Linkage Error Research Articles

Optimized Coiled-Coil Interactions for Multiplexed Peptide-PAINT.

Super-resolution microscopy has revolutionized how researchers characterize samples in the life sciences in the last decades. Amongst methods employing single-molecule localization microscopy, DNA points accumulation for imaging in nanoscale topography (DNA-PAINT) is a relatively easy-to-implement method that uses the programmable and repetitive binding of dye-labeled DNA imager strands to their respective docking strands. Recently developed Peptide-PAINT replaces the interaction of oligonucleotides by short coiled-coil peptide sequences leading to an improved labeling scheme by reducing linkage errors to target proteins. However, only one coiled-coil pair is currently available for Peptide-PAINT, preventing multiplexed imaging. In this study, the initial Peptide-PAINT E/K coil is improved by modifying its length for optimized binding kinetics leading to improved localization precisions. Additionally, an orthogonal P3/P4 coil pair is introduced, enabling 2-plex Peptide-PAINT imaging and benchmarking its performance and orthogonality using single-molecule and DNA origami assays. Finally, the P3/P4 peptide pair is used to image the human epidermal growth factor receptors 2 (ErbB2/Her2) in 2D and 3D at the single receptor level using genetically encoded peptide tags.

Generation of concise 3D building model from dense meshes by extracting and completing planar primitives

AbstractThe generation of a concise building model has been and continues to be a challenge in photogrammetry and computer graphics. The current methods typically focus on the simplicity and fidelity of the model, but those methods either fail to preserve the structural information or suffer from low computational efficiency. In this paper, we propose a novel method to generate concise building models from dense meshes by extracting and completing the planar primitives of the building. From the perspective of probability, we first extract planar primitives from the input mesh and obtain the adjacency relationships between the primitives. Since primitive loss and structural defects are inevitable in practice, we employ a novel structural completion approach to eliminate linkage errors. Finally, the concise polygonal mesh is reconstructed by connectivity‐based primitive assembling. Our method is efficient and robust to various challenging data. Experiments on various building models revealed the efficacy and applicability of our method.

Estimation in exponential family regression based on linked data contaminated by mismatch error

Identification of matching records in multiple files can be a challenging and error-prone task. Linkage error can considerably affect subsequent statistical analysis based on the resulting linked file. Several recent papers have studied post-linkage linear regression analysis with the response variable in one file and the covariates in a second file from the perspective of the "Broken Sample Problem" and "Permuted Data". In this paper, we present an extension of this line of research to exponential family response given the assumption of a small to moderate number of mismatches. A method based on observation-specific offsets to account for potential mismatches and $\ell_1$-penalization is proposed, and its statistical properties are discussed. We also present sufficient conditions for the recovery of the correct correspondence between covariates and responses if the regression parameter is known. The proposed approach is compared to established baselines, namely the methods by Lahiri-Larsen and Chambers, both theoretically and empirically based on synthetic and real data. The results indicate that substantial improvements over those methods can be achieved even if only limited information about the linkage process is available.

A Different Land of Opportunity: The Geography of Intergenerational Mobility in the Early Twentieth-Century United States

Has the geography of intergenerational mobility in the United States changed over time? Constructing a large historical linked sample, I show that upward mobility in the early twentieth century was greater for those who grew up in the coastal and industrial regions, in contrast to more recent times, where mobility is higher among persons who were raised in the middle of the country. The historical patterns are not driven by imperfections in record linkage or measurement error in economic status.

Impact of vaccination on COVID-19-associated admissions to critical care in England: a study of population linked data with quantitative bias analysis for linkage error.

ObjectivesTo explore associations between COVID-19 vaccination and admission to critical care with COVID-19 in England, by age group, dose, and over time. ApproachWe conducted a population cohort study by linking the Case Mix Programme national clinical audit of adult intensive care to the National Immunisation Management System, combined with population denominators from the Office for National Statistics. We compared patient characteristics and estimated rates of critical care admission by vaccination status and age group and explored variation in admission rates and relative protection over time. Finally, we used quantitative bias analysis to explore sensitivity to potential linkage error. ResultsBetween 1 May and 15 December 2021 (England’s Delta wave), 11,431 patients were admitted to adult critical care units in England with COVID-19, of whom 10,141 were included in the cohort. Vaccinated patients were older, with higher levels of severe comorbidity and immunocompromise. Unvaccinated patients were greatly overrepresented, with people who had received two or more doses being at least 92% less likely to be admitted compared with those who were unvaccinated, for all ages, once the second dose had been rolled out. Those aged 50 years or older who had received a booster/third dose were 98-99% less likely to be admitted compared with unvaccinated. Our analysis was robust to linkage error, but closely related analyses could have been exquisitely sensitive to missed links. ConclusionOur findings are consistent with a high degree of vaccine-acquired protection against critical care admission, with little waning in the first 6-9 months for those aged under 70. While our analysis was robust to linkage error, significant care is warranted with related analyses of linked vaccination and outcome databases.

Evaluation of the reported data linkage process and associated quality issues for linked routinely collected healthcare data in Multimorbidity research: a systematic review.

ObjectivesThe objective for this systematic review was to examine how the record linkage process was reported and to understand challenges related to accessing, linking, and analysing linked routinely collected data used for multimorbidity research.
 ApproachA systematic search for relevant studies was conducted in three online databases (Medline, Web of Science and Embase) in May 2021 using predefined search terms, and inclusion and exclusion criteria. Studies using linked routinely collected data for multimorbidity research were included. Information was extracted on how the linkage process was reported, which conditions were studied together, which data sources were used, as well as challenges encountered during the linkage process or with the linked dataset.
 The findings from this study will feed into further guidance to understand and minimise bias due to linkage error in medical research.
 ResultsTwenty studies were included, of which seventeen looked at the relationship between two specified long-term conditions. Fourteen studies received the linked dataset from an external data linkage provider. Hospital Episode Statistics was the most common source of data (n=5). Eight studies reported variables used for the data linkage, while only two studies reported pre-linkage checks. The quality of the linkage was assessed by three studies, of which two reported linkage rate and one reported raw linkage figures. Only one study checked for bias by comparing patient characteristics of linked and non-linked records.
 ConclusionsThe linkage process was poorly reported in multimorbidity research, even though this might introduce bias and potentially lead to inaccurate inferences drawn from the results. There is therefore a need for increased awareness of linkage bias and transparency of the linkage processes, which could be achieved through better adherence to reporting guidelines.

UK Longitudinal Linkage Collaboration – and the challenges in creating a new Longitudinal Populations Studies linked data resource.

ObjectivesThe UK Longitudinal Linkage Collaboration (UK LLC) is a new, unprecedented infrastructure enabling research into the COVID-19 pandemic. The UK LLC integrates data from >20 UK longitudinal studies with systematically linked health, administrative and environmental records to facilitate cross-disciplinary COVID-19 research for accredited UK based researchers. ApproachBringing together all of the key components that form the UK LLC was a huge challenge that may have only been possible in the midst of the pandemic. First, we collaborated with the Longitudinal Population Studies (LPS) to create and agree how data linkage, data provision and applications to access the UK LLC would work. In parallel, public contributors helped to create fair processing materials. Finally, we worked closely with NHS Digital and other key national data providers to organise approvals for all studies to be linked, and for the UK LLC to have delegated decision-making for research applications. ResultsWe faced a myriad of challenges creating the UK LLC including: Short timeframe and short-term funding structure – initial funding for six months with an 18-month extension. Working across >20 different LPS and four nations with different structures for access, consent and data provision. Lack of capacity at various points in the data pipeline due to the volume of COVID-19 research required and underway across the involved organisations. Data processing complexities – split data method means no one can see the entire process therefore catching linkage errors requires working across four different organisations. With such complex data flows it is challenging to find the balance with communications about data to the public – being accurate about what we are doing, but expressing the complexity in lay terms. ConclusionCreating the UK LLC required collaboration with LPS, data providers and researchers. An iterative approach to creating the data application and data provision pipelines was crucial in developing these processes. The UK LLC was built quickly, from initial funding in October 2020 to provisioning data to researchers in December 2021.

Progress in building a longitudinal framework of linked reference data for England and Wales.

The Office for National Statistics (ONS) is working to transform its statistics, moving away from a system that is based on a ten-yearly Census and supporting surveys, to one that uses all available data to produce the highest quality statistics at any given time. This transformation requires that analysts be supplied with new data, new methods, and a new platform. We are developing a longitudinal framework to structure and integrate administrative data; indexing data relating to people, business, location and classifications. The core reference data indexes aim to maximise the use and value of administrative data for statistical purposes within ONS where data standards, security and consistency are designed in from the start. Assigning index ID’s to data allows personally identifiable information to be removed without impacting the usability of the data. The framework enables analysis on data with links between people, businesses and locations. The Demographic Index (DI) clusters together administrative records of a population entity (person) and assigns them a Unique ID. The administrative data sources are selected based on their quality and their population coverage. As there is no unique person identifier available across these sources both deterministic and probabilistic linking methods are used to build the index. The design of the index and how it is updated and maintained over time must meet ONS statistical research needs whilst also adhering to data warehousing standards and keeping personal information safe. The result is an anonymised database of longitudinally linked administrative data that is used in the production of population statistics and other statistical projects. The creation of the DI has many challenges and further development will focus on how we measure and communicate quality to the users, investigating methods to reconcile attributes that are not align across sources and managing the linkage error as the DI is updated with more data.

Robust regression using probabilistically linked data

AbstractThere is growing interest in a data integration approach to survey sampling, particularly where population registers are linked for sampling and subsequent analysis. The reason for doing this is simple: it is only by linking the same individuals in the different sources that it becomes possible to create a data set suitable for analysis. But data linkage is not error free. Many linkages are nondeterministic, based on how likely a linking decision corresponds to a correct match, that is, it brings together the same individual in all sources. High quality linking will ensure that the probability of this happening is high. Analysis of the linked data should take account of this additional source of error when this is not the case. This is especially true for secondary analysis carried out without access to the linking information, that is, the often confidential data that agencies use in their record matching. We describe an inferential framework that allows for linkage errors when sampling from linked registers. After first reviewing current research activity in this area, we focus on secondary analysis and linear regression modeling, including the important special case of estimation of subpopulation and small area means. In doing so we consider both robustness and efficiency of the resulting linked data inferences.This article is categorized under: Algorithms and Computational Methods > Maximum Likelihood Methods Statistical Learning and Exploratory Methods of the Data Sciences > Modeling Methods Statistical and Graphical Methods of Data Analysis > Multivariate Analysis

New generations of respondents: assessing the representativity of the HILDA Survey's child sample.

An important aspect of an indefinite life household panel study is to provide a sample of children who become new generations of respondents over time. The representativity of children and young adults in the Household, Income and Labour Dynamics in Australia (HILDA) Survey is assessed after 16 waves. Estimates from the HILDA Survey are compared to official data sources of the Australian Bureau of Statistics (ABS) and include demographic, education, employment, income and residential mobility variables. Both cross-section and longitudinal estimates are assessed. Overall, the HILDA Survey estimates are relatively close to the ABS estimates with the exception of the year of arrival of recent immigrants, having foreign-born parents, having a certificate level qualification, type of relationship in household, having zero income, the main source of income, and residential mobility. Most of these exceptions can be explained by differences in questionnaire design, respondent recall error, linkage error, and differences in the amount of missing data. The estimate of particular concern is the proportion of immigrants arriving in the last five years, which is underestimated in the HILDA Survey due to undercoverage of recent immigrants. This could be addressed by regular refreshment samples of recent immigrants.

On the consistent estimation of linkage errors without training data

On the consistent estimation of linkage errors without training data

Multi-Parameter Estimation of PMSM Using Differential Model With Core Loss Compensation

Accurate parameters are critical to permanent magnet synchronous machine (PMSM) drive. This paper investigates accurate flux linkages, inductances and PM flux linkage estimation for PMSM with core loss compensation. With conventional model, core loss will induce the flux linkage error especially in the deep saturation region. Hence, this paper firstly proposes a novel differential modeling technique to compensate core loss, in which differential measurement is defined as the incremental value calculated from the actual measurements under two different speed conditions. With multiple differential measurements, the flux linkage error due to core loss can be compensated to improve the accuracy of flux linkage estimation. Then, the polynomial based flux linkage model is employed to derive the PM flux linkage and cross-saturation inductances. Self-inductances are estimated from the flux linkage model using least squares method. The proposed approach can accurately estimate parameters without the need of core loss data and can improve the estimation accuracy especially in deep saturation region, which is validated on a laboratory interior PMSM and compared with existing methods under various operating conditions.

Site-specific nanobody-oligonucleotide conjugation for super-resolution imaging.

Camelid single-domain antibody fragments, also called nanobodies, constitute a class of binders that are small in size (~15 kDa) and possess antigen-binding properties similar to their antibody counterparts. Facile production of recombinant nanobodies in several microorganisms has made this class of binders attractive within the field of molecular imaging. Particularly, their use in super-resolution microscopy has improved the spatial resolution of molecular targets due to a smaller linkage error. In single-molecule localization microscopy techniques, the effective spatial resolution can be further enhanced by site-specific fluorescent labeling of nanobodies owing to a more homogeneous protein-to-fluorophore stoichiometry, reduced background staining and a known distance between dye and epitope. Here, we present a protocol for site-specific bioconjugation of DNA oligonucleotides to three distinct nanobodies expressed with an N- or C-terminal unnatural amino acid, 4-azido-L-phenylalanine (pAzF). Using copper-free click chemistry, the nanobody-oligonucleotide conjugation reactions were efficient and yielded highly pure bioconjugates. Target binding was retained in the bioconjugates, as demonstrated by bio-layer interferometry binding assays and the super-resolution microscopy technique, DNA points accumulation for imaging in nanoscale topography (PAINT). This method for site-specific protein-oligonucleotide conjugation can be further extended for applications within drug delivery and molecular targeting where site-specificity and stoichiometric control are required.

Linking Ambulance Records with Hospital and Death Index Data to Evaluate Patient Outcomes.

ObjectiveLinkage of electronic administrative datasets is becoming increasingly common, offering a powerful resource for research and analysis. However, routine linkage of prehospital data with emergency department (ED) presentation and hospital admission datasets is rare. We describe a methodology used to link ambulance data with hospital ED presentations, admissions, and death records, and examine potential biases between matched and unmatched patients.MethodsIterative deterministic linkage methodologies were employed to link clinical, operational, and secondary triage ambulance data to ED presentations, hospital admissions, and death records in Victoria, Australia. Descriptive analyses and standardised differences were used to examine potential biases between matched and unmatched patients.ResultsA total of 2,813,913 ambulance records were available for linkage. Of the patients that were transported to a public ED (n=1,753,268), 83.3% matched with an ED record. Only small differences were observed between matched and unmatched patients for sex, year, time of day and attending crew type. The data elements with the largest standardised differences were patient age (0.25) and paramedic diagnosis (0.25). Matched patients were older (mean ± standard deviation: 55.6±25.7 vs 49.0±26.0 years) and more likely to have a paramedic-suspected cardiac, respiratory, neurological, or gastrointestinal/genitourinary condition, suspected infection/sepsis, or pain.ConclusionThis linked dataset will facilitate a large body of research into prehospital care and patient outcomes. Although future analysis of matched patients should acknowledge the linkage error rate, our findings suggest that results are likely to be generalisable to the broader ambulance population.

Correcting for linkage errors in contingency tables—A cautionary tale

Record linkage aims to bring records together from two or more files that belong to the same statistical entity. Naïvely treating a linked file as if there are no linkage errors may lead to biased inference. We present two general approaches for compensating for linkage error when calculating and analysing a two-way contingency table for categorical data, and study the following question: under what conditions can a compensation approach improve on the naïve approach, where linkage error is not compensated for? To this end, we compare estimation errors, bias, variance and mean square error for the naïve approach and two compensation approaches by means of an analytical study as well as a simulation study.

Linking education and hospital data in England: linkage process and quality.

IntroductionLinkage of administrative data for universal state education and National Health Service (NHS) hospital care would enable research into the inter-relationships between education and health for all children in England.ObjectivesWe aim to describe the linkage process and evaluate the quality of linkage of four one-year birth cohorts within the National Pupil Database (NPD) and Hospital Episode Statistics (HES).MethodsWe used multi-step deterministic linkage algorithms to link longitudinal records from state schools to the chronology of records in the NHS Personal Demographics Service (PDS; linkage stage 1), and HES (linkage stage 2). We calculated linkage rates and compared pupil characteristics in linked and unlinked samples for each stage of linkage and each cohort (1990/91, 1996/97, 1999/00, and 2004/05).ResultsOf the 2,287,671 pupil records, 2,174,601 (95%) linked to HES. Linkage rates improved over time (92% in 1990/91 to 99% in 2004/05). Ethnic minority pupils and those living in more deprived areas were less likely to be matched to hospital records, but differences in pupil characteristics between linked and unlinked samples were moderate to small.ConclusionWe linked nearly all pupils to at least one hospital record. The high coverage of the linkage represents a unique opportunity for wide-scale analyses across the domains of health and education. However, missed links disproportionately affected ethnic minorities or those living in the poorest neighbourhoods: selection bias could be mitigated by increasing the quality and completeness of identifiers recorded in administrative data or the application of statistical methods that account for missed links.HighlightsLongitudinal administrative records for all children attending state school and acute hospital services in England have been used for research for more than two decades, but lack of a shared unique identifier has limited scope for linkage between these databases.We applied multi-step deterministic linkage algorithms to 4 one-year cohorts of children born 1 September-31 August in 1990/91, 1996/97, 1999/00 and 2004/05. In stage 1, full names, date of birth, and postcode histories from education data in the National Pupil Database were linked to the NHS Personal Demographic Service. In stage 2, NHS number, postcode, date of birth and sex were linked to hospital records in Hospital Episode Statistics.Between 92% and 99% of school pupils linked to at least one hospital record. Ethnic minority pupils and pupils who were living in the most deprived areas were least likely to link. Ethnic minority pupils were less likely than white children to link at the first step in both algorithms.Bias due to linkage errors could lead to an underestimate of the health needs in disadvantaged groups. Improved data quality, more sensitive linkage algorithms, and/or statistical methods that account for missed links in analyses, should be considered to reduce linkage bias.

Regression with linked datasets subject to linkage error

AbstractData are often collected from multiple heterogeneous sources and are combined subsequently. In combing data, record linkage is an essential task for linking records in datasets that refer to the same entity. Record linkage is generally not error‐free; there is a possibility that records belonging to different entities are linked or that records belonging to the same entity are missed. It is not advisable to simply ignore such errors because they can lead to data contamination and introduce bias in sample selection or estimation, which, in return, can lead to misleading statistical results and conclusions. For a long while, this problem was not properly recognized, but in recent years a growing number of researchers have developed methodology for dealing with linkage errors in regression analysis with linked datasets. The main goal of this overview is to give an account of those developments, with an emphasis on recent approaches and their connection to the so‐called “Broken Sample” problem. We also provide a short empirical study that illustrates the efficacy of corrective methods in different scenarios.This article is categorized under:Statistical Models > Model SelectionStatistical and Graphical Methods of Data Analysis > Robust MethodsStatistical and Graphical Methods of Data Analysis > Multivariate Analysis

Speed sensorless control of a bearingless induction motor based on fuzzy PI fractional MRAS scheme

ABSTRACT To handle the suspended rotor speed self-identification problem of a bearingless induction motor (BL-IM), a sensorless control strategy based on fuzzy PI fractional model reference adaptive system (MRAS) is proposed. First, based on the flux linkage error, fractional MRAS adaptive law is designed to accelerate the response speed of the controlled object, and Lyapunov theorem is used to prove the stability of the adaptive law. Then, the fuzzy control rules in the fuzzy PI controller are used to adjust PI parameters of adaptive law online in real time. Finally, the speed under no-load operation, abrupt speed change and abrupt change of load is estimated and sensorless control is realized. The simulation and experimental results show that the proposed fuzzy PI fractional MRAS control system of the BL-IM can not only effectively realize self-identification of speed under no-load, speed change and abrupt change of load, but also have good suspension characteristics of the motor suspended rotor, realizing high reliability and low costs of BL-IM.

Site-Specifically-Labeled Antibodies for Super-Resolution Microscopy Reveal In Situ Linkage Errors.

The precise spatial localization of proteins in situ by super-resolution microscopy (SRM) demands their targeted labeling. Positioning reporter molecules as close as possible to the target remains a challenge in primary cells or tissues from patients that cannot be easily genetically modified. Indirect immunolabeling introduces relatively large linkage errors, whereas site-specific and stoichiometric labeling of primary antibodies relies on elaborate chemistries. In this study, we developed a simple two-step protocol to site-specifically attach reporters such as fluorophores or DNA handles to several immunoglobulin G (IgG) antibodies from different animal species and benchmarked the performance of these conjugates for 3D STORM (stochastic optical reconstruction microscopy) and DNA-PAINT (point accumulation in nanoscale topography). Glutamine labeling was restricted to two sites per IgG and saturable by exploiting microbial transglutaminase after removal of N-linked glycans. Precision measurements of 3D microtubule labeling shell dimensions in cell lines and human platelets showed that linkage errors from primary and secondary antibodies did not add up. Monte Carlo simulations of a geometric microtubule-IgG model were in quantitative agreement with STORM results. The simulations revealed that the flexible hinge between Fab and Fc segments effectively randomized the direction of the secondary antibody, while the restricted binding orientation of the primary antibody’s Fab fragment accounted for most of the systematic offset between the reporter and α-tubulin. DNA-PAINT surprisingly yielded larger linkage errors than STORM, indicating unphysiological conformations of DNA-labeled IgGs. In summary, our cost-effective protocol for generating well-characterized primary IgG conjugates offers an easy route to precise SRM measurements in arbitrary fixed samples.

Record linkage under suboptimal conditions for data-intensive evaluation of primary care in Rio de Janeiro, Brazil

BackgroundLinking Brazilian databases demands the development of algorithms and processes to deal with various challenges including the large size of the databases, the low number and poor quality of personal identifiers available to be compared (national security number not mandatory), and some characteristics of Brazilian names that make the linkage process prone to errors. This study aims to describe and evaluate the quality of the processes used to create an individual-linked database for data-intensive research on the impacts on health indicators of the expansion of primary care in Rio de Janeiro City, Brazil.MethodsWe created an individual-level dataset linking social benefits recipients, primary health care, hospital admission and mortality data. The databases were pre-processed, and we adopted a multiple approach strategy combining deterministic and probabilistic record linkage techniques, and an extensive clerical review of the potential matches. Relying on manual review as the gold standard, we estimated the false match (false-positive) proportion of each approach (deterministic, probabilistic, clerical review) and the missed match proportion (false-negative) of the clerical review approach. To assess the sensitivity (recall) to identifying social benefits recipients’ deaths, we used their vital status registered on the primary care database as the gold standard.ResultsIn all linkage processes, the deterministic approach identified most of the matches. However, the proportion of matches identified in each approach varied. The false match proportion was around 1% or less in almost all approaches. The missed match proportion in the clerical review approach of all linkage processes were under 3%. We estimated a recall of 93.6% (95% CI 92.8–94.3) for the linkage between social benefits recipients and mortality data.ConclusionThe adoption of a linkage strategy combining pre-processing routines, deterministic, and probabilistic strategies, as well as an extensive clerical review approach minimized linkage errors in the context of suboptimal data quality.