Demographic Correlates of Attrition in Longitudinal Online Surveys in Russia: Evidence from Four Waves of the “Values in Crisis” Project

Demographic Correlates of Attrition in Longitudinal Online Surveys in Russia:
Evidence from Four Waves of the “Values in Crisis” Project


Sokolov B.O.

Cand. Sci. (Pol.), Leading Researcher, Assoc. Prof., Department of Sociology, HSE – St. Petersburg, Ronald F. Inglehart Laboratory for Comparative Social Research, HSE University, Moscow, Russia. bssokolov@hse.ru

Korsunova V.I.

Cand. Sci. (Sociol.), Researcher, Ronald F. Inglehart Laboratory for Comparative Social Research, HSE University, Moscow, Russia. vikorsunova@hse.ru

ID of the Article: 10671


The article was prepared within the framework of the HSE University Basic Research Program.


For citation:

Sokolov B.O., Korsunova V.I. Demographic Correlates of Attrition in Longitudinal Online Surveys in Russia: Evidence from Four Waves of the “Values in Crisis” Project. Sotsiologicheskie issledovaniya [Sociological Studies]. 2025. No 9. P. 34-48



Abstract

This study explores the demographic correlates of attrition in longitudinal online surveys by utilizing data from four Russian waves of the international «Values in Crisis» project (designed to examine societal consequences of the COVID‑19 pandemic). Respondents were recruited from an online consumer panel, maintained by OMI, a leading Russian marketing research company. Data collection occurred in June 2020, April-May 2021, November-December 2021, and July-September 2022. Only 606 (39.7 %) out of 1527 initial participants took part in all four rounds; the rest missed at least one round or dropped out. Both descriptive statistics and binary logistic regression analysis reveal that older, male, wealthier, and more educated participants had a higher probability of completing all four rounds. To sum up, attrition in online panels in the Russian context can be substantial and is largely non-random in demographic terms. Researchers should take this into account when planning longitudinal web surveys and interpreting their results.


Keywords
online survey; longitudinal study; sample attrition

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