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AbstractExisting studies have generally measured collective efficacy by combining survey respondents' ratings of their local area into an overall summary for each neighborhood. Naturally, this approach results in a substantive focus on the variation in average levels of collective efficacy between neighborhoods. In this article, we focus on the variation in consensus of collective efficacy judgments. To account for differential consensus among neighborhoods, we use a mixed‐effects location‐scale model, with variability in the consensus of judgments treated as an additional neighborhood‐level random effect. Our results show that neighborhoods in London differ, not just in their average levels of collective efficacy but also in the extent to which residents agree with one another in their assessments. In accord with findings for U.S. cities, our results show that consensus in collective efficacy assessments is affected by the ethnic composition of neighborhoods. Additionally, we show that heterogeneity in collective efficacy assessments is consequential, with higher levels of criminal victimization, worry about crime, and risk avoidance behavior in areas where collective efficacy consensus is low.

Contextual theories of political behaviour assert that the contexts in which people live influence their political beliefs and vote choices. Most studies, however, fail to distinguish contextual influence from self-selection of individuals into areas. This article advances understanding of this controversy by tracking the left–right position and party identification of thousands of individuals over an eighteen-year period in England before and after residential moves across areas with different political orientations. There is evidence of both non-random selection into areas and assimilation of new entrants to the majority political orientation. These effects are contingent on the type of area an individual moves into and contextual effects are weak and dominated by the larger effect of self-selection into areas.

Contextual theories of political behaviour assert that the contexts in which people live influence their political beliefs and vote choices. Most studies, however, fail to distinguish contextual influence from self-selection of individuals into areas. This article advances understanding of this controversy by tracking the left–right position and party identification of thousands of individuals over an eighteen-year period in England before and after residential moves across areas with different political orientations. There is evidence of both non-random selection into areas and assimilation of new entrants to the majority political orientation. These effects are contingent on the type of area an individual moves into and contextual effects are weak and dominated by the larger effect of self-selection into areas.

Contextual theories of political behaviour assert that the contexts in which people live influence their political beliefs and vote choices. Most studies, however, fail to distinguish contextual influence from self-selection of individuals into areas. This article advances understanding of this controversy by tracking the left–right position and party identification of thousands of individuals over an eighteen-year period in England before and after residential moves across areas with different political orientations. There is evidence of both non-random selection into areas and assimilation of new entrants to the majority political orientation. These effects are contingent on the type of area an individual moves into and contextual effects are weak and dominated by the larger effect of self-selection into areas.

Abstract
Effective evaluation of data quality between data collected in different modes is complicated by the confounding of selection and measurement effects. This study evaluates the utility of propensity score matching (PSM) as a method that has been proposed as a means of removing selection effects across surveys conducted in different modes. Our results show large differences in estimates for the same variables between parallel face-to-face and online surveys, even after matching on standard demographic variables. Moreover, discrepancies in estimates are still present after matching between surveys conducted in the same (online) mode, where differences in measurement properties can be ruled out a priori. Our findings suggest that PSM has substantial limitations as a method for separating measurement and selection differences across modes and should be used only with caution.

Abstract
Survey researchers have consistently found that interviewers make a small but systematic contribution to variability in response times. However, we know little about what the characteristics of interviewers are that lead to this effect. In this study, we address this gap in understanding by linking item-level response times from wave 3 of the UK Household Longitudinal Survey (UKHLS) to data from an independently conducted survey of interviewers. The linked data file contains over three million records and has a complex, hierarchical structure with response latencies nested within respondents and questions, which are themselves nested within interviewers and areas. We propose the use of a cross-classified mixed-effects location scale model to allow for the decomposition of the joint effects on response times of interviewers, areas, questions, and respondents. We evaluate how interviewer demographic characteristics, personality, and attitudes to surveys and to interviewing affect the length of response latencies and present a new method for producing interviewer-specific intra-class correlations of response times. Hence, the study makes both methodological and substantive contributions to the investigation of response times.

Abstract
As citizens around the world become ever more reluctant to respond to survey interview requests, incentives are playing an increasingly important role in maintaining response rates. In face-to-face surveys, interviewers are the key conduit of information about the existence and level of any incentive offered and, therefore, potentially moderate the effectiveness with which an incentive translates nonproductive addresses into interviews. Yet, while the existing literature on the effects of incentives on response rates is substantial, little is currently known about the role of interviewers in determining whether or not incentives are effective. In this article, we apply multilevel models to three different face-to-face interview surveys from the United Kingdom, which vary in their sample designs and incentive levels, to assess whether some interviewers are more successful than others in using incentives to leverage cooperation. Additionally, we link the response outcome data to measures of interviewer characteristics to investigate whether interviewer variability on this dimension is systematically related to level of experience and demographic characteristics. Our results show significant and substantial variability between interviewers in the effectiveness of monetary incentives on the probability of cooperation across all three surveys. However, none of the interviewer characteristics considered are significantly associated with more or less successful interviewers.