CEnter for Causal Discovery Distinguished Lecture

The Case for Empirical Evaluation of Methods for Causal Modeling



Date
February 15, 2018
Time
11:00 AM - 12:00 PM
Speaker(s)
David Jensen, DSc
Profesor, College of Information & Computer Sciences, University of Massachusetts Amherst
Location
407A/B BAUM, Offices at Baum, 5607 Baum Blvd.
Category
School of Medicine - Biomedical Informatics
Contact
Toni Porterfield
Training Program Manager


412-648-9203
tls18@pitt.edu
Description
/* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Arial",sans-serif;} /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Arial",sans-serif;} A variety of methods have been developed for constructing causal models.  These include methods for estimating the structure and parameters of causal graphical models, as well as a large number of methods for estimating individual causal dependencies (e.g., propensity score methods).  The primary evidence for the effectiveness of these methods is based on either theoretical proofs or performance on synthetic data.  In this talk, I review the state of this evidence, and argue that empirical evaluation is a virtual necessity for the field to progress.  I show how the progress of non-causal modeling methods was transformed in the 1980s and 1990s by a focus on empirical evaluation.  I describe a set of techniques for empirical evaluation of methods for causal modeling, including some novel data sets and evaluation techniques developed in my research group.  Finally, I briefly survey several practical issues that are likely to arise if empirical evaluation becomes the norm, and how considering these issues could significantly advance the field of causal modeling.