People and institutions involved
IES program contact(s)
Project contributors
Products and publications
Book chapter
Kim, J.S., Anderson, C.J., and Keller, B. (2013). Multilevel Analysis of Assessment Data. Handbook of International Large-Scale Assessment: Background, Technical Issues, snd Methods of Data Analysis, 389-425.
Kim, J.S., Steiner, P.M., and Lim, W.C. (2015). Mixture Modeling Methods gor Causal Inference With Multilevel Data. Advances in Multilevel Modeling for Educational Research, 335-359.
M Steiner, P. (2014). Design-and Model-Based Analysis of Propensity Score Designs. In W. Wiedermann and A. von Eye (Eds), Statistics and Causality: Methods for Applied Empirical Research (pp. 333-361). Wiley Series in Probability and Statistics. Wiley.
Journal article, monograph, or newsletter
Steiner, P.M., Cook, T.D., Li, W., and Clark, M.H. (2015). Bias Reduction in Quasi-Experiments With Little Selection Theory but Many Covariates. Journal of Research on Educational Effectiveness, 8(4): 552-576.
Steiner, P.M., and Kim, Y. (2016). The Mechanics of Omitted Variable Bias: Bias Amplification and Cancellation of Offsetting Biases. Journal of Causal Inference, 4(2).
Steiner, P.M., Kim, Y., Hall, C.E., and Su, D. (2017). Graphical Models for Quasi-Experimental Designs. Sociological Methods and Research, 46(2), 155-188.
Steiner, P.M., Park, S., and Kim, Y. (2016). Identifying Causal Estimands for Time-Varying Treatments Measured With Time-Varying (Age or Grade-Based) Instruments. Multivariate Behavioral Research, 51(6), 865-8780.
West, S. G., Cham, H., Thoemmes, F., Renneberg, B., Schulze, J., and Weiler, M. (2014). Propensity Scores as a Basis for Equating Groups: Basic Principles and Application in Clinical Treatment Outcome Research. Journal of Consulting and Clinical Psychology, 82(5), 906.
Proceedings
Hall, C.E., Steiner, P.M., and Kim, J.S. (2015). Doubly Robust Estimation of Treatment Effects from Observational Multilevel Data. In van der Ark L., Bolt D., Wang WC., Douglas J., Chow SM. (eds) Quantitative Psychology Research. Springer Proceedings in Mathematics & Statistics, vol 140. (pp. 321-340). Springer, Cham.
Keller, B., Kim, J.S., and Steiner, P.M. (2015). Neural Networks for Propensity Score Estimation: Simulation Results and Recommendations. In van der Ark L., Bolt D., Wang WC., Douglas J., Chow SM. (eds), Quantitative Psychology Research. Springer Proceedings in Mathematics & Statistics, vol 140. (pp. 279-291). Springer, Cham.
Kim, J.S., Lim, W.C., and Steiner, P.M. (2017). Causal Inference with Observational Multilevel Data: Investigating Selection and Outcome Heterogeneity. In van der Ark L., Wiberg M., Culpepper S., Douglas J., Wang WC. (Eds), Quantitative Psychology. IMPS 2016. Springer Proceedings in Mathematics & Statistics, vol 196. (pp. 287-308). Springer, Cham.
Kim, J.S., and Steiner, P.M. (2015). Multilevel Propensity Score Methods gor Estimating Causal Effects: A Latent Class Modeling Strategy. In In van der Ark L., Bolt D., Wang WC., Douglas J., Chow SM. (eds), Quantitative Psychology Research. Springer Proceedings in Mathematics & Statistics, vol 140. (pp. 293-306). Springer, Cham.
Steiner, P.M., Kim, J. S., and Thoemmes, F. (2013). Matching Strategies for Observational Multilevel Data. In JSM proceedings (pp. 5020-5032).
Questions about this project?
To answer additional questions about this project or provide feedback, please contact the program officer.
