Resource Overview

Empirical Examples & Calculators

• Published Empirical Application Examples (DOCX) — Real-world write-ups showing how to report KonFound results in peer-reviewed journals.
• Enhanced KonFound-It! Excel Spreadsheet — Calculate sensitivity indices directly in Microsoft Excel.

Impact Threshold for a Confounding Variable (ITCV)

Quantifying sensitivity based on omitted variables in linear regression models.

• Frank, K. A. (2000). Impact of a confounding variable on the inference of a regression coefficient. Sociological Methods & Research, 29(2), 147–194.
  PDF Link | DOI: 10.1177/0049124100029002001

• 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 Link | DOI: 10.3102/0162373707313781

Robustness of Inference to Replacement (RIR)

Quantifying sensitivity based on the potential outcomes and counterfactual case replacement framework.

• 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.
  Preprint DOCX | DOI: 10.1016/j.jclinepi.2021.01.025

• 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 Link | DOI: 10.3102/0162373713493129

• Frank, K. A., & Min, K. (2007). Indices of robustness for sample representation. Sociological Methodology, 37(1), 349–392.
  PDF Link | DOI: 10.1111/j.1467-9531.2007.00186.x

Combined Frameworks & Software Articles

Key papers synthesizing ITCV, RIR, and statistical package implementations.

• 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.
  Preprint PDF | DOI: 10.1016/j.ssresearch.2022.102815

• 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.
  DOI: 10.21105/joss.05779

• 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 Link | DOI: 10.1177/1536867X19874223