Is Success in Obtaining Contact and Cooperation Correlated With the Magnitude of Interviewer Variance?

Brunton‐Smith, Ian; Sturgis, Patrick; Williams, Joel E.

doi:10.1093/poq/nfr067

Cited by 17 publications

(15 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For those aged sixty-five and older, the effect of ethnic segregation within neighbourhoods has a strong positive effect on social cohesion. We can obtain an intuitive feel for the substantive importance of these coefficients by comparing fitted values with those produced from variables with a more natural and intuitively understandable metric (Brunton-Smith, Sturgis, and Williams 2012). For example, using fitted values from models 5 and 6 in Table 1, we find that for individuals aged between fifteen and seventeen, moving from the tenth to the ninetieth percentile on the neighbourhood ethnic diversity index leads to a predicted increase in social cohesion of 0.24, holding all other variables in the model constant.…”

Section: Resultsmentioning

confidence: 99%

Ethnic diversity, segregation and the social cohesion of neighbourhoods in London

Sturgis

Brunton‐Smith

Kuha

et al. 2013

Ethnic and Racial Studies

185

105

View full text Add to dashboard Cite

The question of whether and how ethnic diversity affects the social cohesion of communities has become an increasingly prominent and contested topic of academic and political debate. In this paper we focus on a single city: London. As possibly the most ethnically diverse conurbation on the planet, London serves as a particularly suitable test-bed for theories about the effects of ethnic heterogeneity on prosocial attitudes. We find neighbourhood ethnic diversity in London to be positively related to the perceived social cohesion of neighbourhood residents, once the level of economic deprivation is accounted for. Ethnic segregation within neighbourhoods, on the other hand, is associated with lower levels of perceived social cohesion. Both effects are strongly moderated by the age of individual residents: diversity has a positive effect on social cohesion for young people but this effect dissipates in older age groups; the reverse pattern is found for ethnic segregation.

show abstract

Section: Resultsmentioning

confidence: 99%

Ethnic diversity, segregation and the social cohesion of neighbourhoods in London

Sturgis

Brunton‐Smith

Kuha

et al. 2013

Ethnic and Racial Studies

185

105

View full text Add to dashboard Cite

show abstract

“…More recently, however, researchers have tended to estimate interviewer ρ by using cross‐classified mixed effects models with random effects specified for interviewers and areas and which include interviewer, area and respondent level controls to adjust for non‐random allocation of respondents to interviewers (Durrant et al ., ; Turner et al ., ). As with any procedure which relies on statistical control, this approach cannot guarantee unbiased estimates but comparisons between estimates by using this approach and those from randomized designs show similar patterns of effects (Brunton‐Smith et al ., ).…”

Section: Introductionmentioning

confidence: 97%

Detecting and Understanding Interviewer Effects on Survey data by using a Cross-classified Mixed Effects Location–scale Model

Brunton‐Smith

Sturgis

Leckie

2016

Journal of the Royal Statistical Society Series A: Statistics in Society

View full text Add to dashboard Cite

Summary. We propose a cross-classified mixed effects location-scale model for the analysis of interviewer effects in survey data. The model extends the standard two-way cross-classified random-intercept model (respondents nested in interviewers crossed with areas) by specifying the residual variance to be a function of covariates and an additional interviewer random effect. This extension provides a way to study interviewers' effects on not just the 'location' (mean) of respondents' responses, but additionally on their 'scale' (variability). It therefore allows researchers to address new questions such as 'Do interviewers influence the variability of their respondents' responses in addition to their average, and if so why?'. In doing so, the model facilitates a more complete and flexible assessment of the factors that are associated with interviewer error. We illustrate this model by using data from wave 3 of the UK Household Longitudinal Survey, which we link to a range of interviewer characteristics measured in an independent survey of interviewers. By identifying both interviewer characteristics in general, but also specific interviewers who are associated with unusually high or low or homogeneous or heterogeneous responses, the model provides a way to inform improvements to survey quality.

show abstract

“…Existing studies have shown that respondents to telephone surveys are more likely to satisfice, less engaged and cooperative, more suspicious about the interview process and confidentiality, and more likely to present socially desirable responses (Beland and St. Pierre 2008;Holbrook et al 2003). Interviewers in face-to-face surveys can address these concerns in a more personal manner, and differential ability to address these concerns and/or issues could impact both decisions to participate and measurement errors in a differential manner across interviewers, resulting in greater interviewer variance (Brunton-Smith et al 2012). Differences in nonresponse error variance across interviewers may be one of the primary contributors to the unexpected interviewer variance in more objective survey items (such as age) that has been reported previously for face-to-face surveys, given that the interviewer plays a larger and more personal role in securing cooperation and establishing rapport with the respondent in these surveys.…”

Section: Introductionmentioning

confidence: 99%

“Interviewer” Effects in Face-to-Face Surveys: A Function of Sampling, Measurement Error, or Nonresponse?

West¹,

Kreuter²,

Jaenichen³

2013

Journal of Official Statistics

View full text Add to dashboard Cite

Recent research has attempted to examine the proportion of interviewer variance that is due to interviewers systematically varying in their success in obtaining cooperation from respondents with varying characteristics (i.e., nonresponse error variance), rather than variance among interviewers in systematic measurement difficulties (i.e., measurement error variance) -that is, whether correlated responses within interviewers arise due to variance among interviewers in the pools of respondents recruited, or variance in interviewer-specific mean response biases. Unfortunately, work to date has only considered data from a CATI survey, and thus suffers from two limitations: Interviewer effects are commonly much smaller in CATI surveys, and, more importantly, sample units are often contacted by several CATI interviewers before a final outcome (response or final refusal) is achieved. The latter introduces difficulties in assigning nonrespondents to interviewers, and thus interviewer variance components are only estimable under strong assumptions. This study aims to replicate this initial work, analyzing data from a national CAPI survey in Germany where CAPI interviewers were responsible for working a fixed subset of cases.

show abstract

Is Success in Obtaining Contact and Cooperation Correlated With the Magnitude of Interviewer Variance?

Cited by 17 publications

References 34 publications

Ethnic diversity, segregation and the social cohesion of neighbourhoods in London

Ethnic diversity, segregation and the social cohesion of neighbourhoods in London

Detecting and Understanding Interviewer Effects on Survey data by using a Cross-classified Mixed Effects Location–scale Model

“Interviewer” Effects in Face-to-Face Surveys: A Function of Sampling, Measurement Error, or Nonresponse?

Contact Info

Product

Resources

About