Course module SOW-SCS131 Credits (ECTS) 3 Category - Language of instruction English Offered by Radboud University; Faculty of Social Sciences; Social and Cultural Sciences; Lecturer(s) Examiner prof. dr. R.N. Eisinga Other course modules lecturer Lecturer prof. dr. R.N. Eisinga Other course modules lecturer Contactperson for the course prof. dr. R.N. Eisinga Other course modules lecturer Academic year 2017 Period PER1   (04/09/2017 to 12/11/2017) Starting block PER1 Course mode full-time Remarks - Registration using OSIRIS Yes Course open to students from other faculties No Pre-registration No Waiting list No Placement procedure -

	Aims Knowledge: Students obtain up-to-date statistical knowledge and understanding of multilevel regression models for the analysis of continuous and binary dependent variables. Skills: Students obtain skills in analyzing continuous and binary responses using multilevel regression models with modern computer software. They learn how to communicate the results of multilevel models to a specialist and non–specialist audience. Attitudes: Students are able to look at the analysis of hierarchically structured data with a more sophisticated and critical attitude.   Content In a series of five sessions students gain insight in both theory and practice of linear and logistic multilevel regression models. Each session consists of a lecture providing background and statistical theory, followed by a lecture discussing an assignment in which data are to be analyzed and results communicated. The course includes exams testing theoretical knowledge and practical skills.   Content: 1          introduction multilevel data and models             assignment: creating multilevel datasets, decomposing variance 2          random intercept model, random slope model             assignment: multilevel linear regression analysis 3          cross–level interaction model             assignment: cross–level interaction analysis 4          within and between effects             assignment: analysis of within and between effects 5          multilevel logistic regression             assignment: multilevel logistic regression analysis   Test information Written exam and practical exam Prerequisites None
	Recommended materials Literature Hox, J.J. (2002). Multilevel Analysis. Techniques and Applications. London: Lawrence Erlbaum Associates. Literature Kreft, I. and J. de Leeuw (1998). Introducing Multilevel Modelling. London: Sage. Literature Snijders, T. and R. Bosker (1999). Multilevel Analysis. London: Sage. Literature Finch, W. H., J.E. Bolin and K. Kelley (2014). Multilevel Modeling Using R. Boca Raton: CRC Press. Instructional modes Lecture Attendance Mandatory Yes Remark Lectures and computer lab exercises Tests Written exam and practical exam Test weight 1 Opportunities Block PER1, Block PER2