- Appropriate and practical methods for substantive social science research.
- Contributions by both sociologists and non-sociologists that have important methodological implications for the social sciences.
- Dedication to publishing purely methodological work that may benefi t sociology and the broader social sciences.
1. Multichannel Sequence Analysis Applied to Social Science Data (Jacques-Antoine Gauthier, Eric D. Widmer, Philipp Bucher, and C´edric Notredame).
2. Memory Bias in Retrospectively Collected Employment Careers: A Model-Based Approach to Correct for Measurement Error (Anna Manzoni, Jeroen K. Vermunt, Ruud Luijkx, and Ruud Muffels).
Causal Inference and Multivariate Data Analysis.
3. The Foundations of Causal Inference (Judea Pearl).
4. Bayesian Propensity Score Estimators: Incorporating Uncertainties in Propensity Scores into Causal Inference (Weihua An).
5. Finite Normal Mixture SEM Analysis by Fitting Multiple Conventional SEM Models (Ke-Hai Yuan and Peter M. Bentler).
6. The Simultaneous Decision(s) about the Number of Lower- and Higher-Level Classes in Multilevel Latent Class Analysis (Olga Lukociene, Roberta Varriale, and Jeroen K. Vermunt).
Methods for the Analysis of Social Network Data.
7. Respondent-Driven Sampling: An Assessment of Current Methodology (Krista J. Gile and Mark S. Handcock).
8. Dynamic Networks and Behavior: Separating Selection from Influence (Christian Steglich, Tom A. B. Snijders, and Michael Pearson).