Institute of Sociology
of the Federal Center of Theoretical and Applied Sociology
of the Russian Academy of Sciences

Dorofeeva Z. E., Kozyreva P. M., Kosolapov M. S., Tonis E. I. (2026) Russian Longitudinal Monitoring Survey — Higher School of Economics (RLMS-HSE): Methodological Features, Organizational Principles, Research Opportunities. Monitoring of Public Opinion: Economic and Social Changes.No. 1. P. 40–64. https: ...



Dorofeeva Z. E., Kozyreva P. M., Kosolapov M. S., Tonis E. I. (2026) Russian Longitudinal Monitoring Survey — Higher School of Economics (RLMS-HSE): Methodological Features, Organizational Principles, Research Opportunities. Monitoring of Public Opinion: Economic and Social Changes.No. 1. P. 40–64. https://www.doi.org/10.14515/monitoring.2026.1.3210. (In Russ.)
ISSN 2219-5467
DOI 10.14515/monitoring.2026.1.3210
ÐÈÍÖ: https://elibrary.ru/item.asp?id=89066436

Posted on site: 23.03.26

Òåêñò ñòàòüè íà ñàéòå æóðíàëà URL: https://www.monitoringjournal.ru/index.php/monitoring/article/view/3210/2326 (äàòà îáðàùåíèÿ 23.03.2026)


Abstract

The article examines the method­ology, organizational principles, and research potential of the «Russian Longitudinal Monitor­ing Survey — HSE (RLMS­HSE)». It describes the sample structure, its design features, and size dynamics, including expansion and reduc­tion of the sample. The article focuses on the formation of the pure panel part of the sam­ple, with special emphasis on respondent at­trition across the 30­year survey period. It is shown that the mechanisms of this process are not random; certain groups systematical­ly leave the panel more actively than others. For instance, the proportion of men leaving the study is consistently higher than that of women. Another significant factor is age; the age group most "retained" in the sample con­sists of respondents who were between 31 and 45 years old in 1994. Rural residents are more likely to be among those participating in the survey for 25 years or longer. Weighting as one of the most common and accessible meth­ods is considered as an example for correcting sample bias. Meanwhile, the analysis of sam­pling errors in RLMS­HSE shows that bias in representative samples of each consecutive round is minor. The article presents examples of studies using the panel component of the data along with the broad set of socio­eco­nomic indicators and demonstrate the exten­sive potential of RLMS­HSE, including its appli­cations in the field if interdisciplinary research.