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36 results for “Measurement error”
Dataset for publication "Measurement of the Absolute Phase Error of Digitizers"
<p>This is the dataset related to the paper:</p> <p>G. Crotti, A. D. Femine, D. Gallo, D. Giordano, C. Landi and M. Luiso, "Measurement of the Absolute Phase Error of Digitizers," in <em>IEEE Transactions on Instrumentation and Measurement</em>, vol. 68, no. 6, pp. 1724-1731, June 2019.<br> doi: 10.1109/TIM.2018.2888919</p> <p>Excel file contains the data for Figures 2 and 3.</p>
Data from: Sharing is caring? measurement error and the issues arising from combining 3D morphometric datasets
Geometric morphometrics is routinely used in ecology and evolution and morphometric datasets are increasingly shared among researchers, allowing for more comprehensive studies and higher statistical power (as a consequence of increased sample size). However, sharing of morphometric data opens up the question of how much nonbiologically relevant variation (i.e., measurement error) is introduced in the resulting datasets and how this variation affects analyses. We perform a set of analyses based on an empirical 3D geometric morphometric dataset. In particular, we quantify the amount of error associated with combining data from multiple devices and digitized by multiple operators and test for the presence of bias. We also extend these analyses to a dataset obtained with a recently developed automated method, which does not require human-digitized landmarks. Further, we analyze how measurement error affects estimates of phylogenetic signal and how its effect compares with the effect of phylogenetic uncertainty. We show that measurement error can be substantial when combining surface models produced by different devices and even more among landmarks digitized by different operators. We also document the presence of small, but significant, amounts of nonrandom error (i.e., bias). Measurement error is heavily reduced by excluding landmarks that are difficult to digitize. The automated method we tested had low levels of error, if used in combination with a procedure for dimensionality reduction. Estimates of phylogenetic signal can be more affected by measurement error than by phylogenetic uncertainty. Our results generally highlight the importance of landmark choice and the usefulness of estimating measurement error. Further, measurement error may limit comparisons of estimates of phylogenetic signal across studies if these have been performed using different devices or by different operators. Finally, we also show how widely held assumptions do not always hold true, particularly that measurement error affects inference more at a shallower phylogenetic scale and that automated methods perform worse than human digitization.
SIP-field porbe development: Lessons learned & measurement error estimations
Open the record for dataset details and reuse information.
Data from: Colour patch size and measurement error using reflectance spectrometry
1. Over the past twenty years, portable and relatively affordable spectrophotometers have greatly advanced the study of animal coloration. However, the small size of many colour patches poses methodological challenges that have not, to date, been assessed in the literature. Here, we tackle this issue for a reflectance spectrophotometry set-up widely used in ecology and evolution (the beam method). 2. We reviewed the literature on animal coloration reporting the use of reflectance spectrophotometry to explore how the minimum measurable size of a colour patch is determined. We then used coloured plastic sheets to create artificial colour patches, and quantify the relationship between colour patch size and distortions induced by resulting chimeric spectra (spectra contaminated by an adjacent colour patch). Finally, we assessed the generality of our findings using natural colour spots in the lizard Podarcis muralis, as a biologically realistic model. 3. We found a lack of consensus in the literature, frequently resulting in the rejection of valid data or the potential inclusion of unreliable data. As expected, we show that decreasing colour patch size reduces the reliability of reflectance measurements, but also that spectral distortions resulting from chimeric spectra depend on patch/background colour combinations. We found similar results using natural colour spots in P. muralis. 4. We propose a series of steps to avoid the pitfalls described above. First, we provide guidelines on how to identify chimeric spectra and estimate the minimum size of a measurable colour patch in order to avoid them. Second, we show that reducing the probe-to-surface distance allows for more accurate measurements and therefore improves the spectrophotometric assessment of small colour patches. Third, we suggest that, as a general rule of thumb, very small (< 2 mm) colour patches should be avoided when using traditional spectrophotometry methods.
SP2 measurement error of BC mixing state and radiative forcing evaluation
<p>The first version of dataset.</p>
Study of a Hand-held Device Plus Mobile App Versus Standard Eye Care Devices in Measuring Refractive Error of the Eye
ClinicalTrials.gov study NCT03929588. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: Sharing is caring? measurement error and the issues arising from combining 3D morphometric datasets
Open the record for dataset details and reuse information.
Data from: Colour patch size and measurement error using reflectance spectrometry
Open the record for dataset details and reuse information.
Low-pass sequencing increases the power of GWAS and decreases measurement error of polygenic risk scores compared to genotyping arrays
GEO Series GSE165845. Homo sapiens. 360 samples. Type: Genome variation profiling by array.
Machine-learning method for predicting the scanning parameters influence on random measurement error
<p>Data acompaniing the study.</p>
Dataset for publication: Error in the measurement of partial discharge pulses according to the frequency response of HFCT sensors
<p>Data set belonging to the <a href="https://ieeexplore.ieee.org/xpl/conhome/9611374/proceeding">2021 IEEE Electrical Insulation Conference (EIC)</a> paper with DOI: <a href="https://doi.org/10.1109/EIC49891.2021.9612353">10.1109/EIC49891.2021.9612353</a></p> <p>The authors preprint is available from Zendodo with DOI: <a href="https://doi.org/10.5281/zenodo.5769815">10.5281/zenodo.5769815</a>. </p> <p>Kamlichi, Abderrahim, Garnancho Fernando; Álvarez Fernando</p> <p><em>Error in the measurement of partial discharge pulses according to the frequency response of HFCT sensors</em></p>
Motor Learning of a Planning Task in Stroke Patients: the Maze Paradigm Measured Through Time and Error as Variables
ClinicalTrials.gov study NCT00740402. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Objective of This Study is to Evaluate the Perfomance of a Photorefraction Device for Screening Ametropia in Children. Eligible Participants Will Undergo Multiple Refractive Error Measurements, Vi
ClinicalTrials.gov study NCT06882408. IPD Sharing: NO. Countries: 1. Publications: 0.
Energy Balance Teens: A Measurement Error Approach to Estimating Energy Balance in Free-Living Adolescents
ClinicalTrials.gov study NCT05296330. IPD Sharing: NO. Countries: 1. Publications: 0.
Measurement of Refractive Error in Pseudophakic Eyes Using an Autorefractor and a Wavefront Aberrometer
ClinicalTrials.gov study NCT06797856. IPD Sharing: YES. Countries: 1. Publications: 0.
Dataset of the paper "Minimal detectable change of gait and balance measures in older neurological patients: estimating the standard error of the measurement from before-after rehabilitation data thanks to the linear mixed-effects models"
<p>The Excel file contains the dataset whose analysis has been presented in the manuscript entitled <em>"Minimal detectable change of gait and balance measures in older neurological patients: estimating the standard error of the measurement from before-after rehabilitation data thanks to the linear mixed-effects models" </em>and published in J Neuroeng Rehabil (doi: 10.1186/s12984-024-01339-4; PMID: 38566189).</p> <p>This data set cannot be publicly available because of sensitive information. Please send your request to: a.caronni@auxologico.it.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.