Despite much research effort into response enhancing methods, trend studies over the years showed that response rates are declining. Differences in nonresponse trends over countries can only partially be explained by differences in survey design and field methods between countries. General attitudes towards surveys and survey climate are often named as important theoretical concepts for explaining nonresponse. To provide empirical data on survey climate and its contextual effect on nonresponse rates the Survey Attitude Scale (SAS) was developed. This scale proved to have a replicable three-dimensional factor structure (survey enjoyment, survey value, and survey burden). Partial scalar measurement equivalence was established across three panels that employed two languages (German and Dutch) and three measurement modes (web, telephone, and paper mail). For all three dimensions of the survey attitude scale, the reliability of the corresponding subscales (enjoyment, value, and burden) was satisfactory (de Leeuw et al, 2019; 2022). In this study we use latent state-trait models to examine the stability of survey attitude over time; two-thirds of the variance picked up by the SAS measures enduring aspects of a person’s survey attitude, while one-third relates to the situational aspect of survey attitude. To evaluate the explanatory and predictive power of the SAS for nonresponse and attrition, we use longitudinal negative binomial regression and survival analysis including an extensive list of covariates. We find that the explanatory power of the SAS persists in the presence of a respondent’s socio- and psycho-demographic profile. With respect to the predictive power, we find that the socio- and psycho-demographic profile is better at forecasting nonresponse, while the SAS is better at forecasting panel attrition. Interestingly, the predictive power of the SAS is already realized after including one wave.
- Cite as: Rosche, B., Bons, H., Hox, J., & De Leeuw, E. (2025). Survey Attitude as Indicator for Survey Climate and as Predictor of Nonresponse and Attrition in a Probability-Based Online Panel. Survey Research Methods, 19(3), 279–293.
- The project has been presented at the International Workshop on Household Survey Nonresponse 2016 and the General Online Research Conference 2017.