2026-05-30T08:05:39Z https://datacatalogue.cessda.eu/oai-pmh/v0/oai

358a8af49c55346208252b11b642ec0cf86352c13b93a4b8892444ff0ef85422 2025-06-17T03:14:34Z language:enopenaire_data

DDI study level documentation for study 10.7802/1494 Code: The Stratifying Role of Job level for Sickness Absence and the Moderating Role of Gender and Occupational Gender Composition Code: The Stratifying Role of Job level for Sickness Absence and the Moderating Role of Gender and Occupational Gender Composition Code: The Stratifying Role of Job level for Sickness Absence and the Moderating Role of Gender and Occupational Gender Composition 10.7802/149410.7802/149410.7802/149410.7802/1494 Kröger, Hannes Kröger, Hannes GESIS Data Archive for the Social SciencesGESIS Datenarchiv für Sozialwissenschaften This upload contains the syntax to reproduce the results published in the related article. The data is not published, but the data necessary to reproduce the analyses can be accessed by any researcher after signing a user contract: https://www.diw.de/en/diw_02.c.222518.en/research_data_center_of_the_soep.htmlThis upload contains the syntax to reproduce the results published in the related article. The data is not published, but the data necessary to reproduce the analyses can be accessed by any researcher after signing a user contract: https://www.diw.de/en/diw_02.c.222518.en/research_data_center_of_the_soep.html DeutschlandDeutschland Among the German household population: The sample is restricted in the following way: We exclude the self-employed, persons in vocational or educational training, all employees in the public sector, all those younger than 18 or older than 64, and all those who are not currently employed. We focus on employees from the private sector because, in the public sector, rules regulating promotions are more bureaucratic and job security is much stronger. Therefore, the link between sickness absence and job level will not follow the theory outlined in this paper and cannot be compared to the private sector. Lastly, all observations with missing values on sickness absence or any of the predictors are excluded, as other forms of treatment of missing values are currently not supported by the method implemented in this study. The restrictions result in a sample of 16,384 individuals and 87,573 observations. Stratified random samplingStratified random sampling Face-to-face interviewInterview.FaceToFacePersönliches InterviewInterview.FaceToFace Free access (without registration) - The research data can be downloaded directly by anyone without further limitations. CC BY-NC-SA 4.0: Namensnennung - Nicht kommerziell – Weitergabe unter gleichen Bedingungen (http://creativecommons.org/licenses/by-nc-sa/4.0/deed.de)Freier Zugang (ohne Registrierung) - Die Forschungsdaten können von jedem direkt heruntergeladen werden. CC BY-NC-SA 4.0: Namensnennung - Nicht kommerziell – Weitergabe unter gleichen Bedingungen (http://creativecommons.org/licenses/by-nc-sa/4.0/deed.de) http://dbkapps.gesis.org/dbkoai/oai.asp oai:dbk.gesis.org:SDN/10.7802_1494 2023-03-11 ddi:codebook:2_5