Editorial: Introduction to the special section on causal inference in cross sectional and longitudinal mediational models

Multivariate Behavioral Research

Volumn 46, Issue 5, 2011, Pages 812-815

  West, Stephen G ^a  

^a ARIZONA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84855781915     PISSN: 00273171     EISSN: None     Source Type: Journal    
DOI: 10.1080/00273171.2011.606710     Document Type: Article

References (16)

1. Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182.
2. Cole, D. A., & Maxwell, S. E. (2003). Testing meditational models with longitudinal data: Questions and tips in the use of structural equation modeling. Journal of Abnormal Psychology, 112, 558-577.
3. Gollob, H. F., & Reichardt, C. S. (1987). Taking account of time lags in causal models. Child Development, 58, 80-92.
4. Imai, K., Jo, B., & Stuart, E. A. (2011). Commentary: Using potential outcomes to understand causal mediation analysis. Multivariate Behavioral Research, 46, 861-873.
5. Imai, K., Keele, L., & Tingley, D. (2010). A general approach to causal mediation analysis. Psychological Methods, 15, 309-334.
6. Judd, C. M., & Kenny, D. A. (1981). Estimating the effects of social interventions. New York, NY: Cambridge University Press.
7. MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. Mahwah, NJ: Erlbaum.
8. Maxwell, S. E., & Cole, D. A. (2007). Bias in cross-sectional analyses of longitudinal mediation. Psychological Methods, 12, 23-44.
9. Maxwell, S. E., Cole, D. A., & Mitchell, M. A. (2011). Bias in cross-sectional analyses of longitudinal mediation: Partial and complete mediation under an autoregressive model. Multivariate Behavioral Research, 46, 816-841.
10. Reichardt, C. S. (2011). Commentary: Are three waves of data sufficient for assessing mediation? Multivariate Behavioral Research, 46, 842-851.
11. Rosenbaum, P. R. (1984). The consequences of adjustment for a concomitant variable that has been affected by the treatment. Journal of the Royal Statistical Society, Series A, 147, 656-666.
12. Rubin, D. B. (2005). Causal inference using potential outcomes: Design, modeling, decisions. Journal of the American Statistical Association, 100, 322-331.
13. Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Boston, MA: Houghton Mifflin.
14. Shrout, P. E. (2011). Commentary: Mediation analysis, causal process, and cross-sectional data: Comment on Maxwell, Cole, and Mitchell (2011). Multivariate Behavioral Research, 46, 852-860.
15. Shrout, P. E., Keyes, K. M., & Ornstein, K. (2011). Causality and psychopathology: Finding the determinants of disorders and their cures. New York, NY: Oxford University Press.
16. West, S. G., & Thoemmes, F. (2010). Campbell's and Rubin's perspectives on causal inference. Psychological Methods, 15, 18-37.