Tools
- R package (CRAN version)
- R package (development version)
- R Shiny app
- Stata package
- Benchmarks: What Works Clearinghouse [BETA]
Explanatory Resources
- FAQ
- Overview of KonFound techniques
- Overview of KonFound commands
- Quick examples
- Slides quantifying the robustness of causal inferences combined frameworks
- Slides for comparison of frameworks
Resources for Publication
Publications: Impact Threshold for a Confounding Variable
- Frank, K. (2000). Impact of a confounding variable on the inference of a regression coefficient. Sociological Methods and Research, 29(2), 147-194. PDF | Web
- Frank, K. A., Sykes, G., Anagnostopoulos, D., Cannata, M., Chard, L., Krause, A., & McCrory, R. (2008). Does NBPTS certification affect the number of colleagues a teacher helps with instructional matters?. Educational Evaluation and Policy Analysis, 30(1), 3-30. PDF | Web
Publications: Robustness of Inference to Replacement
- Frank, K. A., Lin, Q., Maroulis, S., Mueller, A. S., Xu, R., Rosenberg, J. M., Hayter, C. S., Mahmoud, R. A., Kolak, M., Dietz, T., & Zhang, L. (2021). Hypothetical case replacement can be used to quantify the robustness of trial results. Journal of Clinical Epidemiology, 134, 150-159. (authors listed alphabetically.) PDF | Web
- Frank, K. A., Maroulis, S. J., Duong, M. Q., & Kelcey, B. M. (2013). What would it take to change an inference? Using Rubin’s causal model to interpret the robustness of causal inferences. Educational Evaluation and Policy Analysis, 35(4), 437-460. PDF | Web
- Frank, K. A., & Min, K. (2007). Indices of robustness for sample representation. Sociological Methodology. 37(1). 349-392. (equal first authors.) PDF | Web
Publications for Both Frameworks
- Frank, K. A., Lin, Q., Xu, R., Maroulis, S. J., Mueller, A. (2023). Quantifying the robustness of causal inferences: Sensitivity analysis for pragmatic social science. Social Science Research, 110, 102815. PDF | Web
- Narvaiz, S., Lin, Q., Rosenberg, J. M., Frank, K. A., Maroulis, S. J., Wang, W., & Xu, R. (2024). konfound: An R sensitivity analysis package to quantify the robustness of causal inferences. Journal of Open Source Software, 9(95), 5779. Web
- Xu, R., Frank, K. A., Maroulis, S. J., & Rosenberg, J. M. (2019). konfound: Command to quantify robustness of causal inferences. The Stata Journal, 19(3), 523–550. PDF | Web