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 2219-5467DOI 10.14515/monitoring.2026.1.3210ÐÈÍÖ: https://elibrary.ru/item.asp?id=89066436Posted on site: 23.03.26Òåêñò ñòàòüè íà ñàéòå æóðíàëà URL: https://www.monitoringjournal.ru/index.php/monitoring/article/view/3210/2326 (äàòà îáðàùåíèÿ 23.03.2026)AbstractThe 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.