Until recently, the study of interviewer effects has focused on establishing direct effects of interviewer characteristics on respondent response. Recently, an alternative approach has been developed which emphasizes the conditioning influence of the interviewer characteristic on the respondent s answering process. The objective of this paper is to illustrate this alternative approach with empirical evidence, using the random coefficient hierarchical regression model. This model's structure is basically as follows. First, the answering process is described at the level of the respondent. Subsequently, respondent specific parameters are related to interviewer specific variables. This structure allows inclusion of the coefficient resulting from the intra-interviewer regression in the regression equation at the interviewer level (inter-interviewer regression model). Thus, the variance to be explained is split up in a respondent part (level 1) and an interviewer part (level 2). This two-level model is applied to data collected in the Longitudinal Aging Study Amsterdam (LASA: 2838 respondents within 43 interviewers). The dependent variable is a scale indicating well-being (Center for Epidemiologic Studies Depression Scale): background variables on respondent level are age. sex. and self-perceived health. Interviewer variables are age, education, personality traits and social skills. Questionnaire Surreys, Response Process, Interviewer Influence, Multilevel Analyse.