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., Lin, Q., & Maroulis, S. (2023). Quantifying sensitivity to selection on unobservables: Refining Oster’s coefficient of proportionality. White paper. PDF
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., 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
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
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
Li, T., & Frank, K. (2022). The probability of a robust inference for internal validity. Sociological Methods & Research, 51(4), 1947-1968. Web
Lin, Q., Nuttall, A., Zhang, Q., Frank, K.A. (2023) How do unobserved confounding mediators and measurement error impact estimated mediation effects and corresponding statistical inferences? Introducing R Package ConMed for sensitivity analysis. Psychological Methods, 28(2), 339-358. 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
Pan, W. (2009). A SAS/IML macro for computing percentage points of Pearson distributions. Journal of Statistical Software, 31(Code Snippet 2), 1-6. Web
Pan, W., & Frank, K. A. (2003). A probability index of the robustness of a causal inference. Journal of Educational and Behavioral Statistics, 28(4), 315-337. Web
Pan, W., & Frank, K. A. (2004). An approximation to the distribution of the product of two dependent correlation coefficients. Journal of Statistical Computation and Simulation, 74(6), 419-443. 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