American Sociological Association



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  1. The Constituents of Rapport in the Standardized Survey Interview

    The starting point of Garbarski, Schaeffer, and Dykema (this volume, pp. 1–38) is the important discussion of how “rapport” between an interviewer and a respondent in a standardized survey interview may benefit or harm (1) the quality of responses and (2) future survey participation. The authors adapt the concept of rapport to the context of standardized interviewing and to actors’ institutional roles by discerning two actor-specific concepts: the interviewer’s responsiveness and the respondent’s engagement.

  2. Interviewing Practices, Conversational Practices, and Rapport: Responsiveness and Engagement in the Standardized Survey Interview

    "Rapport" has been used to refer to a range of positive psychological features of an interaction, including a situated sense of connection or affiliation between interactional partners, comfort, willingness to disclose or share sensitive information, motivation to please, and empathy. Rapport could potentially benefit survey participation and response quality by increasing respondents’ motivation to participate, disclose, or provide accurate information. Rapport could also harm data quality if motivation to ingratiate or affiliate causes respondents to suppress undesirable information.

  3. Response to Comments on "Interviewing Practices, Conversational Practices, and Rapport: Responsiveness and Engagement in the Standardized Survey Interview"

    Response to Comments on "Interviewing Practices, Conversational Practices, and Rapport: Responsiveness and Engagement in the Standardized Survey Interview"
  4. Eliciting Frontstage and Backstage Talk with the Iterated Questioning Approach

    This article advances interviewing methods by introducing the authors’ original contribution: the iterated questioning approach (IQA). This interviewing technique augments the interviewer’s methodological arsenal by exploiting insights from symbolic interactionism, particularly Goffman’s concepts of frontstage and backstage. IQA consists of sequenced iterations of a baseline question designed to elicit multiple forms of talk.

  5. Assessing the Effectiveness of Anchoring Vignettes in Bias Reduction for Socioeconomic Disparities in Self-rated Health among Chinese Adults

    The authors investigate how reporting heterogeneity may bias socioeconomic and demographic disparities in self-rated general health, a widely used health indicator, and how such bias can be adjusted by using new anchoring vignettes designed in the 2012 wave of the China Family Panel Studies (CFPS). The authors find systematic variation by sociodemographic characteristics in thresholds used by respondents in rating their general health status. Such threshold shifts are often nonparallel in that the effect of a certain group characteristic on the shift is stronger at one level than another.

  6. The KISS Principle in Survey Design: Question Length and Data Quality

    Writings on the optimal length for survey questions are characterized by a variety of perspectives and very little empirical evidence. Where evidence exists, support seems to favor lengthy questions in some cases and shorter ones in others. However, on the basis of theories of the survey response process, the use of an excessive number of words may get in the way of the respondent’s comprehension of the information requested, and because of the cognitive burden of longer questions, there may be increased measurement errors.

  7. Generalizing the Network Scale-up Method: A New Estimator for the Size of Hidden Populations

    The network scale-up method enables researchers to estimate the sizes of hidden populations, such as drug injectors and sex workers, using sampled social network data. The basic scale-up estimator offers advantages over other size estimation techniques, but it depends on problematic modeling assumptions. The authors propose a new generalized scale-up estimator that can be used in settings with nonrandom social mixing and imperfect awareness about membership in the hidden population.

  8. The Graphical Structure of Respondent-driven Sampling

    Respondent-driven sampling (RDS) is a chain-referral method for sampling members of hidden or hard-to-reach populations, such as sex workers, homeless people, or drug users, via their social networks. Most methodological work on RDS has focused on inference of population means under the assumption that subjects’ network degree determines their probability of being sampled. Criticism of existing estimators is usually focused on missing data: the underlying network is only partially observed, so it is difficult to determine correct sampling probabilities.

  9. Robust Estimation of Inequality from Binned Incomes

    Researchers often estimate income inequality by using data that give only the number of cases (e.g., families or households) whose incomes fall in "bins" such as $ 0 to $9,999, $10,000 to $14,999, . . . , ≥$200,000. We find that popular methods for estimating inequality from binned incomes are not robust in small samples, where popular methods can produce infinite, undefined, or arbitrarily large estimates. To solve these and other problems, we develop two improved estimators: a robust Pareto midpoint estimator (RPME) and a multimodel generalized beta estimator (MGBE).

  10. Goodness-of-fit of Multilevel Latent Class Models for Categorical Data

    In the context of multilevel latent class models, the goodness-of-fit depends on multiple aspects, among which are two local independence assumptions. However, because of the lack of local fit statistics, the model and any issues relating to model fit can only be inspected jointly through global fit statistics. This hinders the search for model improvements, as it cannot be determined where misfit originates and which of the many model adjustments may improve its fit.