Version Date: Jul 16, 2014 View help for published
Principal Investigator(s): View help for Principal Investigator(s)
Rose Anne Kenny, Trinity College Dublin (Ireland)
Series:
https://doi.org/10.3886/ICPSR34315.v1
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2018-02-15 The citation of this study may have changed due to the new version control system that has been implemented. The previous citation was:
2014-07-16 ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:
The Irish Longitudinal Study on Ageing (TILDA) is a major inter-institutional initiative led by Trinity College Dublin which aims to produce a massive improvement in the quantity and quality of data, research and information relating to older people and ageing in Ireland. Eligible respondents for this study include individuals aged 50 and over and their spouses or partners of any age. The study involves interviews on a two yearly basis with a sample cohort of 8,504 people aged 50 and over (or their spouses/partners) and resident in Ireland, collecting detailed information on all aspects of their lives, including the economic (pensions, employment, living standards), health (physical, mental, service needs and usage) and social aspects (contact with friends and kin, formal and informal care, social participation). Both survey interviews and physical and biological measurements are utilized. Demographic and background variables include age, sex, marital status, household composition, education, and employment.
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These data were organized by Ipsos-MORI.
ESRI - Economic and Social Research Institute, Dublin, Ireland were special collaborators.
Additional information about The Irish Longitudinal Study on Ageing can be found at the TILDA Web site.
This research aims to produce a massive improvement in the quantity and quality of data, research and information relating to older people and ageing in Ireland.
The sample design incorporates stratification, clustering, multi-stage selection, and representative probablity sampling. The dataset contains the cluster variables CLUSTER and HOUSEHOLD, and the strata variable STRATUM. CLUSTER and HOUSEHOLD describe the household and geographic clusters to which participants belong. The selection of geographic clusters was stratified, so that equal numbers of clusters were selected from each of three socio-economic groups. The socio-economic status of a cluster was defined by the proportion of individuals in that cluster. STRATUM describes to which of three cluster-level socio-economic groups the respondents belong. Please refer to the ICPSR Design Report and the ICPSR Release Notes for additional information on sampling.
Individuals aged 50 years and older and their spouses or partners of any age, who are resident in Ireland.
62 percent
See: Tilda-Wave 1 AMF-Derived Variables Codebook-v.1.0.html for scales used.
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2018-02-15 The citation of this study may have changed due to the new version control system that has been implemented. The previous citation was:
2014-07-16 ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:
The data are not weighted. This dataset contains the following weight variables: CAPIWEIGHT, SCQ_WEIGHT, CAPIWEIGHT2011, BASEWEIGHT, and HA_WEIGHT. For inferences based on the TILDA dataset to be applicable to the Irish population, weights must be applied to correct for selection bias before analysis. CAPIWEIGHT is calculated by comparing the distributions of age, sex, education, marital status and geographic location in the sample to those derived from census data. SCQ_WEIGHT inflates each CAPI weight by the probability that each individual returned the SCQ and is created by dividing the CAPI weight by the predicted probability, and incorporates a minor rescaling adjustment to ensure that the total size of the weighted population remains the same. Please refer to the ICPSR Release Notes for additional information on weighting.
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