99 research outputs found
Benford's Law as an Instrument for Fraud Detection in Surveys Using the Data of the Socio-Economic Panel (SOEP)
Multi-source statistics:Basic situations and methods
Many National Statistical Institutes (NSIs), especially in Europe, are moving from single‐source statistics to multi‐source statistics. By combining data sources, NSIs can produce more detailed and more timely statistics and respond more quickly to events in society. By combining survey data with already available administrative data and Big Data, NSIs can save data collection and processing costs and reduce the burden on respondents. However, multi‐source statistics come with new problems that need to be overcome before the resulting output quality is sufficiently high and before those statistics can be produced efficiently. What complicates the production of multi‐source statistics is that they come in many different varieties as data sets can be combined in many different ways. Given the rapidly increasing importance of producing multi‐source statistics in Official Statistics, there has been considerable research activity in this area over the last few years, and some frameworks have been developed for multi‐source statistics. Useful as these frameworks are, they generally do not give guidelines to which method could be applied in a certain situation arising in practice. In this paper, we aim to fill that gap, structure the world of multi‐source statistics and its problems and provide some guidance to suitable methods for these problems
The National Children's Study 2014: Commentary on a Recent National Research Council/Institute of Medicine Report
How to survey displaced workers in Switzerland ? Sources of bias and ways around them
Studying career outcomes after job loss is challenging because individually displaced worker form a self-selected group. Indeed, the same factors causing the workers to lose their jobs, such as lack of motivation, may also reduce their re-employment prospects. Using data from plant closures where all workers were displaced irrespective of their individual characteristics offers a way around this selection bias. There is no systematic data collection on workers displaced by plant closure in Switzerland. Accordingly, we conducted our own survey on 1200 manufacturing workers who had lost their job 2 years earlier. The analysis of observational data gives rise to a set of methodological challenges, in particular nonresponse bias. Our survey addressed this issue by mixing data collection modes and repeating contact attempts. In addition, we combined the survey data with data from the public unemployment register to examine the extent of nonresponse bias. Our analysis suggests that some of our adjustments helped to reduce bias. Repeated contact attempts increased the response rate, but did not reduce nonresponse bias. In contrast, using telephone interviews in addition to paper questionnaires helped to substantially improve the participation of typically underrepresented subgroups. However, the survey respondents still differ from nonrespondents in terms of age, education and occupation. Interestingly, these differences have no significant impact on the substantial conclusion about displaced workers' re-employment prospects
Health status of the advanced elderly in six european countries: results from a representative survey using EQ-5D and SF-12
<p>Abstract</p> <p>Background</p> <p>Due to demographic change, the advanced elderly represent the fastest growing population group in Europe. Health problems tend to be frequent and increasing with age within this cohort.</p> <p>Aims of the study</p> <p>To describe and compare health status of the elderly population in six European countries and to analyze the impact of socio-demographic variables on health.</p> <p>Methods</p> <p>In the European Study of the Epidemiology of Mental Disorders (ESEMeD), representative non-institutionalized population samples completed the EQ-5D and Short Form-12 (SF-12) questionnaires as part of personal computer-based home interviews in 2001-2003. This study is based on a subsample of 1659 respondents aged ≥ 75 years from Belgium (n = 194), France (n = 168), Germany (n = 244), Italy (n = 317), the Netherlands (n = 164) and Spain (n = 572). Descriptive statistics, bivariate- (chi-square tests) and multivariate methods (linear regressions) were used to examine differences in population health.</p> <p>Results</p> <p>68.8% of respondents reported problems in one or more EQ-5D dimensions, most frequently pain/discomfort (55.2%), followed by mobility (50.0%), usual activities (36.6%), self-care (18.1%) and anxiety/depression (11.6%). The proportion of respondents reporting any problems increased significantly with age in bivariate analyses (age 75-79: 65.4%; age 80-84: 69.2%; age ≥ 85: 81.1%) and differed between countries, ranging from 58.7% in the Netherlands to 72.3% in Italy. The mean EQ VAS score was 61.9, decreasing with age (age 75-79: 64.1; age 80-84: 59.8; age ≥ 85: 56.7) and ranging from 60.0 in Italy to 72.9 in the Netherlands. SF-12 derived Physical Component Summary (PCS) and Mental Component Summary (MCS) scores varied little by age and country. Age and low educational level were associated with lower EQ VAS and PCS scores. After controlling for socio-demographic variables and reported EQ-5D health states, mean EQ VAS scores were significantly higher in the Netherlands and Belgium, and lower in Germany than the grand mean.</p> <p>Conclusions</p> <p>More than two thirds of the advanced elderly report impairment of health status. Impairment increases rapidly with age but differs considerably between countries. In all countries, health status is significantly associated with socio-demographic variables.</p
Rare Exonic Minisatellite Alleles in MUC2 Influence Susceptibility to Gastric Carcinoma
BACKGROUND: Mucins are the major components of mucus and their genes share a common, centrally-located region of sequence that encodes tandem repeats. Mucins are well known genes with respect to their specific expression levels; however, their genomic levels are unclear because of complex genomic properties. In this study, we identified eight novel minisatellites from the entire MUC2 region and investigated how allelic variation in these minisatellites may affect susceptibility to gastrointestinal cancer. METHODOLOGY/PRINCIPLE FINDINGS: We analyzed genomic DNA from the blood of normal healthy individuals and multi-generational family groups. Six of the eight minisatellites exhibited polymorphism and were transmitted meiotically in seven families, following Mendelian inheritance. Furthermore, a case-control study was performed that compared genomic DNA from 457 cancer-free controls with DNA from individuals with gastric (455), colon (192) and rectal (271) cancers. A statistically significant association was identified between rare exonic MUC2-MS6 alleles and the occurrence of gastric cancer: odds ratio (OR), 2.56; 95% confidence interval (CI), 1.31-5.04; and p = 0.0047. We focused on an association between rare alleles and gastric cancer. Rare alleles were divided into short (40, 43 and 44) and long (47, 50 and 54), according to their TR (tandem repeats) lengths. Interestingly, short rare alleles were associated with gastric cancer (OR = 5.6, 95% CI: 1.93-16.42; p = 0.00036). Moreover, hypervariable MUC2 minisatellites were analyzed in matched blood and cancer tissue from 28 patients with gastric cancer and in 4 cases of MUC2-MS2, minisatellites were found to have undergone rearrangement. CONCLUSIONS/SIGNIFICANCE: Our observations suggest that the short rare MUC2-MS6 alleles could function as identifiers for risk of gastric cancer. Additionally, we suggest that minisatellite instability might be associated with MUC2 function in cancer cells
Response Error in a Web Survey and a Mailed Questionnaire: The Role of Cognitive Functioning
Estimating error rates in an administrative register and survey questions using a latent class model
Administrative data obtained from government registers provide a wealth of potential for the social sciences. Administrative registers may contain considerable measurement errors, including definition, reporting, timing, processing, editing, linkage, and coverage errors. This chapter explores how to estimate the extent of measurement errors in both administrative register data and survey answers. It demonstrates one approach to doing so: latent variable modeling. Modeling these mode effects allows for the identification of both random classification errors and method effects without the need for multiple “traits” (true values). It could therefore be termed a “single-trait-multimethod” (STMM) approach. The chapter describes the data on neighborhood of residence obtained from a survey and an important Dutch official administrative register, and then details the latent class model built to estimate classification error rates in these measures. The costs of full-scale audits compared with latent variable modeling are gigantic, meaning that a small inaccuracy still leaves latent variable modeling an attractive alternative
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