Charles S. Reichardt
Quantitative

I'm a methodologist and statistician. My research focuses on the logic and practice of causal inference in both laboratory and field settings. I'm particularly interested in quasi-experimentation, structural equation modeling, and program evaluation.

Currently, I'm developing a logic for estimating causal effects and writing a text on quasi-experimentation. Both works are concerned with the means of ruling out alternative explanations for a presumed treatment effect, and with representing and reducing uncertainty about the size of treatment effects especially where uncertainty arises from sources other than random sampling error. Another topic of long standing interest is how, when estimating treatment effects, to take account of initial differences between treatment groups when individuals have not been randomly assigned to the groups. In addition to traditional academic research, I consult for a wide range of organizations and individuals, and include students as apprentices in this work as well.

Like my research, my teaching focuses more on the logic and practice of statistical procedures than on their mathematical derivation. I'd very much welcome collaborators in research as well as in developing hands-on materials for students in both introductory and advanced statistics courses.

Representative Publications:

Reichardt, C. S. & Rallis, S. F. (Eds.) (1994). The qualitative-quantitative debate: New perspectives. New Directions for Program Evaluation, no. 61. San Francisco: Jossey-Bass.

Reichardt, C. S. & Coleman, S. C. (1995). The criteria for convergent and discriminant validity in a multitrait-multimethod matrix. Multivariate Behavioral Research, 30, 513-538.

Reichardt, C. S., Trochim, W. M. K., & Cappelleri, J. C. (1995). Reports of the death of regression-discontinuity analysis are greatly exaggerated. Evaluation Review, 19, 39-63.

Reichardt, C. S. & Gollob, H. F. (1997). When confidence intervals should be used instead of statistical tests, and vice versa. In Harlow, L. L., Mulaik, S. A., & Steiger, J. H. (Eds). What if there were no significance tests? (pp. 259-284). Hillsdale, NJ: Lawrence Erlbaum.

Reichardt, C. S. & Mark, M. M. (1998). Quasi-experimentation. In Bickman, L. & Rog, D. J. (Eds.), Handbook of applied social research methods. (pp. 193-228). Thousand Oaks, CA: Sage.

Reichardt, C. S. & Gollob, H. F. (in press). Justifying the use and increasing the power of a t test for a randomized experiment with a convenience sample. Psychological Methods.