Advanced Quantitative Methods

Please note: This page refers to a course that has already taken place.

Time:

04 - 08 May 2015

Place:

University of Oslo

Organizer:

Håvard Hegre (Univ. Uppsala, PRIO and UiO) and Håvard Strand (UiO and PRIO)

Credits:

10 ECTS

Contact:

Guro Schmidt Øvregard (g.s.ovregard@stv.uio.no)

Lecturers:

Håvard Hegre and Håvard Strand

​This course aims at providing students with a thorough understanding of how quantitative methods can be used in the study of politics. Over the last ten years, the quantitative researcher’s toolbox has been expanded greatly, both in terms of new statistical models, stable implementations in readily available software and in best practices through actual applications of these models.

Course Description:

​This course will provide a solid foundation for future advances into these territories by a thorough examination of the foundational statistical models and examples of how these can be expanded. We will focus on the caveats: what assumptions are made, how much damage is incurred by violating these and, most importantly, how can these models be used to communicate a more efficient answer to a specific audience?

The format will be a mix of lectures (12 hrs) and exercises (6 hrs) in STATA. The lectures will cover the theory whereas the exercises will focus on verification of different estimators, and we will in particular problematize the interpretation of statistical significance.

Please note that this course is organized by the University of Oslo (UiO), in association with the Research School on Peace and Conflict. For more information, please visit the UiO course website.

Schedule:

(Preliminary schedule)

1: OLS and extension2: Spatial regression models
3: Instrumental variable regression4: Logistic regression
5: Logistic regression6: Ordinal Logistic regression
7: Multinominal Logistic regression8: Goodness of fit
9: Count models10: Count models
11: Event history models12: Event history models

Deadlines:

Application deadline: 1 April 2015

Admission:

PhD candidates from ISV: Apply for the course in StudentWeb

Other PhD candidates: Application form