Recommended Reading for Causal Inference | The Methodology Center

Recommended Reading for Causal Inference

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The following papers provide an accessible introduction to causal inference:

 

Schafer, J. L., & Kang, J. D. Y. (2008). Average causal effects from nonrandomized studies: A practical guide and simulated example. Psychological Methods, 13(4), 279-313. doi:10.1037/a0014268  View abstract

Lanza, S. T., Moore, J. E., & Butera, N. M. (2013). Drawing causal inference using propensity scores: A practical guide for community psychologists. American Journal of Community Psychology, 52, 380-392. doi: 10.1007/s10464-013-9604-4 PMCID: PMC4098642

 

The following papers provide the technical details and background on which current causal inference work is based:

 

Stuart, E. A. (2010). Matching methods for causal inference: A review and a look forward. Statistical Science. 25(1): 1–21. Read article 

Pearl, J. (2001). Direct and indirect e ffects. In P. Besnard & S. Hanks (Eds.), Proceedings of the seventeenth conference on uncertainty in arti cial intelligence. San Francisco, CA: Morgan Kaufman.

Robins, J. M., Hernan, M. A., & Brumback, B. A. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11, 550-560.

Rosenbaum, P. R., & Rubin, D. B. (1985). Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. The American Statistician, 39(1), 33-38.  View abstract

Rosenbaum, P. R., & Rubin, D. B. (1984). Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association, 79(387), 516-524.  View abstract

Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology. 66(5), 688-701.  View abstract

 

Ghosh, D., Zhu, Y., & Coffman, D. L. (2015). Penalized regression procedures for variable selection in the potential outcomes framework. Statistics in Medicine. doi: 10.1002/sim.6433

Zhu, Y., Schonbach, M., Coffman, D. L., & Savage, J. (2015). Variable selection for propensity score estimation via balancing covariates. Epidemiology26(2), e14-15. doi: 10.1097/EDE.0000000000000237

Zhu, Y., Coffman, D. L., & Ghosh, D. (2015). A boosting algorithm for estimating generalized propensity scores with continuous treatments. Journal of Causal Inference, 3, 25-40. doi: 10.1515/jci-2014-0022

McCaffrey, D. F., Griffin, B. A., Almirall, D., Slaughter, M. E., Ramchand, R., & Burgette, L. F. (2013). A tutorial on propensity score estimation for multiple treatments using generalized boosted models. Statistics in Medicine, 32, 3388-414.

Ghosh, D. (2011). Propensity score modelling in observational studies using dimension reduction methods. Statistics & Probability Letters, 81(7), 813-820. doi:10.1016/j.spl.2011.03.002 PMCID: PMC3099445 View article

Zhu, Y., Ghosh, D., Coffman, D. L., & Savage, J. (in press). Estimating controlled direct effects of restrictive feeding practices in the early dieting in girls study. Journal of the Royal Statistical Society, Series C (Applied Statistics).

Coffman, D. L., Melde, C., & Esbensen, F. - A. (2014). Gang membership and substance use: Guilt as a gendered causal pathway. Journal of Experimental Criminology. Advance online publication. doi: 10.1007/s11292-014-9220-9 

Coffman, D. L., & Kugler, K. C. (2012). Causal mediation of a human immunodeficiency virus preventive intervention. Nursing Research, 61(3), 224-230. PMCID: PMC2646486

Coffman, D. L. & Zhong, W. (2012). Assessing mediation using marginal structural models in the presence of confounding and moderation. Psychological Methods, 17(4), 642-664doi: 10.1037/a0029311 PMCID: PMC3553264

Coffman, D. L. (2011). Estimating causal effects in mediation analysis using propensity scores. Structural Equation Modeling, 18(3), 357-369. PMCID: PMC3212948 View article

Almirall, D., Griffin, B. A., McCaffrey, D. F., Ramchand, R., Yuen, R. A., & Murphy, S. (2014). Time-varying effect moderation using the structural nested mean model: Estimation using inverse-weighted regression with residuals. Statistics in Medicine, 33(20), 3466-3487.

Coffman, D. L., Melde, C., & Esbensen, F. - A. (2014). Gang membership and substance use: Guilt as a gendered causal pathway. Journal of Experimental Criminology. Advance online publication. doi: 10.1007/s11292-014-9220-9 

Coffman, D. L., Caldwell, L. L., & Smith, E. A. (2012). Introducing the at-risk average causal effect with application to HealthWise South Africa. Prevention Science, 13(4), 437-447. PMCID: PMC3405190

Almirall, D., McCaffrey, D. F., Ramchand, R., & Murphy, S. A. (2011). Subgroups analysis when treatment and moderators are time-varying. Prevention Science, doi:10.1007/s11121-011-0208-7 PMCID: PMC3135740   View abstract

Almirall, D., Ten Have, T., & Murphy, S. A. (2010). Structural nested mean models for assessing time-varying effect moderation. Biometrics, 66(1), 131-139. PMCID: PMC2875310  View article

Coffman, D. L., & Zhong, W. (2012). Assessing mediation using marginal structural models in the presence of confounding and moderation. Psychological Methods, 17,(4), 342-664. PMCID: PMC3553264 doi: 10.1037/a0029311

 

Powers, C. J., Bierman, K., & Coffman, D. L. (in press). Restricted educational placements for students with early-starting conduct problems: Associations with high school non-completion and adolescent maladjustment. Journal of Child Psychology and Psychiatry

Almirall, D., McCaffrey, D. F., Ramchand, R., & Murphy, S. A. (2011). Subgroups analysis when treatment and moderators are time-varying. Prevention Science, doi:10.1007/s11121-011-0208-7 PMCID: PMC3135740   View abstract

Bray, B. C., Almirall, D., Zimmerman, R. S., Lynam, D., & Murphy, S. A. (2006). Assessing the total effect of time-varying predictors in prevention research. Prevention Science, 7, 1-17.  PMCID: PMC1479302  View article

 

Coffman, D. L., Smith, E. A., Flisher, A. J., & Caldwell, L. L. (2011). Effects of HealthWise South Africa on condom use self-efficacy. Prevention Science, 12(2), 162-172. PMCID: PMC3102775  View abstract

Ertefaie, A., & Stephens, A. D. (2010). Comparing approaches to causal inference for longitudinal data: Inverse probability of treatment weighting versus propensity scores.  International Journal of Biostatistics, 6(2).

 

Read about application of causal inference methods on the Applied Research Topics page.

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