Fundamentals of Regression Modeling

VOLUME ONE PART ONE: THE MEANING OF P-VALUES The Non-Utility of Significance Tests - Sanford Labovitz The Significance of Tests of Significance Reconsidered Mindless Statistics - Gerd Gigerenzer Confusion over Measures of Evidence (p's) versus Errors (?'s) in Classical Statistical Testing - Raymond Hubbard and M.J. Bayarri Why We Don't Really Know What Statistical Significance Means - Raymond Hubbard and J. Scott Armstrong Implications for Educators Statistical Significance Researchers Should Make Thoughtful Assessments Instead of Null-Hypothesis Significance Tests - Andrea Schwab et al PART TWO: CONTROL VARIABLES Explaining Interstate Conflict and War - James Lee Ray What Should Be Controlled for? The Phantom Menace - Kevin Clarke Omitted Variable Bias in Econometric Research Beyond Baron and Kenny - Andrew Hayes Statistical Mediation Analysis in the New Millennium Equivalence of the Mediation, Confounding and Suppression Effect - David Mackinnon, Jennifer Krull and Chondra Lockwood Statistical Usage in Sociology - Sanford Labovitz Sacred Cows and Ritual Stepwise Regression in Social and Psychological Research - Douglas Henderson and Daniel Denison Return of the Phantom Menace - Kevin Clarke Stepwise Regression - Michael Lewis-Beck A Caution PART THREE: OUTLIERS AND INFLUENTIAL POINTS Teaching about Influence in Simple Regression - Frederick Lorenz Regression Diagnostics - Kenneth Bollen and Robert Jackman An Expository Treatment of Outliers and Influential Cases A Survey of Outlier Detection Methodologies - Victoria Hodge and Jim Austin Practitioners' Corner - Catherine Dehon, Marjorie Gassner and Vincenzo Verardi Some Observations on Measurement and Statistics - Sanford Labovitz PART FOUR: MULTICOLINEARITY AND VARIANCE INFLATION Issues in Multiple Regression - Robert Gordon A Caution Regarding Rules of Thumb for Variance Inflation Factors - Robert O'Brien What to Do (and Not Do) with Multicolinearity in State Politics Research - Kevin Arceneaux and Gregory Huber On the Misconception of Multicollinearity in Detection of Moderating Effects - Gwowen Shieh Multicollinearity Is Not Always Detrimental Correlated Independent Variables - H.M. Blalock Jr. The Problem of Multicollinearity PART FIVE: SAMPLE SELECTION BIASES Modeling Selection Effects - Thad Dunning and David Freedman An Introduction to Sample Selection Bias in Sociological Data - Richard Berk Models for Sample Selection Bias - Christopher Winship and Robert Mare Sample Selection Bias as a Specification Error - James Heckman How the Cases You Choose Affect the Answers You Get - Barbara Geddes Selection Bias in Comparative Politics When Less Is More - Bernhard Ebbinghaus Selection Problems in Large-N and Small-N Cross-National Comparisons PART SIX: IMPUTATION TECHNIQUES The Treatment of Missing Data - David Howell A Primer on Maximum Likelihood Algorithms Available for Use with Missing Data - Craig Enders What to Do about Missing Values in Time-Series Cross-Section Data - James Honaker and Gary King Multiple Imputation for Missing Data - Paul Allison A Cautionary Tale Multiple Imputation for Missing Data - Mark Fichman and Jonathon Cummings Making the Most of What You Know Imputation of Missing Item Responses - Mark Huisman Some Simple Techniques Analyzing Incomplete Political Science Data - Gary King et al An Alternative Algorithm for Multiple Imputation Landermanetal-1997 PART SEVEN: INTERACTION MODELS Testing for Interaction in Multiple Regression - Paul Allison Understanding Interaction Models - Thomas Brambor, William Roberts Clark and Matt Golder Improving Empirical Analyses Product-Variable Models of Interaction Effects and Causal Mechanisms - Lowell Hargens Limitations of Centering for Interactive Models - Richard Tate Decreasing Multicollinearity - Kent Smith and M.S. Sasaki A Method for Models with Multiplicative Functions Some Common Myths about Centering Predictor Variables in Moderated Multiple Regression and Polynomial Regression - Dev Dalal and Michael Zickar PART EIGHT: LONGITUDINAL MODELS A General Panel Model with Random and Fixed Effects - Kenneth Bollen and Jennie Brand A Structural Equations Approach A Lot More to Do - Sven Wilson and Daniel Butler The Sensitivity of Time-Series Cross-Section Analyses to Simple Alternative Specifications Panel Models in Sociological Research - Charles Halaby Theory into Practice Dynamic Models for Dynamic Theories - Luke Keele and Nathan Kelly The ins and outs of Lagged Dependent Variables Using Panel Data to Estimate the Effects of Events - Paul D. Allison PART NINE: INSTRUMENTAL VARIABLE MODELS Instrumental Variables and the Search for Identification - Joshua Angrist and Alan Krueger From Supply and Demand to Natural Experiments Improving Causal Inference: - Thad Dunning Strengths and Limitations of Natural Experiments Instrumental Variable Estimation in Political Science - Allison Sovey and Donald Green A Readers' Guide Instrumental Variables in Sociology and the Social Sciences - Kenneth Bollen Problems with Instrumental Variables Estimation When the Correlation between the Instruments and the Endogenous Explanatory Variable Is Weak - John Bound et al PART TEN: STRUCTURAL MODELS Practical Issues in Structural Modeling - P.M. Bentler and Chih-Ping Chou As Others See Us - D.A. Freedman A Case Study in Path Analysis: Journal of Education and Behavioral Statistics Causation Issues in Structual Equation Modeling Research - Heather Bullock et al Structural Equation Modeling in Practice - James Anderson and David Gerbing A Review and Recommended Two-Step Approach Structural Equation Models in the Social and Behavioral Sciences - James Anderson Model-Building PART ELEVEN: CAUSALITY Statistical Models for Causation - David Freedman Structural Equations and Causal Explanations - Keith A. Markus Some Challenges for Causal Structural Equation Modeling The Estimation of Causal Effects from Observational Data - Christopher Winship and Stephen Morgan Statistical Models for Causation - David Freedman What Inferential Leverage Do They Provide? Pearl-2010