Target audience: 
  • Physicians
  • Physician Assistants
  • Nurse Practitioners
  • Nurses
  • Psychologists
  • Social Workers
  • Pharmacists
Learning objectives: 

Participants who engage in this educational intervention will be able to:

  • Understand the empirical problems facing retrospective data analysis.
  • Explore causal inference approaches (identification strategies) pursued in economics.
  • Discuss how machine learning is influencing and improving upon traditional economic methods. 
Faculty & credentials: 

Speaker(s):

Sebastian Linde, PhD, MSc, MPhil
Assistant Professor
Department of Medicine | Division of General Internal Medicine
Medical College of Wisconsin
 

In accordance with the ACCME® Standards for Commercial Support Six, all in control of content must disclose any relevant financial relationships. The following in control of content had no relevant financial relationships to disclose.

Sebastian Linde, PhD, MSc, MPhil

In accordance with the ACCME® Standards for Commercial Support Six, all in control of content must disclose any relevant financial relationships. These relationships were reviewed via the MCW conflict of interest resolution process and resolved.
 

NameCompanyRole
   
   

 

Contact

Name: 
Kaycee Valine
Phone number: 
+1 (414) 955-0388

Accreditation Statement
The Medical College of Wisconsin is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians
 
Designation of Credit Statement
The Medical College of Wisconsin designates this live activity for a maximum of 1.0 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity
 
Hours of Participation for Allied Health Professionals
The Medical College of Wisconsin designates this activity for up to 1.0 hours of participation for continuing education for allied health professionals.
 

Session date: 
12/14/2021 - 12:00pm to 1:00pm CST
Location: 
Virtual Meeting
WI
United States
  • 1.00 AMA PRA Category 1 Credit(s)™
    AMA PRA Category 1 Credit(s)™
  • 1.00 Hours of Participation
    Hours of Participation credit.

Please login or register to take this course.