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A person has nonseparable preferences when her preference on an issue depends on the outcome of other issues. A model of survey responses in which preferences are measured with error implies that responses will change depending on the order of questions and vary over time when respondents have nonseparable preferences. Results from two survey experiments confirm that changes in survey responses due to question order are explained by nonseparable preferences but not by the respondent's level of political information, partisanship, or ideology.

This case study is based on the research project I undertook for my PhD dissertation. The goal of the project was to quantitatively analyze the effects of socially constructed identities on the political attitudes and behavior of sexual minorities in the United States. Achieving this goal necessitated the collection of individual-level data about the identity and political experiences of sexual minorities. This case study focuses on the construction of an online survey instrument and its administration to a representative sample of more than 1,200 lesbian, gay, bisexual, and transgender (LGBT) people in the United States. The incorporation of intersectional theory into the research design allowed me to robustly measure heterogeneity within a group often considered politically and behaviorally homogeneous. My experience highlights the difficulties of LGBT survey research, the complexity of quantitative intersectional analysis, and the imperative of survey researchers to justify the use of categorical indicators in survey instruments to prevent the continued marginalization of intersectional identities in survey research.

We describe methods of combining administrative and survey data to improve the measurement of income. We begin by decomposing the total survey error in the mean of survey reports of dollars received from a government transfer program. We decompose this error into three parts, generalized coverage error (which combines coverage and unit non-response error and any error from weighting), item non-response or imputation error, and measurement error. We then discuss these three sources of error in turn and how linked administrative and survey data can assess and reduce each of these sources. We then illustrate the potential of linked data by showing how using linked administrative variables improves the measurement of income and poverty in the Current Population Survey, focusing on the substitution of administrative for survey data for three government transfer programs. Finally, we discuss how one can examine the accuracy of the underlying links used in the combined data.

Trust is a field of research in social sciences that has complex, well-developed theoreticalapproaches, but its empirical tools are less precisely grounded. The most common survey toolfor measuring generalized trust is a formula often referred to in the literature as "standard"trust question, which reads as follows: "Generally speaking, would you say that most people canbe trusted or that you need to be very careful in dealing with people?" The aim of the paper is toexamine this standard survey item along the dimensions of reliability and validity. In our analysis,we use Hungarian data obtained from various international surveys. Our results indicate seriousvalidity problems, as the standard question shows only weak linkage with additional variables,which, based on the conceptual background, should be in a close relationship with trust.KEYWORDS: trust, generalized trust, survey methods, reliability, validity

Basic principles -- Surveys and societies -- Planning a survey -- Measurement -- Sampling -- Data collection -- Preparing data for use -- Assessing and improving data quality -- Further issues

State departments of transportation are investing suabstantial time and effort in developing performance measurement systems to help manage more effectively in a period of unprecedented change. Based on information obtained from a mail survey, review of documents, and follow-up telephone interviews, this article examines conventional and leading-edge approaches to performance measurement in these large public works agencies, which have often been characterized as being "data rich/information poor." Compared with the traditional operations-oriented management information systems, the new generation of performance measures emerging in departments of transportation tend to be more outcome-oriented and more strategically focused, with much greater emphasis on quality and customer service.