In this chapter, we first use the different patterns of participation to define three subsamples of primary interest for the analysis of the SHARE data collected in Wave 8: CAPI, CATI and CAPI & CATI. We then describe the procedure used to construct calibrated cross-sectional and longitudinal weights for handling, respectively, problems of unit non-response and attrition in the CAPI subsample. Afterwards, we describe the model used to obtain multiple imputations of the missing values due to item non-response in the CAPI data.
De Luca Giuseppe, Li Donni Paolo, Rashidi Moslem (2022). Weights and Imputations in SHARE Wave 8. In SHARE WAVE 8 METHODOLOGY: Collecting Cross-National Survey Data in Times of COVID-19 (pp. 133-145). Munich : Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy (MPISOC).
Weights and Imputations in SHARE Wave 8
De Luca Giuseppe
Membro del Collaboration Group
;Li Donni PaoloMembro del Collaboration Group
;Rashidi MoslemMembro del Collaboration Group
2022-01-01
Abstract
In this chapter, we first use the different patterns of participation to define three subsamples of primary interest for the analysis of the SHARE data collected in Wave 8: CAPI, CATI and CAPI & CATI. We then describe the procedure used to construct calibrated cross-sectional and longitudinal weights for handling, respectively, problems of unit non-response and attrition in the CAPI subsample. Afterwards, we describe the model used to obtain multiple imputations of the missing values due to item non-response in the CAPI data.
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