KonFound-It!
The facts below are what the maker publishes about KonFound-It!, checked and dated. Our editors have not written about it yet.
The facts
Each one read from KonFound-It!'s own pages, with the date it was checked.
What it does
- Audience
- The project describes its intended users as researchers, policy makers, and pragmatists evaluating statistical inferences.checked 12 Oct 2026
- Benchmark tool
- The project provides an interactive tool for sensitivity analyses calculated for the What Works Clearinghouse benchmark dataset.checked 11 Oct 2026
- Bias analysis
- The project develops sensitivity analyses that quantify how robust inferences are to omitted variables and other sources of bias.checked 11 Oct 2026
- Deployment
- bothchecked 23 Sep 2026
- Guidance
- The Practical Guide is intended to help implement ITCV and RIR sensitivity analyses.checked 11 Oct 2026
- ITCV
- Impact Threshold for a Confounding Variable estimates how strongly an omitted variable would need to relate to the predictor and outcome to change an inference.checked 12 Oct 2026
- ITCV caveat
- The package documentation cautions that ITCV was originally derived for OLS standard errors and should be interpreted cautiously when reported standard errors are not OLS-based.checked 12 Oct 2026
- Known limitation
- The FAQ says there is currently no module specifically designated for multinomial outcomes.checked 12 Oct 2026
- Known model gaps
- The FAQ says there is no module specifically designated for multinomial outcomes, and that predictive models using machine learning and fixed effects are under development.checked 11 Oct 2026
- License
- The konfound R package is listed as MIT licensed.checked 12 Oct 2026
- Meta-analysis
- The R package includes mkonfound() for comparing or synthesizing sensitivity analyses across multiple analyses.checked 12 Oct 2026
- Purpose
- KonFound-It! provides sensitivity analyses to evaluate how robust statistical inferences are to potential bias.checked 12 Oct 2026
- Regression models
- Yeschecked 23 Sep 2026
- RIR
- Robustness of Inference to Replacement estimates how much of an observed effect would need to be bias-driven to change an inference.checked 12 Oct 2026
- R package
- The konfound R package supports sensitivity analysis for models fit in R and published study results.checked 12 Oct 2026
- Scripting support
- Yeschecked 23 Sep 2026
- Security
- The pages opened describe the browser app and software packages but do not state security or compliance claims.checked 11 Oct 2026
- Stata package
- The project provides a Stata command for quantifying the robustness of causal inferences.checked 12 Oct 2026
- Statistical tests
- Yeschecked 23 Sep 2026
- Support
- The team directs general questions and support to its Google Group community forum.checked 12 Oct 2026
- WWC benchmarks
- A dedicated interactive tool presents sensitivity analyses calculated for the What Works Clearinghouse benchmark dataset.checked 12 Oct 2026
Where it runs
- Browser app
- The Shiny app runs sensitivity analyses in a web browser without requiring software installation.checked 12 Oct 2026
Money
- Free plan
- Yeschecked 23 Sep 2026
The company
- Maker
- The site describes KonFound-It! as a project run by a group of researchers spanning multiple institutions.checked 11 Oct 2026
