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HaSpaD - Data Manual (September 2021)
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GESIS - Leibniz-Institut für Sozialwissenschaften
Abstract Extensive harmonization of survey and especially biographical data has not been common in the social sciences. HaSpaD provides a tool for harmonizing and accumulating, and thus comprehensively analyzing, survey-based longitudinal data sets on partnership biographies. The following studies were harmo... view more
Extensive harmonization of survey and especially biographical data has not been common in the social sciences. HaSpaD provides a tool for harmonizing and accumulating, and thus comprehensively analyzing, survey-based longitudinal data sets on partnership biographies. The following studies were harmonized and merged for a joint analysis for the third-party funded project "Harmonizing and synthesizing partnership histories from different research data infrastructures" (HaSpaD): the panel studies pairfam, SOEP and SHARE; the cross-section studies General German Social Survey, Mannheim Divorce Study and the Fertility and Family Survey; as well as the cross-section studies combined with partially repeated surveys Family Surveys, German Life History Studies and the Generations and Gender Surveys. The project provides syntax-based harmonization processes available through the HaSpaD Harmonization Wizard. The HaSpaD Harmonization Wizard enables a customized selection of survey programs and variables. After downloading the source data sets from their repositories, the HaSpaD syntax package enables to generate an individually customized and harmonized data set of the source datasets. In addition to biographical data on partnerships, the HaSpaD target dataset may include other variables such as age, gender, citizenship, and education level. If all surveys are selected, the target data set will contain approximately 182,000 partnership biographies.... view less
Keywords
survey research; harmonization; secondary analysis; data preparation; married couple; partnership; divorce; parental separation; Federal Republic of Germany; data capture; data quality
Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Document language
English
Publication Year
2021
City
Köln
Page/Pages
105 p.
Series
GESIS Papers, 2021/12
ISSN
2364-3781
Status
Published Version; reviewed