Applied Statistical Modeling

1. Variables and Colinearity Explaining Interstate Conflict and War - J.L. Ray What Should Be Controlled for? The Moderator-Mediator Variable Distinction in Social Psychological Research - R.M. Baron and D.A. Kenny Conceptual, Strategic and Statistical Considerations Understanding and Using Mediators and Moderators - A.D. Wu and B.D. Zumbo Collinearity, Power and Interpretation of Multiple Regression Analysis - C.H. Mason and W.D. Perreault Jr. A Caution Regarding Rules of Thumb for Variance Inflation Factors - R.M. O'Brien What to Do (and Not Do) with Multicollinearity in State Politics Research - K. Arceneaux and G.A. Huber 2. Interaction Models Theory-Building and the Statistical Concept of Interaction - H.M. Blalock Jr. Testing for Interaction in Multiple Regression - P.D. Allison In Defense of Multiplicative Terms in Multiple Regression Equations - R.J. Friedrich Hypothesis-Testing and Multiplicative Interaction Terms - B.F. Braumoeller Understanding Interaction Models - T. Brambor, W.R. Clark and M. Golder Improving Empirical Analyses PART FOUR: MULTILEVEL MODELS Modeling Multilevel Data Structures - M.R. Steenbergen and B.S. Jones Multilevel Models - T.A. DiPrete and J.D. Forristal Methods and Substance Multilevel Analysis in Public Health Research - A.V. Diez-Roux Multilevel Modeling - R.F. Dedrick et al A Review of Methodological Issues and Applications Sufficient Sample Sizes for Multilevel Modeling - C.J.M. Maas and J.J. Hox PART FIVE: MODELS FOR PANEL DATA Panel Models in Sociological Research - C.N. Halaby Theory into Practice Problems with Repeated Measures Analysis - D.D. Bergh Demonstration with a Study of the Diversification and Performance Relationship Modeling Error in Quantitative Macro-Comparative Research - S.J. Babones Advances in Analysis of Longitudinal Data - R.D. Gibbons, D. Hedeker and S. DuToit PART SIX: TIME SERIES CROSS-SECTIONAL ANALYSIS What to Do (and Not to Do) with Time-Series Cross-Section Data - N. Beck and J.N. Katz Sense and Sensitivity in Pooled Analysis of Political Data - B. Kittel Dirty Pool - D.P. Green, S.Y. Kim and D.H. Yoon Time Series Cross-Section Data - N. Beck What Have We Learned in the Past Few Years? A Lot More to Do - S.E. Wilson and D.M. Butler The Sensitivity of Time-Series Cross-Section Analyses to Simple Alternative Specifications PART SEVEN: SPATIAL MODELS Spatial Autocorrelation - P. Legendre Trouble or New Paradigm? 'The Problem of Spatial Autocorrelation and Local Spatial Statistics - A.S. Fotheringham Under the Hood - L. Anselin Issues in the Specification and Interpretation of Spatial Regression Models Spatial Regression Models for Demographic Analysis - G. Chi and J. Zhu Space Is More Than Geography - N. Beck, K.S. Gleditsch and K. Beardsley Using Spatial Econometrics in the Study of Political Economy PART EIGHT: LOGISTIC REGRESSION An Introduction to Logistic Regression Analysis and Reporting - C.-Y.J. Peng, K.L. Lee and G.M. Ingersoll A Tutorial in Logistic Regression - A. DeMaris Logistic Regression: Description, Examples and Comparisons - S.P. Morgan and J. D. Teachman Binary Response Models - J.L. Horowitz and N.E. Savin Logits, Probits and Semi-Parametrics Logistic Regression - C. Mood Why We Cannot Do What We Think We Can Do, and What We Can Do about It PART NINE: MULTINOMIAL LOGIT A Primer for Social Worker Researchers on How to Conduct a Multinomial Logistic Regression - C.J. Petrucci Multinomial Probit and Multinomial Logit - J.K. Dow and J.W. Endersby A Comparison of Choice Models for Voting Research A Conceptual Framework for Ordered Logistic Regression Models - A.S. Fullerton PART TEN: POISSON REGRESSION Analysis of Count Data Using Poisson Regression - M.K. Hutchinson and M.C. Holtman The Analysis of Count Data - D.N. Barron Over-Dispersion and Autocorrelation Negative Multinomial Regression Models for Clustered Event Counts - G. Guo A Comparison of Poisson, Negative Binomial and Semi-Parametric Mixed Poisson Regression Models - K.C. Land, P.L. McCall and D.S. Nagin PART ELEVEN: INSTRUMENTAL VARIABLES Instrumental Variables and the Search for Identification - J.D. Angrist and A.B. Krueger From Supply and Demand to Natural Experiments Controlling for Endogeneity with Instrumental Variables in Strategic Management Research - G. Bascle Model Specification in Instrumental-Variables Regression - T. Dunning That Instrument Is Lousy! In Search of Agreement When Using Instrumental Variables Estimation in Substance Use Research - M.T. French and I. Popovici PART TWELVE: STRUCTURAL EQUATION MODELING Path Analysis - O.D. Duncan Sociological Examples Structural Equation Models - W.T. Bielby and R.M. Hauser Practical Issues in Structural Modeling - P.M. Bentler and C.-P. Chou Total, Direct and Indirect Effects in Structural Equation Models - K.A. Bollen Principles and Practice in Reporting Structural Equation Analyses - R.P. McDonald and M.-H.R. Ho Instrumental Variables in Sociology and the Social Sciences - K.A. Bollen PART THIRTEEN: LATENT VARIABLE MODELS Confirmatory Factor-Analytic Structures and the Theory Construction Process - R.S. Burt Latent Variables in Psychology and the Social Sciences - K.A. Bollen Specification, Evaluation and Interpretation of Structural Equation Models - R.P. Bagozzi and Y. Yi Latent Variable Models under Misspecification - K.A. Bollen et al Two-Stage Least Squares (2SLS) and Maximum Likelihood (ML) Estimators The Fallacy of Formative Measurement - J.R. Edwards