Announcing the NEW AND IMPROVED Konfound-it app and upcoming workshops

[Ken Frank]

Subject: Announcing the NEW AND IMPROVED Konfound-it app and upcoming workshops

We have released a new versions of the konfound package in R (1.0.2) and in Stata. Features include:

• Conditional Robustness of Inference for Replacement (CRIR) in which there is no relationship between predictor and outcome in the replacement data conditional on other terms in the model (e.g., for use with interaction effects when models include main effects as applied in diff in diff).
• 2x2 and logistic regression added to Stata (already in R). 
  • More options for Fragility index (e.g., switch_trm)
• Unconditional Impact Threshold for a Confounding Variable is provided when possible.
  •  See Lonati, S., & Wulff, J. N. (2024). Hic Sunt Dracones: On the risks of comparing the ITCV with control variable correlations. Journal of Management.
• Coefficient of Proportionality – how strong would selection on unobserved covariates have to be relative to observed covariates to nullify an estimated effect. index = "COP"
• Directly specify a threshold for inference (other than statistical significance) via eff_thr
• Specify a non-zero null hypothesis for significance testing via nu
• Application to What Works Clearinghouse Benchmarks for educational research
• All raw results provided (in R, to_return = "raw", in Stata use “return list” after command)
• Improved statements in print out
• Improved konfound-it app interface: https://konfound-project.shinyapps.io/konfound-it/

 

Check out the konfound-it web site for more. And be sure to check out the Podcast!

 

Commands

In R:

install.packages("konfound")

library(konfound)
pkonfound(est_eff = -9.01, std_err = .68, n_obs = 7639, n_covariates = 221)

In Stata:

.   ssc install konfound
.   ssc install indeplist
.   ssc install moss
.   ssc install matsort

.   pkonfound -9.01 .68 7639 221

Upcoming workshops:

March 5 and 6 for Statistical Horizons

April 1 (possibly April 8) at 12:40-3:30 on my zoom: https://msu.zoom.us/j/783760435.  This will be a class meeting, but you can drop in.

April 7 and 9 (10:10am-11:20) on my zoom: https://msu.zoom.us/j/783760435.  This will be a class meeting, but you can drop in

Look for an announcement re: ICPSR this summer.

Sensitivity analysis within a pragmatic world view

 

Frank, K.A., Lin, Q., Maroulis, S.J. (accepted). “Causal Inferences from Observational Studies in Education Policy: Towards Pragmatic Social Science” Handbook on Education Policy Research. Published by the American Educational Research Association. Lora Cohen-Vogel, Janelle Scott and Peter Youngs editors.

 

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. ERIC:ED628601.

Support:

Thanks to U.S. Department of Education Institute for Education Sciences through R305D220022 to Michigan State University. The opinions expressed are those of the authors and do not represent views of the Institute for education Sciences or the U.S. Department. of Education.