - Sage benchmarks in social research methods SN - 9781446208281 (hbk : 4 vol. set) U1 - 000SB:300 23 PY - 2013/// CY - Los Angeles PB - SAGE, KW - Social sciences KW - Statistical methods KW - Regression analysis KW - Research KW - Statistics N1 - Includes bibliographical references; Machine generated contents note: Volume I -- 1. Regression Fundamentals for the Social Sciences / Salvatore Babones -- 1. The Meaning of p-Values -- 2. The Nonutility of Significance Tests: The Significance of Tests of Significance Reconsidered / Sanford Labovitz -- 3. Mindless Statistics / Gerd Gigerenzer -- 4. Confusion over Measures of Evidence (p's) versus Errors ([alpha]'s) in Classical Statistical Testing / M.J. Bayarri -- 5. Why We Don't Really Know What Statistical Significance Means: Implications for Educators / J. Scott Armstrong -- 6. Researchers Should Make Thoughtful Assessments Instead of Null-Hypothesis Significance Tests / Fiona Fidler -- 2. Control Variables -- 7. Explaining Interstate Conflict and War: What Should Be Controlled For? / James Lee Ray -- 8. The Phantom Menace: Omitted Variable Bias in Econometric Research / Kevin A. Clarke -- 9. Beyond Baron and Kenny: Statistical Mediation Analysis in the New Millennium / Andrew F. Hayes. Contents note continued: 10. Equivalence of the Mediation, Confounding and Suppression Effect / Chondra M. Lockwood -- 11. Statistical Usage in Sociology: Sacred Cows and Ritual / Sanford Labovitz -- 12. Stepwise Regression in Social and Psychological Research / Daniel R. Denison -- 13. Return of the Phantom Menace: Omitted Variable Bias in Political Research / Kevin A. Clarke -- 14. Stepwise Regression: A Caution / Michael S. Lewis-Beck -- Volume II -- 3. Outliers and Influential Points -- 15. Teaching about Influence in Simple Regression / Frederick O. Lorenz -- 16. Regression Diagnostics: An Expository Treatment of Outliers and Influential Cases / Robert W. Jackman -- 17.A Survey of Outlier Detection Methodologies / Jim Austin -- 18. Practitioners' Corner: Beware of `Good' Outliers and Overoptimistic Conclusions / Vincenzo Verardi -- 19. Some Observations on Measurement and Statistics / Sanford Labovitz -- 4. Multicolinearity and Variance Inflation. Contents note continued: 20. Issues in Multiple Regression / Robert A. Gordon -- 21.A Caution Regarding Rules of Thumb for Variance Inflation Factors / Robert M. O'Brien -- 22. What to Do (and Not Do) with Multicollinearity in State Politics Research / Gregory A. Huber -- 23. On the Misconception of Multicollinearity in Detection of Moderating Effects: Multicollinearity Is Not Always Detrimental / Gwowen Shieh -- 24. Correlated Independent Variables: The Problem of Multicollinearity / H.M. Blalock Jr -- 5. Sample Selection Biases -- 25. Modeling Selection Effects / David A. Freedman -- 26. An Introduction to Sample Selection Bias in Sociological Data / Richard A. Berk -- 27. Models for Sample Selection Bias / Robert D. Mare -- 28. Sample Selection Bias as a Specification Error / James J. Heckman -- 29. How the Cases You Choose Affect the Answers You Get: Selection Bias in Comparative Politics / Barbara Geddes. Contents note continued: 30. When Less Is More: Selection Problems in Large-N and Small-N Cross-National Comparisons / Bernhard Ebbinghaus -- Volume III -- 6. Imputation Techniques -- 31. The Treatment of Missing Data / David C. Howell -- 32.A Primer on Maximum Likelihood Algorithms Available for Use with Missing Data / Craig K. Enders -- 33. What to Do about Missing Values in Time-Series Cross-Section Data / Gary King -- 34. Multiple Imputation for Missing Data: A Cautionary Tale / Paul D. Allison -- 35. Multiple Imputation for Missing Data: Making the Most of What You Know / Jonathon N. Cummings -- 36. Imputation of Missing Item Responses: Some Simple Techniques / Mark Huisman -- 37. Analyzing Incomplete Political Science Data: An Alternative Algorithm for Multiple Imputation / Kenneth Scheve -- 38. An Empirical Evaluation of the Predictive Mean Matching Method for Imputing Missing Values / Carl F. Pieper -- 7. Interaction Models. Contents note continued: 39. Testing for Interaction in Multiple Regression / Paul D. Allison -- 40. Understanding Interaction Models: Improving Empirical Analyses / Matt Golder -- 41. Product-Variable Models of Interaction Effects and Causal Mechanisms / Lowell L. Hargens -- 42. Limitations of Centering for Interactive Models / Richard L. Tate -- 43. Decreasing Multicollinearity: A Method for Models with Multiplicative Functions / M.S. Sasaki -- 44. Some Common Myths about Centering Predictor Variables in Moderated Multiple Regression and Polynomial Regression / Michael J. Zickar -- 8. Longitudinal Models -- 45.A General Panel Model with Random and Fixed Effects: A Structural Equations Approach / Jennie E. Brand -- 46.A Lot More to Do: The Sensitivity of Time-Series Cross-Section Analyses to Simple Alternative Specifications / Daniel M. Butler -- 47. Panel Models in Sociological Research: Theory Into Practice / Charles N. Halaby. Contents note continued: 48. Dynamic Models for Dynamic Theories: The Ins and Outs of Lagged Dependent Variables / Nathan J. Kelly -- 49. Using Panel Data to Estimate the Effects of Events / Paul D. Allison -- Volume IV -- 9. Instrumental Variable Models -- 50. Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments / Alan B. Krueger -- 51. Improving Causal Inference: Strengths and Limitations of Natural Experiments / Thad Dunning -- 52. Instrumental Variables Estimation in Political Science: A Readers' Guide / Donald P. Green -- 53. Instrumental Variables in Sociology and the Social Sciences / Kenneth A. Bollen -- 54. Problems with Instrumental Variables Estimation When the Correlation between the Instruments and the Endogenous Explanatory Variable Is Weak / Regina M. Baker -- 10. Structural Models -- 55. Practical Issues in Structural Modeling / Chih-Ping Chou -- 56. As Others See Us: A Case Study in Path Analysis / D.A. Freedman. Contents note continued: 57. Causation Issues in Structural Equation Modeling Research / Stanley A. Mulaik -- 58. Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach / David W. Gerbing -- 59. Structural Equation Models in the Social and Behavioral Sciences: Model Building / James G. Anderson -- 11. Causality -- 60. Statistical Models for Causation / David A. Freedman -- 61. Structural Equations and Causal Explanations: Some Challenges for Causal SEM / Keith A. Markus -- 62. The Estimation of Causal Effects from Observational Data / Stephen L. Morgan -- 63. Statistical Models for Causation: What Inferential Leverage Do They Provide / David A. Freedman -- 64. The Foundations of Causal Inference / Judea Pearl N2 - This new four-volume major work presents a collection of landmark studies on the topic of regression modeling, identifying the most important, fundamental articles out of thousands of relevant contributions ER -