An investigation of response variance in sample surveys.

The dissertation considers response variance in sample surveys in the broader context of survey quality and survey error. Following a historical review of the evolution of both the terms and the concepts a brief overview is given of earlier research in the area. The principal content of the dissertation draws on investigations carried out by the author over the last thirty years. There are three separate strands of argument, each associated with a particular approach to the analysis. First there is the descriptive (simple diagnostic) orientation of establishing the circumstances under which (or if) response variance arises, the associated issue of how it should be accommodated in analysis - primarily estimating the impact on the variance of univariate statistics - and an assessment of its likely order of magnitude. Second, there is the model-assisted orientation which attempts to decompose the effects into their constituent parts: one approach is to incorporate the correlating source (cluster or interviewer for example) as a term or terms in other models that we are estimating so that the effect is incorporated into the estimation of these models; the other is to model the response error itself -- in doing this we are trying to decompose it into its constituent parts. Third, and most radical, is to view error as information. By conceptualizing the process that generated the errors as a substantive process rather than as a set of nuisance effects we can extract from the results of the process information about both the process and the subject matter. Any particular piece of analysis may include any combination of these three approaches. The dissertation draws on special studies incorporated into a number of major sample surveys. Two principal data sets are involved. The first arises from a special investigation of response error carried out in conjunction with the World Fertility Survey; the second is the reinterview data set from the Current Population Survey carried out by the US Bureau of the Census. Four other surveys are used; an absenteeism survey in Ireland, two cross-sectional British surveys (one on Noise Annoyance, the other on Physical Handicap), and a British panel survey (the British Household Panel Survey)

Public communication by research institutes compared across countries and sciences: building capacity for engagement or competing for visibility?

Leading academic institutions, governments, and funders of research across the world have spent the last few decades fretting publicly about the need for scientists and research organisations to engage more widely with the public and be open about their research. While a global literature asserts that public communication has changed from a virtue to a duty for scientists in many countries and disciplines, our knowledge about what research institutions are doing and what factors drive their 'going public' is very limited. Here we present the first cross-national study of N = 2,030 research institutes within universities and large scientific organisations in Brazil, Germany, Italy, Japan, the Netherlands, Portugal, the United Kingdom, and the United States of America. We find that institutes embrace communication with non-peers and do so through a variety of public events and traditional news media-less so through new media channels-and we find variation across countries and sciences, yet these are less evident than we expected. Country and disciplinary cultures contribute to the level of this communication, as do the resources that institutes make available for the effort; institutes with professionalised staff show higher activity online. Future research should examine whether a real change in the organisational culture is happening or whether this activity and resource allocation is merely a means to increase institutional visibility

A one dimension latent trait model to infer attitude from nonresponse for nominal data

This paper discusses the problem of missing values in attitude scales with categorical items. A simple method is proposed for obtaining information about attitude from nonresponse that is based on a latent variable model for nominal responses, The analysis treats nonresponse as a separate response category and then fits a latent variable model to the set of attitudinal items. The model coefficients provide information about the relationships between attitude and the probability of not responding to an item in the scale. Graphical methods based on response probabilities and posterior probabilities are used to reveal any relationship between attitude and missing values

Interviewers, Interviewer Continuity, and Panel Survey Nonresponse

interviewers, panel surveys, nonresponse, interviewer continuity, hierarchical models,

The Importance of Experimental Control in Testing the Impact of Interviewer Continuity on Panel Survey Nonresponse

interviewers, panel surveys, nonresponse, interviewer continuity, hierarchical models,

Mapping Cultural Participation in Chicago

Chicago is internationally known for the excellence of its major cultural institutions, which attract millions of visitors every year. What is the relationship between these organizations and the diverse population of Chicago? This study takes a significant step toward answering this question. Mapping Cultural Participation in Chicago is the first study of its kind of a major U.S. metropolitan area, and draws upon data – ticket purchases, subscriptions, donor lists – from Chicago’s 12 largest cultural organizations and 49 smaller organizations. This information was linked to census data on socio-economic status, race, and ethnicity to provide neighborhood-by-neighborhood maps of participation patterns. The study, funded by a grant from the Joyce Foundation, establishes the first benchmark to enable organizations to assess the future effectiveness of their diversity-building efforts among African-Americans and Latinos. Researchers, led by Professors Robert LaLonde and Colm O’Muircheartaigh of the Harris School of Public Policy Studies at the University of Chicago, found that Chicagoans are generally strong supporters of the largest institutions, with one household in six participating. The most engaged communities – where one household in two participates – are located in the North Shore suburbs and in the western suburb of River Forest. The lowest involvement in the major cultural institutions falls in the south and west sides and the near south suburbs. While race and ethnicity do play a role in lower participation rates among African-Americans and Latinos, "socio-economic factors are the strongest predictors of participation," says O'Muircheartaigh. Among other key findings: Smaller ethnic and diverse organizations successfully reach different audiences from those targeted by larger organizations. There are large, predominantly white areas, regardless of income, where participation rates are low. In the lowest participation communities, an average of one in twenty households was involved in the largest organizations

Correction: Public communication by research institutes compared across countries and sciences: Building capacity for engagement or competing for visibility?

[This corrects the article DOI: 10.1371/journal.pone.0235191.]