Linking PIAAC Data to Individual Administrative Data: Insights from a German Pilot Project

Linking survey data to administrative data offers researchers many opportunities. In particular, it enables them to enrich survey data with additional information without increasing the burden on respondents. German PIAAC data on individual skills, for example, can be combined with administrative data on individual employment histories. However, as the linkage of survey data with administrative data records requires the consent of respondents, there may be bias in the linked dataset if only a subsample of respondents - for example, high-educated individuals - give their consent. The present chapter provides an overview of the pilot project about linking the German PIAAC data with individual administrative data. In a first step, we illustrate characteristics of the linkable datasets and describe the linkage process and its methodological challenges. In a second step, we provide an illustrative example of the use of the linked data and investigate how the skills assessed in PIAAC are associated with the linkage decision

Parametric bootstrap mean squared error of a small area multivariate EBLUP

© 2018, © 2018 Taylor & Francis Group, LLC. This article deals with mean squared error (MSE) estimation of a multivariate empirical best linear unbiased predictor (MEBLUP) under the unit-level multivariate nested-errors regression model for small area estimation via parametric bootstrap. A simulation study is designed to evaluate the performance of our algorithm and compare it with the univariate case bootstrap MSE which has been shown to be consistent to the true MSE. The simulation shows that, in line with the literature, MEBLUP provides unbiased estimates with lower MSE than EBLUP. We also provide a short empirical analysis based on real data collected from the U.S. Department of Agriculture

Measurement Equivalence in Sequential Mixed-Mode Surveys

Many surveys collect data using a mixture of modes administered in sequential order. Although the impacts of mixed-mode designs on measurement quality have been extensively studied, their impacts on the measurement quality of unobservable (or latent) constructs is still an understudied area of research. In particular, it is unclear whether latent constructs derived from multi-item scales are measured equivalently across different sequentially-administered modes—an assumption that is often made by analysts, but rarely tested in practice. In this study, we assess the measurement equivalence of several commonly-used multi-item scales collected in a sequential mixed-mode (Web-telephone-face-to-face) survey: the Age 25 wave of the Next Steps cohort study. After controlling for selection via an extensive data-driven weighting procedure, a multi-group confirmatory factor analysis was performed to assess measurement equivalence across the three modes. We show that cross-mode measurement equivalence is achieved for nearly all scales, with partial equivalence established for the remaining. Although measurement equivalence was achieved, some differences in the latent means were observed between the modes, particularly between the interviewer-administered and selfadministered modes. We conclude with a discussion of these findings, their potential causes, and implications for survey practice

Analysis of four studies in a comparative framework reveals: health linkage consent rates on British cohort studies higher than on UK household panel surveys

Background: A number of cohort studies and longitudinal household panel studies in Great Britain have asked for consent to link survey data to administrative health data. We explore commonalities and differences in the process of collecting consent, achieved consent rates and biases in consent with respect to socio-demographic, socio-economic and health characteristics. We hypothesise that British cohort studies which are rooted within the health sciences achieve higher consent rates than the UK household longitudinal studies which are rooted within the social sciences. By contrast, the lack of a specific health focus in household panel studies means there may be less selectivity in consent, in particular, with respect to health characteristics. Methods: Survey designs and protocols for collecting informed consent to health record linkage on two British cohort studies and two UK household panel studies are systematically compared. Multivariate statistical analysis is then performed on information from one cohort and two household panel studies that share a great deal of the data linkage protocol but vary according to study branding, survey design and study population. Results: We find that consent is higher in the British cohort studies than in the UK household panel studies, and is higher the more health-focused the study is. There are no systematic patterns of consent bias across the studies and where effects exist within a study or study type they tend to be small. Minority ethnic groups will be underrepresented in record linkage studies on the basis of all three studies. Conclusions: Systematic analysis of three studies in a comparative framework suggests that the factors associated with consent are idiosyncratic to the study. Analysis of linked health data is needed to establish whether selectivity in consent means the resulting research databases suffer from any biases that ought to be considered

The measurement of household consumption expenditures

Household-level data on consumer expenditures underpin a wide range of empirical research in modern economics, spanning micro-and macroeconomics. This research includes work on consumption and saving, on poverty and inequality, and on risk sharing and insurance. We review different ways in which such data can be collected or captured: traditional detailed budget surveys, less onerous survey procedures that might be included in more general surveys, and administrative or process data. We discuss the advantages and difficulties of each approach and suggest directions for future investigation. © 2014 by Annual Reviews. All rights reserved

Seasonal and annual fluxes of nutrients and organic matter from large rivers to the Arctic Ocean and surrounding seas

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Estuaries and Coasts 35 (2012): 369-382, doi:10.1007/s12237-011-9386-6.River inputs of nutrients and organic matter impact the biogeochemistry of arctic estuaries and the Arctic Ocean as a whole, yet there is considerable uncertainty about the magnitude of fluvial fluxes at the pan-arctic scale. Samples from the six largest arctic rivers, with a combined watershed area of 11.3 x 106 km2, have revealed strong seasonal variations in constituent concentrations and fluxes within rivers as well as large differences among the rivers. Specifically, we investigate fluxes of dissolved organic carbon, dissolved organic nitrogen, total dissolved phosphorus, dissolved inorganic nitrogen, nitrate, and silica. This is the first time that seasonal and annual constituent fluxes have been determined using consistent sampling and analytical methods at the pan arctic scale, and consequently provide the best available estimates for constituent flux from land to the Arctic Ocean and surrounding seas. Given the large inputs of river water to the relatively small Arctic Ocean, and the dramatic impacts that climate change is having in the Arctic, it is particularly urgent that we establish the contemporary river fluxes so that we will be able to detect future changes and evaluate the impact of the changes on the biogeochemistry of the receiving coastal and ocean systems.This work was supported by the National Science Foundation through grants OPP-0229302, OPP-0519840, OPP-0732522, and OPP-0732944. Additional support was provided by the U. S. Geological Survey (Yukon River) and the Department of Indian and Northern Affairs (Mackenzie River)

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

Sources of potential bias when combining routine data linkage and a national survey of secondary school-aged children: a record linkage study

Background Linking survey data to administrative records requires informed participant consent. When linkage includes child data, this includes parental and child consent. Little is known of the potential impacts of introducing consent to data linkage on response rates and biases in school-based surveys. This paper assessed: i) the impact on overall parental consent rates and sample representativeness when consent for linkage was introduced and ii) the quality of identifiable data provided to facilitate linkage. Methods Including an option for data linkage was piloted in a sub-sample of schools participating in the Student Health and Wellbeing survey, a national survey of adolescents in Wales, UK. Schools agreeing to participate were randomized 2:1 to receive versus not receive the data linkage question. Survey responses from consenting students were anonymised and linked to routine datasets (e.g. general practice, inpatient, and outpatient records). Parental withdrawal rates were calculated for linkage and non-linkage samples. Multilevel logistic regression models were used to compare characteristics between: i) consenters and non-consenters; ii) successfully and unsuccessfully linked students; and iii) the linked cohort and peers within the general population, with additional comparisons of mental health diagnoses and health service contacts. Results The sub-sample comprised 64 eligible schools (out of 193), with data linkage piloted in 39. Parental consent was comparable across linkage and non-linkage schools. 48.7% (n = 9232) of students consented to data linkage. Modelling showed these students were more likely to be younger, more affluent, have higher positive mental wellbeing, and report fewer risk-related behaviours compared to non-consenters. Overall, 69.8% of consenting students were successfully linked, with higher rates of success among younger students. The linked cohort had lower rates of mental health diagnoses (5.8% vs. 8.8%) and specialist contacts (5.2% vs. 7.7%) than general population peers. Conclusions Introducing data linkage within a national survey of adolescents had no impact on study completion rates. However, students consenting to data linkage, and those successfully linked, differed from non-consenting students on several key characteristics, raising questions concerning the representativeness of linked cohorts. Further research is needed to better understand decision-making processes around providing consent to data linkage in adolescent populations

Global, regional, and national incidence of six major immune-mediated inflammatory diseases: findings from the global burden of disease study 2019

Background The causes for immune-mediated inflammatory diseases (IMIDs) are diverse and the incidence trends of IMIDs from specific causes are rarely studied. The study aims to investigate the pattern and trend of IMIDs from 1990 to 2019. Methods We collected detailed information on six major causes of IMIDs, including asthma, inflammatory bowel disease, multiple sclerosis, rheumatoid arthritis, psoriasis, and atopic dermatitis, between 1990 and 2019, derived from the Global Burden of Disease study in 2019. The average annual percent change (AAPC) in number of incidents and age standardized incidence rate (ASR) on IMIDs, by sex, age, region, and causes, were calculated to quantify the temporal trends. Findings In 2019, rheumatoid arthritis, atopic dermatitis, asthma, multiple sclerosis, psoriasis, inflammatory bowel disease accounted 1.59%, 36.17%, 54.71%, 0.09%, 6.84%, 0.60% of overall new IMIDs cases, respectively. The ASR of IMIDs showed substantial regional and global variation with the highest in High SDI region, High-income North America, and United States of America. Throughout human lifespan, the age distribution of incident cases from six IMIDs was quite different. Globally, incident cases of IMIDs increased with an AAPC of 0.68 and the ASR decreased with an AAPC of −0.34 from 1990 to 2019. The incident cases increased across six IMIDs, the ASR of rheumatoid arthritis increased (0.21, 95% CI 0.18, 0.25), while the ASR of asthma (AAPC = −0.41), inflammatory bowel disease (AAPC = −0.72), multiple sclerosis (AAPC = −0.26), psoriasis (AAPC = −0.77), and atopic dermatitis (AAPC = −0.15) decreased. The ASR of overall and six individual IMID increased with SDI at regional and global level. Countries with higher ASR in 1990 experienced a more rapid decrease in ASR. Interpretation The incidence patterns of IMIDs varied considerably across the world. Innovative prevention and integrative management strategy are urgently needed to mitigate the increasing ASR of rheumatoid arthritis and upsurging new cases of other five IMIDs, respectively. Funding The Global Burden of Disease Study is funded by the Bill and Melinda Gates Foundation. The project funded by Scientific Research Fund of Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital (2022QN38)