Testing for measurement error in survey data analysis using paradata

Biometrika ◽  
2020 ◽  
Author(s):  
D N Da Silva ◽  
C J Skinner

Summary Paradata refers to survey variables which are not of direct interest themselves, but are related to the quality of data on survey variables which are of interest. We focus on a categorical paradata variable, which reflects the presence of measurement error in a variable of interest. We propose a quasi-score test of the hypothesis of no measurement error bias in the estimation of regression coefficients under models for paradata. We also propose a regression-based test, analogous to a simple test proposed by Fuller for instrumental variables. The methods developed can take account of a complex sampling design. In an application with data from the British Household Panel Survey, all tests provide clear evidence of measurement bias in the estimated coefficient of gross pay. In a simulation study, all tests have rejection rates close to the nominal level under the null hypothesis; the quasi-score tests display more power than the regression-based test. The size of the quasi-score test is shown to be robust to some forms of misspecification of the paradata model, both by a theoretical argument and in findings of the simulation study.

Author(s):  
B. L. Armbruster ◽  
B. Kraus ◽  
M. Pan

One goal in electron microscopy of biological specimens is to improve the quality of data to equal the resolution capabilities of modem transmission electron microscopes. Radiation damage and beam- induced movement caused by charging of the sample, low image contrast at high resolution, and sensitivity to external vibration and drift in side entry specimen holders limit the effective resolution one can achieve. Several methods have been developed to address these limitations: cryomethods are widely employed to preserve and stabilize specimens against some of the adverse effects of the vacuum and electron beam irradiation, spot-scan imaging reduces charging and associated beam-induced movement, and energy-filtered imaging removes the “fog” caused by inelastic scattering of electrons which is particularly pronounced in thick specimens.Although most cryoholders can easily achieve a 3.4Å resolution specification, information perpendicular to the goniometer axis may be degraded due to vibration. Absolute drift after mechanical and thermal equilibration as well as drift after movement of a holder may cause loss of resolution in any direction.


Author(s):  
Nur Maimun ◽  
Jihan Natassa ◽  
Wen Via Trisna ◽  
Yeye Supriatin

The accuracy in administering the diagnosis code was the important matter for medical recorder, quality of data was the most important thing for health information management of medical recorder. This study aims to know the coder competency for accuracy and precision of using ICD 10 at X Hospital in Pekanbaru. This study was a qualitative method with case study implementation from five informan. The result show that medical personnel (doctor) have never received a training about coding, doctors writing that hard and difficult to read, failure for making diagnoses code or procedures, doctor used an usual abbreviations that are not standard, theres still an officer who are not understand about the nomenclature and mastering anatomy phatology, facilities and infrastructure were supported for accuracy and precision of the existing code. The errors of coding always happen because there is a human error. The accuracy and precision in coding very influence against the cost of INA CBGs, medical and the committee did most of the work in the case of severity level III, while medical record had a role in monitoring or evaluation of coding implementation. If there are resumes that is not clearly case mix team check file needed medical record the result the diagnoses or coding for conformity. Keywords: coder competency, accuracy and precision of coding, ICD 10


2017 ◽  
Vol 4 (1) ◽  
pp. 25-31 ◽  
Author(s):  
Diana Effendi

Information Product Approach (IP Approach) is an information management approach. It can be used to manage product information and data quality analysis. IP-Map can be used by organizations to facilitate the management of knowledge in collecting, storing, maintaining, and using the data in an organized. The  process of data management of academic activities in X University has not yet used the IP approach. X University has not given attention to the management of information quality of its. During this time X University just concern to system applications used to support the automation of data management in the process of academic activities. IP-Map that made in this paper can be used as a basis for analyzing the quality of data and information. By the IP-MAP, X University is expected to know which parts of the process that need improvement in the quality of data and information management.   Index term: IP Approach, IP-Map, information quality, data quality. REFERENCES[1] H. Zhu, S. Madnick, Y. Lee, and R. Wang, “Data and Information Quality Research: Its Evolution and Future,” Working Paper, MIT, USA, 2012.[2] Lee, Yang W; at al, Journey To Data Quality, MIT Press: Cambridge, 2006.[3] L. Al-Hakim, Information Quality Management: Theory and Applications. Idea Group Inc (IGI), 2007.[4] “Access : A semiotic information quality framework: development and comparative analysis : Journal ofInformation Technology.” [Online]. Available: http://www.palgravejournals.com/jit/journal/v20/n2/full/2000038a.html. [Accessed: 18-Sep-2015].[5] Effendi, Diana, Pengukuran Dan Perbaikan Kualitas Data Dan Informasi Di Perguruan Tinggi MenggunakanCALDEA Dan EVAMECAL (Studi Kasus X University), Proceeding Seminar Nasional RESASTEK, 2012, pp.TIG.1-TI-G.6.


2018 ◽  
Author(s):  
Zisheng Ai ◽  
Yuhong Tang ◽  
Jiaqi Zheng ◽  
Sanyou Wu ◽  
Ying Wu

BACKGROUND Figures are an important form of expressing results commonly found in medical papers and make data easy to read and compare. The quality of graphs in original papers has improved in western medical journals. However, some figures fail to correctly express the results of a paper. Additionally, graph quality and application has not been assessed in medical journals outside western countries. OBJECTIVE To determine the frequency and types of data graphs used in Chinese academic medical journals and evaluate the quality of graphs used in original medical papers. METHODS A total of 783 papers were surveyed from the medical journals of five colleges and universities in Shanghai from 2011 to 2015. A cross-sectional study was used to analyse the applied status and graph quality. The evaluation criteria of graphs mainly included graph type, visual clarity, completeness, and special standards. RESULTS Most authors prefer to use simple charts, and bar charts with 95% CI were the most widely used. More than 60% of charts have problems with visual clarity, completeness, and special standards. Of 841 incorrect graphs, 10 (0.58%) graphs had three combined problems of graph characteristics, and 292 (34.72%) graphs had any two combined problems of graph characteristics. For detailed errors, the absence of variance description was the most substantial problem, especially in 2014 and in some academic medical journals. CONCLUSIONS Graphs are less commonly applied in the five university journals. However, the quality of papers using graphs was not properly controlled. Editors and journal quality management should strengthen the quality control of charts in papers. Authors should also avoid error bias and distorting their conclusions.


2019 ◽  
Author(s):  
Bogdan Corneliu Andor ◽  
Dionisio Franco Barattini ◽  
Dumitru Emanuel Dogaru ◽  
Simone Guadagna ◽  
Serban Rosu

BACKGROUND Osteoarthritis (OA) is one of the top five most disabling conditions and it affects more than one third of persons over 65 years of age. Currently 80% of persons affected by OA already report having some movement limitation, 20% of people are not be able to perform major activities of daily living, and about 11% of the total affected population need of personal care. On 2014 the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis (ESCEO) suggested as first step of pharmacological treatment for knee OA a background therapy with chronic symptomatic slow-acting drugs for osteoarthritis (SYSADOAs), such as glucosamine sulphate, chondroitin sulphate and hyaluronic acid (HA). In studies with oral HA, symptoms of OA are often measured using subjective parameters such as the visual analog scale (VAS) or the quality of life questionnaire (QoL) and objective measurements as ultrasonography (US) or range of motion (ROM) are employed in very few trials. This affects the quality of data in the literature. OBJECTIVE The primary objective of this work is to assess the feasibility of implementing US and ROM as objective measurements to correlate the improvement of knee mobility with pain reduction, evaluated using a subjective scale (VAS) in patients assuming a nutraceutical containing HA. The secondary objective is to evaluate the enrollment rate in one month to verify the feasibility for time and budget of the planned future main study. The explorative objective of the trial is to obtain preliminary data on efficacy of the tested product. METHODS This open-label pilot trial is performed in an orthopedic clinic (Timisoara, Romania). Male and female subjects (from 50 to 70 years) diagnosed with symptomatic OA of the knee with mild joint discomfort for at least 6 months are included. Following protocol, 8 patients are administered for 8 weeks Syalox® 300 Plus (River Pharma, Italy), a product based on HA of high molecular weight. Baseline and final visit assessments include orthopedic assessment, US, Knee injury and Osteoarthritis Outcome Score (KOOS) questionnaire, VAS and ROM of knee. RESULTS Data collection occurred between February 2018 and June 2018. All results are expected to be available by the end of 2018. CONCLUSIONS This pilot trial will be the first study to analyze the potential correlation between subjective evaluation (VAS, KOOS questionnaire) and objective measurements (US, ROM and actigraphy). The data from this study will assess the feasibility of the planned monthly recruitment rate and the necessary time and budget, and should provide preliminary information on efficacy of the tested product. CLINICALTRIAL ClinicalTrials.gov (NCT number: NCT03421054).


2020 ◽  
Author(s):  
Juqing Zhao ◽  
Pei Chen ◽  
Guangming Wan

BACKGROUND There has been an increase number of eHealth and mHealth interventions aimed to support symptoms among cancer survivors. However, patient engagement has not been guaranteed and standardized in these interventions. OBJECTIVE The objective of this review was to address how patient engagement has been defined and measured in eHealth and mHealth interventions designed to improve symptoms and quality of life for cancer patients. METHODS Searches were performed in MEDLINE, PsychINFO, Web of Science, and Google Scholar to identify eHealth and mHealth interventions designed specifically to improve symptom management for cancer patients. Definition and measurement of engagement and engagement related outcomes of each intervention were synthesized. This integrated review was conducted using Critical Interpretive Synthesis to ensure the quality of data synthesis. RESULTS A total of 792 intervention studies were identified through the searches; 10 research papers met the inclusion criteria. Most of them (6/10) were randomized trial, 2 were one group trail, 1 was qualitative design, and 1 paper used mixed method. Majority of identified papers defined patient engagement as the usage of an eHealth and mHealth intervention by using different variables (e.g., usage time, log in times, participation rate). Engagement has also been described as subjective experience about the interaction with the intervention. The measurement of engagement is in accordance with the definition of engagement and can be categorized as objective and subjective measures. Among identified papers, 5 used system usage data, 2 used self-reported questionnaire, 1 used sensor data and 3 used qualitative method. Almost all studies reported engagement at a moment to moment level, but there is a lack of measurement of engagement for the long term. CONCLUSIONS There have been calls to develop standard definition and measurement of patient engagement in eHealth and mHealth interventions. Besides, it is important to provide cancer patients with more tailored and engaging eHealth and mHealth interventions for long term engagement.


2021 ◽  
pp. 004912412199553
Author(s):  
Jan-Lucas Schanze

An increasing age of respondents and cognitive impairment are usual suspects for increasing difficulties in survey interviews and a decreasing data quality. This is why survey researchers tend to label residents in retirement and nursing homes as hard-to-interview and exclude them from most social surveys. In this article, I examine to what extent this label is justified and whether quality of data collected among residents in institutions for the elderly really differs from data collected within private households. For this purpose, I analyze the response behavior and quality indicators in three waves of Survey of Health, Ageing and Retirement in Europe. To control for confounding variables, I use propensity score matching to identify respondents in private households who share similar characteristics with institutionalized residents. My results confirm that most indicators of response behavior and data quality are worse in institutions compared to private households. However, when controlling for sociodemographic and health-related variables, differences get very small. These results suggest the importance of health for the data quality irrespective of the housing situation.


Author(s):  
Cornelius J Clancy ◽  
Ilan S Schwartz ◽  
Brittany Kula ◽  
M Hong Nguyen

Abstract Background Limited clinical data suggest ~16% prevalence of bacterial superinfections among critically ill patients with coronavirus disease 2019 (COVID-19). Methods We reviewed postmortem studies of patients with COVID-19 published in English through 26 September 2020 for histopathologic findings consistent with bacterial lung infections. Results Worldwide, 621 patients from 75 studies were included. The quality of data was uneven, likely because identifying superinfections was not a major objective in 96% (72/75) of studies. Histopathology consistent with potential lung superinfection was reported in 32% (200/621) of patients (22-96 years old; 66% men). Types of infections were pneumonia (95%), abscesses or empyema (3.5%), and septic emboli (1.5%). Seventy-three percent of pneumonias were focal rather than diffuse. Predominant histopathologic findings were intra-alveolar neutrophilic infiltrations that were distinct from those typical of COVID-19-associated diffuse alveolar damage. In studies with available data, 79% of patients received antimicrobial treatment; most common agents were beta-lactam/beta-lactamase inhibitors (48%), macrolides (16%), cephalosoprins (12%), and carbapenems (6%). Superinfections were proven by direct visualization or recovery of bacteria in 25.5% (51/200) of potential cases, and 8% of all patients in postmortem studies. In rank order, pathogens included Acinetobacter baumannii, Staphylococcus aureus, Pseudomonas aeruginosa and Klebsiella pneumoniae. Lung superinfections were causes of death in 16% of potential cases, and 3% of all patients with COVID-19. Conclusions Potential bacterial lung superinfections were evident at postmortem examination in 32% of persons who died with COVID-19 (proven, 8%; possible, 24%), but they were uncommonly the cause of death.


2021 ◽  
Vol 15 (4) ◽  
pp. 1-20
Author(s):  
Georg Steinbuss ◽  
Klemens Böhm

Benchmarking unsupervised outlier detection is difficult. Outliers are rare, and existing benchmark data contains outliers with various and unknown characteristics. Fully synthetic data usually consists of outliers and regular instances with clear characteristics and thus allows for a more meaningful evaluation of detection methods in principle. Nonetheless, there have only been few attempts to include synthetic data in benchmarks for outlier detection. This might be due to the imprecise notion of outliers or to the difficulty to arrive at a good coverage of different domains with synthetic data. In this work, we propose a generic process for the generation of datasets for such benchmarking. The core idea is to reconstruct regular instances from existing real-world benchmark data while generating outliers so that they exhibit insightful characteristics. We propose and describe a generic process for the benchmarking of unsupervised outlier detection, as sketched so far. We then describe three instantiations of this generic process that generate outliers with specific characteristics, like local outliers. To validate our process, we perform a benchmark with state-of-the-art detection methods and carry out experiments to study the quality of data reconstructed in this way. Next to showcasing the workflow, this confirms the usefulness of our proposed process. In particular, our process yields regular instances close to the ones from real data. Summing up, we propose and validate a new and practical process for the benchmarking of unsupervised outlier detection.


2020 ◽  
Vol 10 (1) ◽  
pp. 1-16
Author(s):  
Isaac Nyabisa Oteyo ◽  
Mary Esther Muyoka Toili

AbstractResearchers in bio-sciences are increasingly harnessing technology to improve processes that were traditionally pegged on pen-and-paper and highly manual. The pen-and-paper approach is used mainly to record and capture data from experiment sites. This method is typically slow and prone to errors. Also, bio-science research activities are often undertaken in remote and distributed locations. Timeliness and quality of data collected are essential. The manual method is slow to collect quality data and relay it in a timely manner. Capturing data manually and relaying it in real time is a daunting task. The data collected has to be associated to respective specimens (objects or plants). In this paper, we seek to improve specimen labelling and data collection guided by the following questions; (1) How can data collection in bio-science research be improved? (2) How can specimen labelling be improved in bio-science research activities? We present WebLog, an application that we prototyped to aid researchers generate specimen labels and collect data from experiment sites. We use the application to convert the object (specimen) identifiers into quick response (QR) codes and use them to label the specimens. Once a specimen label is successfully scanned, the application automatically invokes the data entry form. The collected data is immediately sent to the server in electronic form for analysis.


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