scholarly journals Realistic precision and accuracy of online experiment platforms, web browsers, and devices

2020 ◽  
Author(s):  
Alexander Anwyl-Irvine ◽  
Edwin S. Dalmaijer ◽  
Nick Hodges ◽  
Jo K. Evershed
Keyword(s):  
Data Quality ◽  
Ease Of Use ◽  
Web Browsers ◽  
Display Time ◽  
Manual Response ◽  
Accuracy And Precision ◽  
Impact Experiment ◽  
Behavioural Research ◽  
Impact Data ◽  
Web Building

Abstract Due to increasing ease of use and ability to quickly collect large samples, online behavioural research is currently booming. With this popularity, it is important that researchers are aware of who online participants are, and what devices and software they use to access experiments. While it is somewhat obvious that these factors can impact data quality, the magnitude of the problem remains unclear. To understand how these characteristics impact experiment presentation and data quality, we performed a battery of automated tests on a number of realistic set-ups. We investigated how different web-building platforms (Gorilla v.20190828, jsPsych v6.0.5, Lab.js v19.1.0, and psychoJS/PsychoPy3 v3.1.5), browsers (Chrome, Edge, Firefox, and Safari), and operating systems (macOS and Windows 10) impact display time across 30 different frame durations for each software combination. We then employed a robot actuator in realistic set-ups to measure response recording across the aforementioned platforms, and between different keyboard types (desktop and integrated laptop). Finally, we analysed data from over 200,000 participants on their demographics, technology, and software to provide context to our findings. We found that modern web platforms provide reasonable accuracy and precision for display duration and manual response time, and that no single platform stands out as the best in all features and conditions. In addition, our online participant analysis shows what equipment they are likely to use.

scholarly journals Online Timing Accuracy and Precision: A comparison of platforms, browsers, and participant's devices

2020 ◽  
Author(s):  
Alexander Leslie Anwyl-Irvine ◽  
Edwin S. Dalmaijer ◽  
Nick Hodges ◽  
Jo Evershed
Keyword(s):  
Data Quality ◽  
Ease Of Use ◽  
Display Time ◽  
Manual Response ◽  
Timing Accuracy ◽  
Large Samples ◽  
Accuracy And Precision ◽  
Impact Experiment ◽  
Impact Data ◽  
Web Building

Due to its increasing ease-of-use and ability to quickly collect large samples, online behavioral research is currently booming. With this increasing popularity, it is important that researchers are aware of who online participants are, and what devices and software they use to access experiments. While it is somewhat obvious that these factors can impact data quality, it remains unclear how big this problem is. To understand how these characteristics impact experiment presentation and data quality, we performed a battery of automated tests on a number of representative setups. We investigated how different web-building platforms (Gorilla, jsPsych, Lab.js, and psychoJS/PsychoPy3), browsers (Chrome, Edge, Firefox, and Safari), and operating systems (mac OS and Windows 10) impact display time across 30 different frame durations for each software combination. In addition, we employed a robot actuator in representative setups to measure response recording across aforementioned platforms, and between different keyboard types (desktop and integrated laptop). We then surveyed over 200 000 participants on their demographics, technology, and software to provide context to our findings. We found that modern web-platforms provide a reasonable accuracy and precision for display duration and manual response time, but also identify specific combinations that produce unexpected variance and delays. While no single platform stands out as the best in all features and conditions, our findings can help researchers make informed decisions about which experiment building platform is most appropriate in their situation, and what equipment their participants are likely to have.

A comparative study of qualitative immunochemical screening assays for the combined measurement of T-2/HT-2 in cereals and cereal-based products

2011 ◽  
Vol 4 (4) ◽  
pp. 385-394 ◽  
Author(s):  
J. Meneely ◽  
F. Ricci ◽  
S. Vesco ◽  
M. Abouzied ◽  
M. Sulyok ◽  
...  
Keyword(s):  
Sample Preparation ◽  
Low Cost ◽  
Ease Of Use ◽  
The Other ◽  
Accuracy And Precision ◽  
Cost Implications ◽  
Electrochemical Array ◽  
The Cost ◽  
Preparation Techniques ◽  
Speed Of Analysis

Many different immunochemical platforms exist for the screening of naturally occurring contaminants in food from the low cost enzyme linked immunosorbent assays (ELISA) to the expensive instruments such as optical biosensors based on the phenomenon of surface plasmon resonance (SPR). The primary aim of this study was to evaluate and compare a number of these platforms to assess their accuracy and precision when applied to naturally contaminated samples containing HT-2/T-2 mycotoxins. Other important factors considered were the speed of analysis, ease of use (sample preparation techniques and use of the equipment) and ultimately the cost implications. The three screening procedures compared included an SPR biosensor assay, a commercially available ELISA and an enzymelinked immunomagnetic electrochemical array (ELIME array). The qualitative data for all methods demonstrated very good overall agreements with each other, however on comparison with mass spectrometry confirmatory results, the ELISA and SPR assay performed slightly better than the ELIME array, exhibiting an overall agreement of 95.8% compared to 91.7%. Currently, SPR is more costly than the other two platforms and can only be used in the laboratory whereas in theory both the ELISA and ELIME array are portable and can be used in the field, but ultimately this is dependent on the sample preparation techniques employed. Sample preparative techniques varied for all methods evaluated, the ELISA was the most simple to perform followed by that of the SPR method. The ELIME array involved an additional clean-up step thereby increasing both the time and cost of analysis. Therefore in the current format, field use would not be an option for the ELIME array. In relation to speed of analysis, the ELISA outperformed the other methods.

A Methodology to Assure Measurement Data Quality for Key Engineering Materials

2010 ◽  
Vol 108-111 ◽  
pp. 972-978
Author(s):  
Ying Su ◽  
Jing Hua Huang ◽  
Latif Al-Hakim
Keyword(s):  
Decision Making ◽  
Data Quality ◽  
Measurement Data ◽  
Limited Attention ◽  
Decision Making Process ◽  
Precision Determination ◽  
Accuracy And Precision ◽  
Process Documentation ◽  
Engineering Materials

Purpose – Only limited attention has been paid to the issue of Measurement Data Quality (MDQ) in a metrology context. To address this critique of the literature a methodology to assure MDQ was proposed. Methodology – The study proposes a methodology which consists of four steps can be used to 1 identify the importance of a measurement (identification), 2 determine accuracy and precision (determination), 3 evaluate the criticality of the measurement to its impact on the final result (evaluation) and 4 record the facts that influenced the decision making process (documentation). Findings –When followed and properly documented, these four steps can help ensure our measurements are valid and worthwhile. Identifying the important measurements that are made, determining the level of accuracy required and then using the proper tools to make the measurements will yield valid, useful results.

scholarly journals A Case Report of Switching from Specific Vendor-Based to R-Based Pipelines for Untargeted LC-MS Metabolomics

Metabolites ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 28 ◽  
Author(s):  
Álvaro Fernández-Ochoa ◽  
Rosa Quirantes-Piné ◽  
Isabel Borrás-Linares ◽  
María de la Luz Cádiz-Gurrea ◽  
Marta E. Alarcón Riquelme ◽  
...  
Keyword(s):  
Case Report ◽  
Data Quality ◽  
Open Source ◽  
Open Source Software ◽  
Ease Of Use ◽  
Plasma Samples ◽  
Batch Effects ◽  
Multivariate Models ◽  
Metabolomic Study

Data pre-processing of the LC-MS data is a critical step in untargeted metabolomics studies in order to achieve correct biological interpretations. Several tools have been developed for pre-processing, and these can be classified into either commercial or open source software. This case report aims to compare two specific methodologies, Agilent Profinder vs. R pipeline, for a metabolomic study with a large number of samples. Specifically, 369 plasma samples were analyzed by HPLC-ESI-QTOF-MS. The collected data were pre-processed by both methodologies and later evaluated by several parameters (number of peaks, degree of missingness, quality of the peaks, degree of misalignments, and robustness in multivariate models). The vendor software was characterized by ease of use, friendly interface and good quality of the graphs. The open source methodology could more effectively correct the drifts due to between and within batch effects. In addition, the evaluated statistical methods achieved better classification results with higher parsimony for the open source methodology, indicating higher data quality. Although both methodologies have strengths and weaknesses, the open source methodology seems to be more appropriate for studies with a large number of samples mainly due to its higher capacity and versatility that allows combining different packages, functions, and methods in a single environment.

scholarly journals Chromatic: WebAssembly-Based Cancer Genome Viewer

2018 ◽  
Vol 17 ◽  
pp. 117693511877197 ◽  
Author(s):  
Richard Finney ◽  
Daoud Meerzaman
Keyword(s):  
Ease Of Use ◽  
Data Sets ◽  
Web Browsers ◽  
Web Browser ◽  
Cancer Data ◽  
Genomic Variations ◽  
Genome Viewer ◽  
Code Format ◽  
Generation Sequencing ◽  
Cancer Bioinformatics

Chromatic is a novel web-browser tool that enables researchers to visually inspect genomic variations identified through next-generation sequencing of cancer data sets to determine whether such calls are, in fact, valid. It is the first cancer bioinformatics tool developed using WebAssembly technology, which comprises a portable, low-level byte code format that provides for the rapid execution of programs within supported web browsers. It has been designed expressly for ease of use by scientists without extensive expertise in bioinformatics.

scholarly journals Quantitative accuracy and precision in multiplexed single-cell proteomics

2021 ◽  
Author(s):  
Claudia Ctortecka ◽  
Karel Stejskal ◽  
Gabriela Krššáková ◽  
Sasha Mendjan ◽  
Karl Mechtler
Keyword(s):  
Data Quality ◽  
Single Cell ◽  
Experimental Designs ◽  
Ion Current ◽  
Impact Measurement ◽  
Measurement Variability ◽  
Biological Phenomena ◽  
Accuracy And Precision ◽  
Quantitative Accuracy ◽  
Proteomics Experiment

AbstractSingle-cell proteomics workflows have considerably improved in sensitivity and reproducibility to characterize yet unknown biological phenomena. With the emergence of multiplexed single-cell proteomics, studies increasingly present single-cell measurements in conjunction with an abundant congruent carrier to improve precursor selection and enhance identifications. While these extreme carrier spikes are often >100-times more abundant than the investigated samples, undoubtedly the total ion current increases, but quantitative accuracy possibly is affected. We here focus on narrowly titrated carrier spikes (i.e., <20x) and assess their elimination for comparable sensitivity at superior accuracy. We find that subtle changes in the carrier ratio can severely impact measurement variability and describe alternative multiplexing strategies to evaluate data quality. Lastly, we demonstrate elevated replicate overlap while preserving acquisition throughput at improved quantitative accuracy with DIA-TMT and discuss optimized experimental designs for multiplexed proteomics of trace samples. This comprehensive benchmarking gives an overview of currently available techniques and guides conceptualizing the optimal single-cell proteomics experiment.

Assessment and Stratification of High-Impact Data Elements in Electronic Clinical Quality Measures: A Joint Data Quality Initiative Between CancerLinQ® and Cancer Treatment Centers of America

2018 ◽  
pp. 1-10
Author(s):  
Rory J. Lettvin ◽  
Alpna Wayal ◽  
Amy McNutt ◽  
Robert S. Miller ◽  
Robert Hauser
Keyword(s):  
Data Quality ◽  
Cancer Treatment ◽  
Quality Measures ◽  
Potential Effect ◽  
High Impact ◽  
Specific Data ◽  
Clinical Quality ◽  
Data Elements ◽  
Clinical Measures ◽  
Impact Data

Purpose A joint data quality initiative between the Cancer Treatment Centers of America and the ASCO big data health technology platform CancerLinQ® was initiated to document and codify the steps taken to evaluate, stratify, and determine the potential effect of data elements used for electronic clinical quality measures as captured within structured fields in electronic health records. Methods The processes involved the identification of clinical concepts required in measure population criteria and then to map these to the corresponding components of the CancerLinQ data model. A quantitative assessment of mappings between electronic clinical quality measure clinical concepts and attributes from the CancerLinQ clinical database was performed. In parallel, a qualitative analysis of high-impact data elements from the Cancer Treatment Centers of America clinical measures was made using local, expert consensus. Results An impact assessment was derived using a count of the data elements across measures and the specific population criteria affected. Conclusion A list of putative high-impact data elements can provide guidance for clinicians to facilitate specific data element capture related to quality metrics in an electronic environment.

scholarly journals A Descriptive Study about Factors Affecting Data Quality of EWARS in Surabaya 2016

2017 ◽  
Vol 5 (2) ◽  
pp. 265
Author(s):  
Sobhita Paramita
Keyword(s):  
Data Quality ◽  
Sex Education ◽  
Simple Random Sampling ◽  
Descriptive Study ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Perceived Ease Of Use ◽  
Good Level ◽  
Level Of Knowledge

Early Warning and Response System (EWARS) is a health information technology used to report diseases in particular with potential outbreaks and it can generate "alerts" when an outbreak is found. EWARS report is conducted on a weekly basis by reporting disease data on EWARS website according to the code of each disease that has been established. This research is a descriptive study based on quantitative assessment. Sampling is done by using simple random sampling method. Interviews were conducted to 33 officers at Puskesmas Kota Surabaya by using questionnaires. The variables are respondent characteristics including age, sex, education level, length of work, computer experience, and EWARS socialization experience. Then, it also examines the level of knowledge, attitudes, perceived ease of use, perceived usefulness towards EWARS implementation, and data quality of EWARS itself. The result shows that the majority of respondents are at the age of 20-40 years, female sex, have a sufficient level of education, have worked as EWARS officers for more than 2 years, have been using computers for more than 2 years, been through EWARS socialization. In addition, most respondents have good level of knowledge, attitudes, perceived ease of use, and perceived usefulness towards EWARS implementation, but unfortunately, the data quality is still undervalued. The conclusion is that having good level of knowledge, attitude, perception of ease, and perception of usefulness does not always result EWARS report in high quality because other attributes still need to be measured.

Accuracy and Precision of the CoaguChek S versus Laboratory INRs in a Clinic

2002 ◽  
Vol 36 (5) ◽  
pp. 769-775 ◽  
Author(s):  
Dawn E Havrda ◽  
Toni L Hawk ◽  
Carrie M Marvin
Keyword(s):  
International Normalized Ratio ◽  
Ease Of Use ◽  
Laboratory Assessment ◽  
Altman Plot ◽  
Quality Controls ◽  
Technical Errors ◽  
Accuracy And Precision ◽  
Therapeutic Decisions ◽  
High Level ◽  
Local Laboratory

BACKGROUND: The CoaguChek S is the next-generation coagulation monitor for measuring the international normalized ratio (INR) that replaces the CoaguChek device. Studies are lacking comparing the CoaguChek S with local laboratory INR assessment to ensure its accuracy and precision for monitoring patients on anticoagulation. OBJECTIVE: To evaluate accuracy, precision, and technical ease-of-use of the CoaguChek S compared with laboratory measurements. METHODS: Accuracy was evaluated in 101 patients by parallel assessment of INRs (CoaguChek S and laboratory); precision was evaluated in 31 patients using duplicate INRs from CoaguChek S and laboratory and from liquid quality controls. Accuracy was determined using orthogonal regression, Bland—Altman plot, and clinical applicability (INRs discrepant in categorization of INR goal and resulting in different therapeutic decisions). Precision was examined by comparing mean difference ± SD between repeated INRs from CoaguChek S and laboratory, coefficient of variation (CV), and coefficient of repeatability (CR). The influence of low and elevated INRs on accuracy and precision was also examined. To assess ease-of-use of the monitor, the number of technical errors was recorded. RESULTS: The CoaguChek S significantly correlated to laboratory measurement (r = 0.93); 16.7% of INRs resulted in discrepant categorization and 24.5% would have required a different therapeutic plan. The CV and CR compared well between CoaguChek S and laboratory (6% vs. 4.9%; 0.455 vs. 0.346, respectively). When subgroups of INR values <4.0 and <3.0 were evaluated, the precision improved with both methods. Precision, based on liquid quality controls, was good (CV 4.6% = low-level; 3.3% = high-level). The CoaguChek S was found to have an error rate of 1.8%. CONCLUSIONS: The CoaguChek S is an accurate and precise alternative to laboratory assessment of the INR at values <4.0; it is an efficient device with a low likelihood of errors during testing.

scholarly journals Data quality of Whole Genome Bisulfite Sequencing on Illumina platforms

2017 ◽  
Author(s):  
Amanda Raine ◽  
Ulrika Liljedahl ◽  
Jessica Nordlund
Keyword(s):  
Dna Methylation ◽  
Data Quality ◽  
Large Scale ◽  
Cost Effective ◽  
Bisulfite Treatment ◽  
Real Time Analysis ◽  
Genome Bisulfite Sequencing ◽  
Software Upgrade ◽  
Impact Data

AbstractThe powerful HiSeq X sequencers with their patterned flowcell technology and fast turnaround times are instrumental for many large-scale genomic and epigenomic studies. However, assessment of DNA methylation by sodium bisulfite treatment results in sequencing libraries of low diversity, which may impact data quality and yield. In this report we assess the quality of WGBS data generated on the HiSeq X system in comparison with data generated on the HiSeq 2500 system and the newly released NovaSeq system. We report a systematic issue with low basecall quality scores assigned to guanines in the second read of WGBS when using certain Real Time Analysis (RTA) software versions on the HiSeq X sequencer, reminiscent of an issue that was previously reported with certain HiSeq 2500 software versions. However, with the HD.3.4.0/RTA 2.7.7 software upgrade for the HiSeq X system, we observed an overall improved quality and yield of the WGBS data generated, which in turn empowers cost-effective and high quality DNA methylation studies.

Sign in / Sign up

Export Citation Format

Share Document