Full presentations of many of the entries below have already been distributed to BMS subscribers and RC33 members over the BMS-RC33 distribution list
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Zerrin Aşan and H. Öztaş Ayhan (2013) Sampling Frame Coverage and Domain Adjustment Procedures for Internet Surveys. Quality and Quantity 47(6): 3031-42. The objective of this paper is to define and compare alternative sampling frames for the representative population coverage as a basis for sample selection in Internet surveys. The study aims to provide a methodology for domain weighting and adjustment procedures for free access Web surveys that are based on the restricted access surveys. Some basic variables can be proposed for the data adjustment, namely gender breakdown, age groups, and education groups. The application of our work consists of a first stage based on a Web survey by an email invitation (restricted access) and a second stage based on a voluntary participation Web survey (free access). An advertising company's registered customer list was taken as the sampling frame population for the first stage. This frame was an electronic email list of the population of registered customers. Two different types of questionnaires were loaded on the company's Internet Web site for a month each, for two independent rounds, for testing the visual aspects of the questionnaire design. The restricted access Internet survey design relies on probability selection procedures in this study. These results are used with the provided algorithms for the adjustment procedures of free access Web surveys. A new methodology is also proposed for the estimation and allocation of the population frame characteristics of adult Internet users by gender and age groups. The proposed alternative methodologies will be beneficial tools for future Web survey users.
Rubén Castro and Rubén Castro (2013) Inconsistent Respondents and Sensitive Questions. Field Methods 25(3): 283-98. This article focuses on respondents as the source of measurement error, regardless of the question being asked, interviewer effects, or other factors that influence survey quality. Some individuals simply provide poorer answers as a result of a behavior called “satisficing”. An especially troublesome case is that of sensitive questions, where misreporting is common. In the study reported here, a significant role was found for individual-level time consistency as a predictor for answers to sensitive questions related to children, sex, condoms, and HIV. Couples’ reports, where couple-level fixed effects (including the “true” answer) can be ruled out, confirm this result. Satisficing may have more of an impact on how individuals respond to sensitive questions than previously thought.
Richard Breen, Kristian Bernt Karlson and Anders Holm (2013) Total, Direct, and Indirect Effects in Logit and Probit Models. Sociological Methods and Research (42)2: 164-91. This article presents a method for estimating and interpreting total, direct, and indirect effects in logit or probit models. The method extends the decomposition properties of linear models to these models; it closes the much-discussed gap between results based on the “difference in coefficients” method and the “product of coefficients” method in mediation analysis involving nonlinear probability models; it reports effects measured on both the logit or probit scale and the probability scale; and it identifies causal mediation effects under the sequential ignorability assumption. We also show that while our method is computationally simpler than other methods, it always performs as well as, or better than, these methods. Further derivations suggest a hitherto unrecognized issue in identifying heterogeneous mediation effects in nonlinear probability models. We conclude the article with an application of our method to data from the National Educational Longitudinal Study of 1988.
Jennifer Merluzzi and Ronald S. Burt (2013) How Many Names are Enough? Identifying Network Affects with the Least Set of Listed Contacts. Social Networks 35(3): 331-37. How many names are enough to reveal network effects using a name generator for network analysis? We analyze network data from two large organizations varying in complexity. We ask how much the network association with achievement is strengthened by adding another name to the recorded list of each person's sociometric citations. We conclude that five names is the cost effective number of sociometric citations to record. The network association with achievement weakens quickly with fewer names, especially in the more clustered network.
Domenico De Stefano, Vittorio Fuccella, Maria Prosperina Vitale and Susanna Zaccarin (2013) The Use of Different Data Sources in the Analysis of Co-authorship Networks and Scientific Performance. Social Networks 35(3): 370-81. Scientific collaboration is usually derived from archival co-authorship data. Several data sources may be examined, but they all have advantages and disadvantages, especially when a specific discipline or community is of interest. The aim of this paper is to explore the effect of the use of three data sources – Web of Science, Current Index to Statistics and nationally funded research projects – on the analysis of co-authorship networks among Italian academic statisticians. Results provide evidence of our hypotheses on distinct collaboration patterns among statisticians, as well as distinct effects of scientist network positions on scientific performance, by both statistics subfield and data source.
J. Michael Brick (2013) Unit Nonresponse and Weighting Adjustments: A Critical Review. Journal of Official Statistics 29(3): 329-53. This article reviews unit nonresponse in cross-sectional household surveys, the consequences of the nonresponse on the bias of the estimates, and methods of adjusting for it. We describe the development of models for nonresponse bias and their utility, with particular emphasis on the role of response propensity modeling and its assumptions. The article explores the close connection between data collection protocols, estimation strategies, and the resulting nonresponse bias in the estimates. We conclude with some comments on the current state of the art and the need for future developments that expand our understanding of the response phenomenon. This article is followed by several “Discussion” texts by Olena Kaminska, by Phillip S. Kott, by Roderick J. Little, by Geert Loosveldt, and a “Rejoinder” by the author.
Tom Wells Nielsen, Justin T. Bailey and Michael W. Link Nielsen (2013) Filling the Void: Gaining a Better Understanding of Tablet-based Surveys. Survey Practice 6(1) at http://surveypractice.org/index.php/SurveyPractice/issue/view/22. “Survey respondents are increasingly attempting to take surveys on their mobile devices, whether researchers intend for this or not” (Cazes et al., 2011: 2). Approximately 50 percent of US adults own a smartphone (Nielsen, 2012; Smith, 2012), and approximately 20 percent of US adults own a tablet (Rainie, 2012). These trends have serious implications for online surveys, especially for online surveys that are designed specifically for a computer screen and not modified, or optimized, for the smaller screen typical of a mobile device. In this paper, we present results from tablet, computer, and smartphone administrations of a survey. For each, we examine three measures of survey taking behavior. Our main focus is on surveys taken with tablets and whether tablet survey administration is comparable to computer survey administration. Our results are preliminary, but instructive, since there is currently very little research on tablet administration of online surveys. However, with tablet ownership on the rise, understanding the effects of this survey mode will become exceedingly more important. Just as tablets have served to fill the void between the often difficult-to-read smartphone screen and the difficult-to-transport computer, tablets can also fill the void for mobile survey takers.
Jeannis McKinlay, Terry Tamara, Richard Heman-Ackah and Michael Price (2013) Video Interviewing: An Exploration of the Feasibility as a Mode of Survey Application. Survey Practice 6(1) at http://surveypractice.org/index.php/SurveyPractice/issue/view/22. To stay current with today’s constant evolution of technology, survey researchers continue to seek and modernize their data collection methods and offer alternative opportunities for respondents to participate. More traditional survey data collection modes such as mail, field, telephone, and Web surveys are becoming more limited as a result of advances in communications technology. These traditional data collection methods continue to be valuable, although innovative technologies in communication add promising features and capabilities. Researchers should continue to investigate new methodologies to gain further insight on the benefits and challenges of these new technologies.
