Modeling group-specific interviewer effects on survey participation using separate coding for random slopes in multilevel models

Despite its importance in terms of survey participation, the literature is sparse on how face-to-face interviewers differentially affect specific groups of sample units. In this paper, we demonstrate how an alternative parametrization of the random components in multilevel models, so-called separate coding, delivers valuable insights into differential interviewer effects for specific groups of sample members. At the example of a face-to-face recruitment interview for a probability-based online panel, we detect small interviewer effects regarding survey participation for non-Internet households, whereas we find sizable interviewer effects for Internet households. Based on the proposed variance decomposition, we derive practical guidance for survey practitioners to address such differential
interviewer effects.