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Article

Organizing and Analyzing Data from the SHARE Study with an Application to Age and Sex Differences in Depressive Symptoms

by 1,2,*,† and 3
1
Department of Mathematics, Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, 1000 Koper/Capodistria, Slovenia
2
Medical Faculty, Institute for Biostatistics and Medical Informatics, University of Ljubljana, 1000 Ljubljana, Slovenia
3
Department of Statistics and Probability, Michigan State University, East Lansing, MI 48824, USA
*
Author to whom correspondence should be addressed.
Current address: FAMNIT, University of Primorska, Glagoljaška 8, 6000 Koper/Capodistria, Slovenia.
Academic Editor: Jouko Miettunen
Int. J. Environ. Res. Public Health 2021, 18(18), 9684; https://doi.org/10.3390/ijerph18189684
Received: 28 July 2021 / Revised: 6 September 2021 / Accepted: 10 September 2021 / Published: 14 September 2021
The SHARE study contains health, lifestyle, and socioeconomic data from individuals ages 50 and older in European countries collected over several waves. Leveraging these data for research purposes can be daunting due to the complex structure of the longitudinal design. The two aims of our study are (1) to develop a framework and R code for data management of the SHARE data to prepare for data analysis, and (2) to demonstrate how to apply the framework to a specific research question, where the aim is to model the presence of clinically significant depression assessed by the 12-item Europe depression scale. The result is a framework that substantially reduces the time to initiate research studies using SHARE data, facilitating the data extraction, data preparation and initial data analysis, with reproducible R code. Further, we illustrate the extensive work required to prepare an analysis-ready data set to ensure the validity of the modeling results. This underlines the importance of carefully considering and recording data management decisions that have to be built into the research process. The results about sex differences in the probability of depression are consistent with previous literature. Our findings about age-associated changes can be opportunities for adequate treatment interventions. View Full-Text
Keywords: SHARE; initial data analysis; data cleaning; prediction modelling; depression; older adults; sex differences; Europe SHARE; initial data analysis; data cleaning; prediction modelling; depression; older adults; sex differences; Europe
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MDPI and ACS Style

Lusa, L.; Huebner, M. Organizing and Analyzing Data from the SHARE Study with an Application to Age and Sex Differences in Depressive Symptoms. Int. J. Environ. Res. Public Health 2021, 18, 9684. https://doi.org/10.3390/ijerph18189684

AMA Style

Lusa L, Huebner M. Organizing and Analyzing Data from the SHARE Study with an Application to Age and Sex Differences in Depressive Symptoms. International Journal of Environmental Research and Public Health. 2021; 18(18):9684. https://doi.org/10.3390/ijerph18189684

Chicago/Turabian Style

Lusa, Lara, and Marianne Huebner. 2021. "Organizing and Analyzing Data from the SHARE Study with an Application to Age and Sex Differences in Depressive Symptoms" International Journal of Environmental Research and Public Health 18, no. 18: 9684. https://doi.org/10.3390/ijerph18189684

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