Tuesday 16th July
Wednesday 17th July
Thursday 18th July
Friday 19th July
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Explanatory and independent variables in social surveys across countries 2 |
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| Convenor | Dr Uwe Warner (CEPS/INSTEAD) |
| Coordinator 1 | Professor Juergen H.p. Hoffmeyer-zlotnik (University Giessen) |
This session deals with the national standardization and the international harmonization of explanatory and independent variables in social surveys.
National standards for socio-demographic variables allow to compare surveys with other national survey data from official statistics, market and academic research. This is of importance because data from official statistics are often used to describe the quality of social survey outcomes.
International harmonization of background variables allows the comparison of survey data across countries.
For this session we welcome contributions on
- theories about the comparative approach in survey methodology in particular during the data collection,
- the strength and weakness of standardization on national and the harmonization on international level,
- the "best practice" to make social and demographic variables in register data comparable across countries,
- new and innovative measurements of explanatory and independent variables in social surveys,
- ongoing research discussing the explanatory power of social-demographic background variables in comparative surveys,
- studies exploring the total survey error and the measurement quality of independent variables in international surveys,
- and other topics on national standards and international harmonization of survey measurements.
Researchers want to be able compare data both within and across international surveys. To facilitate the within-country comparison of national surveys, some countries have developed national 'demographic standards'.
Although Eurostat has developed a corresponding instrument for the cross-national comparison of official statistics, no such instrument exists in the area of academic social research.
The problem of comparing data across surveys always manifests itself when the variables have not been centrally formulated. The ESS formulates the socio-demographic variables in an English-language source questionnaire and checks the translations into the languages spoken by the national research teams.
The problem of comparing data across surveys always manifests itself when the variables have not been centrally formulated. The ESS formulates the socio-demographic variables in an English-language source questionnaire and checks the translations into the languages spoken by the national research teams.
We will explore the extent to which socio-demographic variables can be compared across academically driven surveys. By way of example, we compare five core variables from three large international surveys: the ESS, the ISSP, and the EVS.
Since 2005, the European Union is monitoring a disability-free life expectancy indicator named "Healthy Life Years" (HLY). HLY measures the remaining number of years a person can expect to live free of activity limitation. Accurate monitoring of HLY across European countries is imperative. Accordingly, extensive efforts were deployed in order to harmonize the data collection underlying the measurement of the HLY indicator.
The study aims to validate and increase understanding of the Global Activity Limitation Indicator (GALI) - the activity limitation measure from which the HLY indicator is generated - by investigating country variations in answering behaviors.
Data from the European Health Interview Survey (EHIS) wave1 is used to explore how the GALI is associated with other existing health measures and whether the GALI is consistent or reflects different health levels in different countries. For every country and every health measure, a logistic regression model is fitted to estimate the odds of activity limitation vs. no limitations, adjusting for age and gender. The odds ratios of the models were then compared by assessing heterogeneity between countries by fitting a random-effect meta-analysis model for the health measure of interest.
Analyses reveal that although the GALI shows association with other existing health measures in every country, it reflects functioning, disability and morbidity differently across Member States. This suggests that HLY values derived from EHIS data are not sufficiently valid to allow international comparisons.
In this paper the waves 2 to 4 of the pairfam-survey are analyzed with special respect to interviewer behavior in first contact. Interviewers were asked to fill out a contact protocol for each respondent (n=12.402 in wave 1) that allows us to analyze the date and time of up to 8 contacts and whether this contact is by phone or personal. Unfortunately, not all interviewers did what there were asked for, but the dataset contains information for nearly 3.000 respondents for all three waves. I will focus on first contact and describe what changes and what keeps stable over the three waves and how this influences the participation rate. E.g. the rate of using telephone to contact first increases significantly, whereas the time of first contact is nearly the same in all three waves. Additionally, the contact protocols allow to prove whether there is a kind of agreement between the respondent and the interviewer of when and how the first contact in the next wave will take place. The results show that every day that goes by between the distribution of the letters of information and first contact by the interviewer significantly decreases the probability to participate in the survey, whereas the time of first contact has no influence.
In times of population ageing, information on life-phases becomes more important. Life-phases are longer-lasting situations within a person's live, e.g. the middle-age during which people work for pay, or old age, which starts upon retirement. These life-phases paint a detailed picture of the social implications of population ageing. Previous studies developed categorical variables that capture life-phases in cross-sectional country-comparative surveys. However, life-phases are a longitudinal phenomenon. This paper studies whether cross-sectional variables capture the longitudinal phenomenon of life-phases with enough precision, or whether they are skewed indicators