1,891 research outputs found

    ADRC-E: making a methodological impact

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    As part of its remit, the Administrative Data Research Centre for England is undertaking a programme of methodological research. In this paper I will describe a few examples from this programme including work on: guidance about the information that needs to be made available about the data linkage process by data providers, data linkers, analysts and researchers; a new approach to linkage based upon weights derived using a scaling algorithm; and the representativeness of surveys using a unique data set linking call record paradata from three UK social surveys to census auxiliary attribute information on sample households

    Models for combining aggregate-level administrative data in the absence of a traditional census

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    Administrative data sources are an important component of population data collection and they have been used in census data production in the Nordic countries since the 1960s. A large amount of information about the population is already collected in administrative data sources by governments. However, there are some challenges to using administrative data sources to estimate population counts by age, sex, and geographical area as well as population characteristics. The main limitation with the administrative data sources is that they only collect information from a subset of the population about specific events, and this may result in either undercoverage or overcoverage of the population. Another issue with the administrative data sources is that the information may not have the same quality for all population groups. This research aims to correct an inaccurate administrative data source by combining aggregate-level administrative data with more accurate marginal distributions or two-way marginal information from an auxiliary data source and produce accurate population estimates in the absence of a traditional census. The methodology developed is applied to estimate population counts by age, sex, and local authority area in England and Wales. The administrative data source used is the Patient Register which suffers from overcoverage, particularly for people between the ages of 20 and 50

    Knock-to-nudge methods to improve survey participation in the UK

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    Relevance & research question: data collection organisations are shifting toward new approaches, with social surveys undergoing significant design and implementation changes. Since the COVID-19 pandemic, agencies have increasingly moved to online data collection due to dwindling response rates and rising fieldwork costs. A key challenge for self-completion general population surveys is the absence of field interviewers to facilitate recruitment and participant retention. This research examines the UK survey landscape, aiming to identify recruitment methods for self-administered surveys, that can produce more representative samples of the general population.Methods & data: we present findings from an information request sent to the UK’s nine most important survey agencies. We collected information on surveys without field interviewers conducted between 2018 and early 2024, including publicly available technical and methodological reports and other survey materials, along with internal reports provided by the agencies. We processed and codified this information, building a spreadsheet containing 144 instances of 59 longitudinal and cross-sectional surveys, along with 227 communication materials. Results: the responses for the surveys in our dataset use 57% online, 38% paper, and 5% telephone modes. Most surveys (84%) offer incentives to participants, with 92% being monetary and only 33% given unconditionally. Response rates vary widely – household-based cross-sectional surveys tend to have lower response rates (81% at 30% response or lower) than individual-based ones (47% at 30% or lower). Longitudinal surveys generally have the highest response rates. While only 35% of reports assess sample representativeness, the general trend confirms that mixed-mode surveys yield more representative samples than single-mode surveys.Added value: to our knowledge, this review is the first coordinated effort to collate and summarise recruitment strategies for surveys without field interviewers in the UK. It covers sampling design, communication strategies and materials, incentivisation, fieldwork procedures, response rates, and report quality assessments. Our dataset provides insights into the current state of survey practice and helps identifying practices that might contribute towards higher response rates and sample representativeness

    Model-based inference for categorical survey data subject to non-ignorable non-response (with discussion)

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    We consider non-response models for a single categorical response with categorical covariates whose values are always observed. We present Bayesian methods for ignorable models and a particular non-ignorable model, and we argue that standard methods of model comparison are inappropriate for comparing ignorable and non-ignorable models. Uncertainty about ignorability of non-response is incorporated by introducing parameters describing the extent of non-ignorability into a pattern mixture specification and integrating over the prior uncertainty associated with these parameters. Our approach is illustrated using polling data from the 1992 British general election panel survey. We suggest sample size adjustments for surveys when non-ignorable non-response is expected
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