This course is discontinued

UV9917V2 – Monte Carlo Simulations: Principles and Applications in the Social Sciences

Course content

Monte Carlo simulations play a crucial role in academic research. In the social sciences, more specifically, they are frequently used for examining the performance of new psychometric models, of estimation techniques, of statistical modelling approaches, of statistical tests, or other methodological aspects. Nearly all methodological innovations in the areas of Educational Measurement and Psychometrics are introduced based on evidence stemming from Monte Carlo simulations. Thus, this kind of study is very important for the advancement of methodological research as a prerequisite for elaborate analyses of empirical data.

The workshop covers (a) the objectives of Monte Carlo simulations, (b) their basic steps, and (c) provides practical advice for planning, setting up, conducting, and analyzing Monte Carlo simulations. The workshop format is a mixture of lectures and hands-on exercises. Participants are expected to bring their own laptop with the latest version of R installed. Further information regarding R-packages and additional software that should be installed prior to the workshop will be provided some weeks before the workshop. Prior knowledge of R is not necessary.

Learning outcome

After completing the course students will (a) know for which research questions Monte Carlo simulations are good tools, (b) know the basic steps of Monte Carlo simulations, and (c) are able to conduct own Monte Carlo simulation studies using the statistical software R.

Admission

PhD candidates at the Faculty of Educational Sciences will be given priority, but it is also possible for others to apply for the course. All applicants must hold at least a Master's degree.

Deadline for registration is April 7 2017.

Candidates admitted to a PhD-program at the Faculty of Educational Sciences (UV): Apply by Studentweb.

Other applicants: apply through registration form

Maximum number of participants is 25.

Teaching

Dates: 9th -11th May 2017

Times: 09:00-15:00

Responsible: Prof. Dr. Andreas Frey, University of Jena/Prof II CEMO and Prof. Dr. Rolf V Olsen rolfvo@cemo.uio.no.

Lecturers: Prof. Dr. Andreas Frey & Dr. Christian Spoden, University of Jena, Germany

Location: room 201, Harriet Holters Hus, University of Oslo

 

Structure

The course will span three days. On each day there will be mixture of lectures with discussion parts and hands-on exercises. At the third day, participants are invited to work on a larger simulation study (replications of published simulations) in groups. The group-specific results will be presented and discussed.

Participants are expected to bring their own laptop with the latest version of R installed. Further information regarding required R-packages, additional software that needs be installed prior to the workshop, and recommended reading will be provided some weeks before the workshop. Prior knowledge of R is not necessary.

 

Suggested Readings

Chapters 1 – 4 (pages 1-82) in: Carsey, T. M., & Harden, J. J. (2014). Monte carlo simulation and resampling methods for the social science. Thousand Oaks, CA: Sage.

This book is freely available as an e-book through the library system: https://bibsys-almaprimo.hosted.exlibrisgroup.com/primo_library/libweb/action/dlDisplay.do?vid=UBO&institution=UBO&docId=BIBSYS_ILS71528556720002201

Feinberg, R.A., & Rubright, J.D. (2016). Conducting simulation studies in psychometrics. Educational Measurement: Issues and Practise, 35(2), 36-49. pdf

The list of readings will be supplied with a number of examples of published simulation studies

Examination

To obtain 1 credit, 80 % attendance in the course is required.

To obtain 3 credits, 80 % attendance and a submitted and positively rated paper is required. A more specific description of requirement for the paper will be given at the course.

Evaluation

Evaluation form

 

Facts about this course

Credits

3

Level

PhD

Teaching

Spring 2017

Examination

Spring 2017

Teaching language

English