History | Staff & Course Pages (2011-2018)
History | Staff & Course Pages (2011-2018)
Lectures 24 hours
PC classes 9 hours
Credits: 4/6 ECTS credits
Assessment: Active participation during the course, exam 4 cu + optional homework assignment of 2 cu
The course covers materials on modern survey research methods used for empirical quantitative research in social and behavioral sciences and economics. Topics include study design, sampling methods, data collection and measurement, data cleaning (edit, imputation) and the analysis of complex survey data. The course is of applied type. Treatment of each method includes general description of the methodology, data requirements, computation, worked examples and real-world case studies. Selected computational tools (SAS, SPSS) are practiced in computer classes.
The course is intended to post-graduate students in social and behavioral sciences and economics but also can be included in methodologically oriented Master studies (e.g. the REMS program) and Master studies in statistical science.
Topics of Part 1 (Seppo Laaksonen): Study design, basic sampling techniques, data collection modes, treatment of nonresponse, reweighting, imputation techniques (single and multiple imputation), use of secondary data (data archives, administrative and register data sources). Examples include: The European Social Survey, The PISA and the Ethiopian Consumption and Welfare Monitoring Survey.
Topics of Part 2 (Kimmo Vehkalahti): Exploratory and confirmatory analysis, reliability, validity and measurement errors, data reduction with factor analysis, visualization of multidimensional data.
Topics of Part 3 (Risto Lehtonen): Hierarchical or multilevel data, analysis of multilevel or cluster correlated data, basic multilevel modelling, linear and logistic mixed models, software.
Part 1: Seppo Laaksonen
Lectures: Tuesday 11 Sept. at 14-18
Thursday 13 Sept. at 14-16
PC training: Thursday 13 Sept. at 16-19
Part 2: Kimmo Vehkalahti
Lectures: Tuesday 18 Sept. at 14-18
Thursday 20 Sept. at 14-16
PC training: Thursday 20 Sept. at 16-19
Part 3: Risto Lehtonen
Lectures: Tuesday 25 Sept. at 16-20 (please note timing!)
Thursday 27 Sept. at 14-16
PC training: Thursday 27 Sept. at 16-19
Venue: SSKH IT-sal, Snellmaninkatu 1. Please note the exception: Tuesday 18 Sept. at 14-16, Unioninkatu 37, seminar room 4
Course exam: Tuesday 2 October at 14:00-17:00, Unioninkatu 40, room 2
Course exam 2 (resit): *New*
Date: Monday 22 October 2012 at 12:00-16
Venue: Kumpula Campus, Exactum Building (Gustaf Hällströmin katu 2b), Auditorium A111 / B123
Registration by 14 October 2012 (Weboodi)
Lehtonen R. and Pahkinen E. (2004). Practical Methods for Design and Analysis of Complex Surveys. Second Edition. Chichester: John Wiley & Sons. Chapter 8.
International Handbook of Survey Methodology by Edith D. de Leeuw (Editor), Joop Hox (Editor), Don Dillman (Editor). (European Association of Methodology Series), 2008
Survey Methodology (Wiley Series in Survey Methodology) by Robert M. Groves (Author), Floyd J. Fowler (Author), Mick P. Couper (Author), James M. Lepkowski (Author), Eleanor Singer (Author), Roger Tourangeau (Author)
Applied survey methods: a statistical perspective by Jelke G. Bethlehem. John Wiley and Sons, 2009
VLISS-virtual laboratory in survey sampling http://mathstat.helsinki.fi/VLISS/
A concrete practical survey example from Ethiopia, considered in the end of 11 Sept: http://wiki.helsinki.fi/download/attachments/87965093/Ethiopia_hy_2012.pdf
Downloads for PC training:
Mplus code for design-based logistic regression with Mplus (COMPLEX type analysis)
PART 1: One task is to look at some ideas of questionnaires and their designing; this includes ESS questionnaires and possibly PISA questionnaires and British question banks etc mentioned in lectures. Second option is to download a ESS file from the ESS website and work with it. The third option is to look at the PISA file available here: https://wiki.helsinki.fi/download/attachments/87965093/Pisa_2009.zip
The best option is to work with her/his own file and to progress his/her own work further. Of course, the time is limited but continue during next parts.
Alternatively, own data set can be used
NOTE: For those who plan homework based on own data: Please prepare a 1 page document describing study problem, data, methods and tools, and send it to the instructors as email attachment (pdf).
Meetings will be organized for details (if needed) after exam date (will be agreed separately).
Did you forget to register? What to do.