Search

Interviewer characteristics are usually assumed fixed over the fieldwork period. The number of sample units that require the interviewers’ attention, however, can vary strongly over the fieldwork period. Different workload levels produce different constraints on the time interviewers have available to contact, recruit and interview each target respondent, and may also induce different motivational effects on interviewers’ behavior as they perform their different tasks. In this article we show that fine-grained, time-varying operationalizations of project-specific workload can be useful to explain differences in interviewers’ field efforts and achieved response outcomes over the fieldwork period. We derive project-specific workload for each interviewer on each day of fieldwork in two rounds of the European Social Survey in Belgium from contact history and assignment paradata. Project-specific workload is measured as (1) the number of sample units which have been and remain assigned on any day t (assigned case workload), and (2) the number of sample units for which interviewer activity has started and not yet ceased on any day t (active case workload). Capturing temporal variation in interviewers’ workloads in a direct way, the time-varying operationalizations, are better predictors than are the interviewer-level operationalizations of typical (active or potential) workload that are derived from them, as well as the traditional total-count workload operationalization.

A growing body of literature points to the possibilities offered by postsurvey interviewer observations as a source of paradata to obtain insights into data quality. However, their utility in predicting actual behavior of respondents has attracted limited scholarly attention so far. Using data from Round 7 of the European Social Survey, we aim to clarify the relationship between interviewer observations and response styles (straightlining, item nonresponse, use of middle and extreme categories). We contribute to previous research by empirically verifying whether interviewer observations in face-to-face interviews can be effectively used as accurate predictors of data quality. Findings suggest that interviewers’ assessments of response behavior to some extent reflect response styles and can potentially be a valuable tool for the evaluation and improvement of survey data quality, although this seems mainly restricted to the most overt (i.e., easily observable) response styles.

The proportion of elderly people in general population samples is increasing. Therefore, it is becoming more important to pay special attention to older respondents when assessing the quality of data. The main hypothesis of the current article is that interviewer effects are higher in the older age-group. We use data collected in 13 countries during Round 7 of the European Social Survey. The results support the supposition that older respondents tend to need more clarification, are more prone to misunderstand the questions, and are likely to have longer interviews. In line with the expectations, we also observe that among older respondents, particularly those aged 71 and above, interviewer effects are more common than among younger respondents.

Purpose In survey methodology, it is well-known that interviewers can have an impact on the registered answers. This paper aims to focus on one type of interviewer effect that arises from the differences between interviewers in the systematic effects of each interviewer on the answers. In the first case, the authors evaluate interviewer effects on the measurement of alcohol consumption in European countries. The second case is about the interviewer effects on the respondents’ tendency to (non)differentiate their responses and the consequences of this response style for the correlation between variables. Design/methodology/approach The interviewer effects are evaluated by means of interviewer variance analysis. Because respondents are nested within interviewers, we can specify a two- or three-level random intercept model to calculate the proportion of variance explained by the interviewers. Data from the seventh round of the European Social Survey are used. Findings The results in the first case show that the substantive conclusions about the effect of gender and education on the alcohol measures continue to hold when interviewer effects are taken into account. The results of the second case make clear that interviewer effects on attitudinal questions are considerable. There is also a significant effect of the interviewers on the degree that respondents differentiate their responses. The results also illustrate that correlations between attitudinal variables are influenced. This also implies that the results of statistical procedures using a correlation or covariance matrix can be strongly influenced by the tendency to (non)differentiate and the interviewers’ impact on this tendency. Originality/value The results clearly demonstrate that there are considerable differences between countries concerning the impact of the interviewers on substantive variables. Cross-national differences are striking and the importance and necessity to evaluate interviewer effects in a cross-national survey becomes clear.

Adaptive and responsive survey designs rely on monitoring indicators based on paradata. This process can better inform fieldwork management if the indicators are paired with a benchmark, which relies on empirical information collected in the first phase of the fieldwork or, for repeated or longitudinal surveys, in previous rounds or waves. We propose the “fieldwork power” (fieldwork production per time unit) as an indicator for monitoring, and we simulate this for the European Social Survey (ESS) Round 7 in Belgium and in the Czech Republic. We operationalize the fieldwork power as the weekly number of completed interviews and of contacts, the ratio of the number of completed interviews to the number of contact attempts and to the number of refusals. We use a repeated measurement multilevel model, with surveys in the previous rounds of the European Social Survey as the macro level and the weekly fieldwork power as repeated measurements to create benchmarks. We also monitor effort and data quality metrics. The results show how problems in the fieldwork evolution can be detected by monitoring the fieldwork power and by comparing it with the benchmarks. The analysis also proves helpful regarding post-survey fieldwork evaluation, and links effort, productivity, and data quality. ispartof: Journal of Official Statistics vol:33 issue:3 pages:659-686 status: published

Interviewer characteristics affect nonresponse and measurement errors in face-to-face surveys. Some studies have shown that mismatched sociodemographic characteristics – for example gender – affect people’s behaviour when interacting with an interviewer at the door and during the survey interview, resulting in more nonresponse. We investigate the effect of sociodemographic (mis)matching on nonresponse in two successive rounds of the European Social Survey in Belgium. As such, we replicate the analyses of the effect of (mis)matching gender and age on unit nonresponse on the one hand, and of gender, age and education level(mis)matching on item nonresponse on the other hand. Recurring effects of sociodemographic (mis)match are found for both unit and item nonresponse. ispartof: Social Science Research vol:67 pages:229-238 ispartof: location:United States status: published

Suitable auxiliary data is important in order to assess the potentially detrimental effects of nonresponse on survey estimates. Whereas sufficient individual-level auxiliary data is rarely available, aggregated data is often quite readily accessible. We investigate whether municipality-level data from official administrative registries is useful to explain and predict individuals’ survey response outcomes in two rounds of the European Social Survey (ESS) in Belgium. This study was prompted by the recent publication of the 2011 Belgian Census. This is the first Belgian census produced by linking various national administrative databases instead of a nationwide survey. It offers free and easy access to a broad range of data at the municipality level. We find no consistent results in the two rounds of the ESS, and the overall usefulness of aggregated data appears limited. Individual-level data available from other auxiliary sources is more strongly and more consistently related to survey response outcomes. Nonresponse analyses in the ESS and other surveys would benefit from access to individual-level administrative registry data, but as this is usually restricted, alternative auxiliary data sources such as interviewer observations will need to suffice. ispartof: Statistical Journal of the IAOS vol:33 issue:3 pages:645-659 status: published

© Statistics Sweden. In this article we examine the interviewer effects on different aspects of response styles, namely non-differentiation and straightlining, which in general refers to the tendency to provide the same answers to questions in a block of questions. According to research about response styles, the impact of the interviewer on this kind of response behavior is rare. Five blocks of items in the questionnaire in the sixth round of the European Social Survey (2012) are used in the analysis. These data also allow for an evaluation of the differences between countries in terms of non-differentiation and straightlining. Five different measurements of these aspects of response style are used in the analysis. To disentangle the impact of respondents and interviewers on these aspects of response style, a three-level random intercept model is specified. The results clearly show interviewer effects on the respondent’s tendency to select a response category that is the same as the response category for the previous item. In some countries the proportion of explained variance due to differences between interviewers is larger than the proportion of variance explained by the differences between respondents. ispartof: Journal of Official Statistics vol:33 issue:2 pages:409-426 status: published

Previous research shows that interviewers to some extent fail to expend the effort that is needed to collect high-quality survey data. We extend the idea of interviewer satisficing to a related task, in which the interviewers themselves answer survey questions. We hypothesize that interviewers who self-administer the questionnaire in a careless manner, also will not apply themselves fully to the task of administering survey interviews. Based on interviewer and respondent data from the sixth round of the European Social Survey in Belgium, we find support for some of the hypothesized associations between (suboptimal) response characteristics of interviewers in the “task as respondent” and the same (suboptimal) response characteristics recorded for their respondents, specifically with regard to interview speed, multiple response, and item nonresponse to the household income question. ispartof: Field Methods vol:29 issue:2 pages:140-153 status: published

Researchers have been looking for easily accessible and straightforwardly useable paradata and auxiliary data to improve survey data. Lately, there is also attention for the evaluation and validation of this external data, such as the assessment of the quality of interviewer-generated paradata. For these purposes, we investigated how useful Google Street View can be as auxiliary data and whether it allows us to assess the quality of interviewer observations on the houses and neighbourhoods of sample units. Additionally, we test whether Google Maps can inform us about the reachability of sample units and which data can predict non-response better. Although it is rather simple to use Google Maps and Street View in daily life, using it to code auxiliary data for surveys is more challenging than expected. Hence, this paper also offers a thorough discussion of the pitfalls of coding these auxiliary data as well as their current solutions., Survey Research Methods, Vol 11, No 3 (2017): Special Issue: Uses of Geographic Information Systems Tools in Survey Data Collection and Analysis

Unit nonresponse in the second wave of a panel survey is related to several respondent characteristics and to the interviewer of that wave. More striking is the effect of the interviewer of the first wave, who is not involved in the second interview. To analyze both interviewer effects simultaneously, the authors use a multilevel cross-classified model. In that analysis, the effect of the interviewer of the second wave almost disappears. That effect turns out to be at least partly spurious due to a correlation of both interviewer effects. The authors conclude that the interviewer of the first interview is very important regarding participation in the subsequent waves of a panel survey.

Caractéristique des interactions dans des expériences de l'utilisation des mots dans les questionnaires. Des résultats d'analyses de l'interaction interviewer-répondant sont peu utilisés dans les recherches sur la qualité des données. Avec une analyse d'interaction des entretiens enregistrés sur bande lors d'une expérience sur l'utilisation des mots dans des questionnaires. Il est possible de valider quelqu'unes des explications proposées pour certains effets produit par l'utilisation des mots. Des expériences sur l'étendue de l'échelle des réponses, l'utilisation explicite du filtre "pas d'opinion" , et l'utilisation des verbes "Interdire" ou "permettre" sont étudiées.

Understanding the dynamics of the data collection efficiency is key to developing strategies to increase response rates. In this article, we model data collection efficiency, specifically the number of completed interviews, number of contacts, ratio of completed interviews and contact attempts, and ratio of completed interviews and refusals, per time unit in the field. We apply this concept to the first six rounds of the European Social Survey. The time course of efficiency for the surveys–148 country-round combinations –is analyzed using a multilevel repeated measurement model, in which the weekly data collection efficiency measures are repeated measurements nested in the surveys. The results show that the data collection has four main characteristics over time: the initial efficiency, the initial increase in efficiency (speed), the initial decrease in speed, and the start of a tail when the efficiency levels off. The values of these characteristics seem to be linked with the length of the data collection period. Moreover, across all surveys, the analysis suggests that although most interviews are completed and most contacts established in the first weeks, the fieldwork becomes more productive at the end, with fewer but more successful contact attempts. The covariance parameters, however, show large differences between the surveys in terms of fieldwork dynamics. The results from a model with explanatory variables show that more interviewers, a good survey climate, and a non-individual frame type lead to a higher efficiency, while higher percentages of refusal conversion slow down its decrease. ispartof: Journal of Survey Statistics and Methodology vol:5 issue:2 pages:212-232 status: published

Le profil du répondant difficile à interviewer. Dans cet article nous faisons l'hypothèse que tout répondant est motivé à coopérer et qu'il a suffisamment de capacités cognitives et de communication pour remplir de façon adéquate le rôle de répondant. Une typologie des motivations et des capacités de répondants est construites avec l'analyse des classes latentes. Les classes de cette typologie peuvent être caractérisées par rapport à la difficulté ou la facilité à être interviewer des répondants. Il est possible de mettre la typologie en relations avec l'âge et l'éducation. La typologie est aussi liée à des aspects concrets du comportement de réponse: "utilisation du 'je ne sais pas"'. "réponses contradictoires", et "utilisation du style de réponse restreinte". Les répondants difficile-à-interviewer ont un niveau d'éducation plus bas, sont plus vieux, utilisant le "je ne sais pas" fréquemment et tendent à donner des réponses contradictoires.