DRE 1009 Multilevel Analyses

APPLIES TO ACADEMIC YEAR 2013/2014

DRE 1009 Multilevel Analyses


Responsible for the course
Karl Gustaf Jøreskog

Department
Department of Economics

Term
According to study plan

ECTS Credits
6

Language of instruction
English

Introduction
Please note that this course will be revised before it is offered again
Multilevel analysis is the analysis of multilevel data where some observational units are nested within other observational units. For example, students are grouped in classes, classes are grouped in schools, and so on. Multilevel models, also called hierarchical linear models and their associated techniques take the inherent data into account in the analysis.
Lectures and Computer Exercises (30 hours).

Learning outcome
Students should learn the theory and practice of Multilevel Analysis so as to be able to carry out such analysis with LISREL on empirical data.

Prerequisites
Either DRE 1011 Quantitative Research Methods: Multivariate Statistics or DRE 1004 Multivariate Statistics.

Admission to a PhD Programme is a general requirement for participation in PhD courses at BI Norwegian Business School.

External candidates are kindly asked to attach confirmation of admission to a PhD programme when signing up for a course with the doctoral administration. Other candidates may be allowed to sit in on courses by approval of the courseleader. Sitting in on courses does not permit registration for courses, handing in exams or gaining credits for the course. Course certificates or conformation letters will not be issued for sitting in on courses


Compulsory reading
Books:
Bollen, Kenneth A. & Patrick J. Curran. 2006. Latent curve models : a structural equation perspective. Hoboken, N.J. : Wiley-Interscience
Snijders, T.A.B. and Roel J. Bosker. 1999. Multilevel analysis : an introduction to basic and advanced multilevel modeling. London : Sage


Recommended reading
Books:
Heck, Ronald H. & Scott L. Thomas. 2009. An introduction to multilevel modeling techniques. 2nd ed. New York : Routledge
Hox, J. J. 2010. Multilevel analysis : techniques and applications. 2nd ed. New York : Routledge. Ny utgave forventes juni 2010


Course outline
Importing data into LISREL and data management
Regression analysis and generalized linear models
Two- and three-level regression models
Multilevel models with categorical outcomes
Multilevel models for longitudinal data
Latent curve models

Computer-based tools
LISREL, It's learning / homepage

Learning process and workload
Workload
Lectures and computer exercises 30 hours
Specified learning activities 80 hours
Autonomous student learning 50 hours
Three class presentations 3 hours
Total 163 hours


Examination
Termpaper.
The paper should be original work, and be written specifically for this course. The course will be graded pass / fail


Examination code(s)
DRE 10092 accounts for 100% of the grade.

Examination support materials


Re-sit examination
Next time the course is offered

Additional information
Honour Code
Academic honesty and trust are important to all of us as individuals, and represent values that are encouraged and promoted by the honour code system. This is a most significant university tradition. Students are responsible for familiarizing themselves with the ideals of the honour code system, to which the faculty are also deeply committed.

Any violation of the honour code will be dealt with in accordance with BI’s procedures for cheating. These issues are a serious matter to everyone associated with the programs at BI and are at the heart of the honor code and academy integrity. If you have any questions about your responsibilities under the honour code, please ask.