22 February 2013
Introduction to Maximum Likelihood and Limited Dependent Variables
We begin the course with a review of the statistical theory of maximum likelihood. During the first two days the general linear model will be used as a heuristic for developing your understanding of the theory of likelihood. The remainder of the course will provide an overview of techniques in three broad categories. Day three will extend the basic framework by developing binomial models. Day four will extend to multinomial models. Finally, day five will develop binomial models with multiple trials (i.e., count models).
B. Dan Wood
Texas A&M University
Advanced students and junior researchers in political science and adjacent disciplines
Participants have the opportunity to gain 2 ECTS credits from the University of Vienna for attending an Introductory or Advanced Courses (15 hours). Participants must successfully complete their course, and successfully complete their project assignment in order to obtain 2 ECTS credits – Transcripts will be sent to the participants by The University of Vienna.
For all courses being attended (Introductory, Advanced and/or Software Training Courses), participants also receive a certificate of attendance.
Certificates of accreditation (if applicable) as well as certificates of attendance are sent to the participants after the Winter School has ended, by the University of Vienna
EUR 0: ECPR Member – €495
Non-ECPR Member – €690
ECPR Member who has attended the ECPR SSMT 2012* – €445
Non-ECPR Member who has attended the ECPR SSMT 2012* – €640
*There is a €50 loyalty discount deducted from all Introductory and Advanced Courses to participants who attended the 2012
Summer School in Methods and Techniques (SSMT) in Ljubljana (this discount does not apply to Software Training Courses).
Self funded students from ECPR member institutions will be able to apply for funding in the form of scholarship funds and travel and accommodation grants. Please use the following link for further information: http://new.ecprnet.eu/Funding/WinterSchool.as