1 / 29

A SWISS SURVEY LANDSCAPE FOR COMMUNICATION RESEARCH

A SWISS SURVEY LANDSCAPE FOR COMMUNICATION RESEARCH. Dr. Boris Wernli Head of Survey Unit FORS, c/o University of Lausanne USI, Lugano, 2010 June 15, Institute of Communication and Health. A SWISS SURVEY LANDSCAPE FOR COMMUNICATION RESEARCH. survey typology

yaakov
Download Presentation

A SWISS SURVEY LANDSCAPE FOR COMMUNICATION RESEARCH

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. A SWISS SURVEY LANDSCAPE FOR COMMUNICATION RESEARCH Dr. Boris Wernli Head of Survey Unit FORS, c/o University of Lausanne USI, Lugano, 2010 June 15, Institute of Communication and Health

  2. A SWISS SURVEY LANDSCAPE FOR COMMUNICATION RESEARCH • survey typology • swiss survey landscape (availability, periodicity and national coverage) • Swiss Health Survey • Swiss Household Panel • SHARE project

  3. representative surveys • random sample ----- statistical inference • probabilistic interpretation • cases = anonymous individuals • data collected by sampling and surveying • problems related to unit and item non-response

  4. different survey designs no survey can satisfy everybody’s needs in terms of • topical interests • hypothesis to test • precision • available time • ressources • …

  5. survey design I • apart topical interest • who’s interviewed? what is the mother population of interest? • general population? • adults? • electors? • specific group ? (students, pensioners, children, internet users, etc.)

  6. survey design II • What is our perspective? situation at a given moment? for instance « who is now affected by a specific condition? » • cross-sectional survey trend at aggregated level ? for instance, « change in prevalence concerning a specific condition? » • repeated cross-sectional survey • same questionnaire • different samples trajectory at individual level? for instance, « who gets affected, who gets cured ? » • panel or cohort survey • same questionnaire • same respondents interviewed several times

  7. a survey typology

  8. swiss survey landscapeofficial repeated cross-sectional surveys I

  9. swiss survey landscapeofficial repeated cross-sectional surveys II

  10. swiss survey landscapeacademic driven repeated cross-sectional surveys I

  11. swiss survey landscapeacademic driven repeated cross-sectional surveys II

  12. swiss survey landscapeofficial longitudinal surveys

  13. swiss survey landscapeacademic driven longitudinal surveys I

  14. swiss survey landscapeacademic driven longitudinal surveys II

  15. the Swiss Health Survey I • realized by the SFO • every 5 years, 1992, 1997, 2002, 2007, next in 2012 • repeated cross-sectional, CATI + drop-off paper questionnaire • very large sample (12’000 national + cantonal oversampling  19’000) • general population (15 and older) • data collected during the whole year- seasonal variations • data disponibility • SUF complete file, with contract, charge but discount… • PUS reduced version, no contract, free, download • limited set of sociodemo variables (privacy) • downloadable from end of 2010 on FORS COMPASS site

  16. the Swiss Health Survey II • International (and national) comparability • 18 items European Health Interview Surveys (EHIS) (Eurostat + WHO) • EHSM (health status) • EHDM (health determinants) • EHCM (health care) • EBM (background variables) • MEHM, 3 items Minimum European Health Module • general health • chronic condition • activity restriction

  17. the SHP (Swiss Household Panel) www.swisspanel.ch

  18. Swiss Household Panel • a survey on living conditions of the Swiss population • principal aim: monitor social change • the Swiss Household Panel is originally (1999) a joint project of the Swiss National Science Foundation (SNF), the Swiss Federal Statistical Office and the University of Neuchâtel. • since January 2008, the SHP is part of the Swiss Competence Center for Social Research FORS at the University of Lausanne. • financed by the Swiss National Science Foundation • ressources: ± 8 full-time jobs, pluridisciplinary team

  19. Characteristics of SHP • started 1999, yearly  11 waves available • household survey (individual questionnaires with all household-members 14 years old and older) • panel survey: individuals are followed over time • large sample (3200 – 7500 HH, 5200–11’400 P per year) • CATI-survey (Computer Assisted Telephone Interviews) • interviews in German, French and Italian • various disciplines covered (social sciences in a broad sense) • objective and subjective questions • complex survey

  20. Interviewed individuals SHP 1999-2009 / SILC 2004-2005

  21. survey realized with 5+1 complementary questionnaires • GRID : household composition, basic characteristics of members (sex, birthyear, occupation, civil status, nationality), relations between members + adress, phone numbers, etc. • HOUSEHOLD QUESTIONNAIRE with reference person • INDIVIDUAL QUESTIONNAIRE, for persons 14 and older • PROXY QUESTIONNAIRE: for persons under 14 or unable to answer • BIOGRAPHIC QUESTIONNAIRE (paper) : unique, 2001-2002 • INTERVIEWERS QUESTIONNAIRE (paper)

  22. Topics of the survey • Socio-economic variables: socio-demographic characteristics, education, work, housing, income and standard of living + social origins (mother and father’s education, etc.) →social stratification and mobility • Events: Marriage, Birth, Death, Illness, Accident, Conflicts etc. → Life cycle, but also “accidents” of life • Social, political and cultural participation: social networks, associations, votes, elections, parties, leisure activities → Integration, social relationships, political behavior • Perceptions and values: feeling of poverty, insecurity, confidence, gender equality → Representation, values, social capital • Psychological scales and mesures: Big Five Ten, risk aversion, self-efficacy since W11 • Satisfaction and health: Self-evaluations, various pains, chronic handicaps, (tobacco since W12) → Quality of life, health sociology, public health

  23. individual level – health modulepartly compatible EHIS « subjective » elements • health status • change in health since last wave • satisfaction of health status • impediment in everyday activities • depression and optimism « objective » elements » • troubles and problems • back • sleeping • weakness, weariness • headaches • doctor’s visits, hospitalisation • medication • weight, height • present and former smoking (w12) • physical activity • number of days affected • long term illness or condition • cause • since when

  24. Data structure I data and documentation files download • 2 annual files (now 11 waves available) • households • individuals 5 data files «all waves» • master Persons • master Household • social Origin • last job • activities calendar • additional files • biographic questionnaire • interviewer data

  25. Data structure II • additional data (on demand) • Contact data (from centralized CATI) • Imputed income (of income variable in annual CD) • Geographic data (municipalities) • SILC Pilot-Study (2004, 2005) • data access • Sign contract (www.swisspanel.ch) • code for dowload sent by e-mail

  26. International household panels landscape

  27. SHP CNEF-Data • Demographics: all • Employment: all • Medical/health: partly available • Equivalence scale inputs, location, psychological, weights, identifiers: all • Yearly income • Not available: Imputed rental income, Household Federal Taxes, Household Private Retirement Income • Household taxes completely simulated • Imputed item non-response and unit non-response • Imputation method: depending on variable • Little and Su (distinguished by education groups) • Carry over (for stable social security pensions)

  28. SHP – analytical perspectives • cross-sectional « classic » analysis • matching partners and/or children data • matching parents-children data not living together (social origin) • three generations models • multilevel modeling (individual, household, commune, canton, etc.) • repeated cross sectional – trends at aggregated level • longitudinal analysis • event history analysis (survival analysis, discret time logistics, Cox regression) • study sequences (optimal matching, TraMiner) • change on continuous variables (LMM, growth curve models, SEM, etc.)

  29. Thank you! www.swisspanel.ch swisspanel@fors.unil.ch boris.wernli@fors.unil.ch

More Related