last reminder: What would it take to change your inference? May 19 1pm-5pm (EDT) as part of the American Educational Research Association virtual learning series.

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Ken Frank

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May 14, 2020, 9:09:42 AM5/14/20

to KonFound-it!

Last reminder:

I will be giving a workshop on May 19 1pm-5pm (EDT) as part of the American Educational Research Association virtual learning series.

Course Description

What would it take to Change your Inference? Quantifying the Discourse about Causal Inferences in the Social Sciences

Motivation
Statistical inferences are often challenged because of uncontrolled bias. There may be bias due to uncontrolled confounding variables or non-random selection into a sample. We will answer the question about what it would take to change an inference by formalizing the sources of bias and quantifying the discourse about causal inferences in terms of those sources. For example, we will transform challenges such as “But the inference of a treatment effect might not be valid because of pre-existing differences between the treatment groups” to questions such as “How much bias must there have been due to uncontrolled pre-existing differences to make the inference invalid?” “QQQ% of the cases would have to be replaced with cases with no treatment effect to change the inference.”

Approaches
In part I we will use Rubin’s causal model to interpret how much bias there must be to invalidate an inference in terms of replacing observed cases with counterfactual cases or cases from an unsampled population. In part II, we will quantify the robustness of causal inferences in terms of correlations associated with unobserved variables or in unsampled populations. Calculations for bivariate and multivariate analysis will be presented using an app: http://konfound-it.com as well as macros in STATA and R and a spreadsheet for calculating indices [KonFound-it!].