scholarly journals Hemoglobin-Dilution Method: Effect of Measurement Errors on Vascular Volume Estimation

2017 ◽  
Vol 2017 ◽  
pp. 1-5 ◽  
Author(s):  
Matthew B. Wolf
Keyword(s):  
Measurement Error ◽  
Blood Volume ◽  
Measurement Errors ◽  
Geometric Mean ◽  
Hemoglobin Concentration ◽  
Repeated Measurements ◽  
Volume Estimation ◽  
Dilution Method ◽  
Log Normal ◽  
Normally Distributed

The hemoglobin-dilution method (HDM) has been used to estimate changes in vascular volumes in patients because direct measurements with radioisotopes are time-consuming and not practical in many facilities. The HDM requires an assumption of initial blood volume, repeated measurements of plasma hemoglobin concentration, and the calculation of the ratio of hemoglobin measurements. The statistics of these ratio distributions resulting from measurement error are ill-defined even when the errors are normally distributed. This study uses a “Monte Carlo” approach to determine the distribution of these errors. The finding was that these errors could be closely approximated with a log-normal distribution that can be parameterized by a geometric mean (X) and a dispersion factor (S). When the ratio of successive Hb concentrations is used to estimate blood volume, normally distributed hemoglobin measurement errors tend to produce exponentially higher values ofXandSas the SD of the measurement error increases. The longer tail of the distribution to the right could produce much greater overestimations than would be expected from the SD values of the measurement error; however, it was found that averaging duplicate and triplicate hemoglobin measurements on a blood sample greatly improved the accuracy.

scholarly journals The Effect of Random Error in Exposure Measurement upon the Shape of the Exposure Response

Dose-Response ◽  
2005 ◽  
Vol 3 (4) ◽  
pp. dose-response.0 ◽  
Author(s):  
Kenny S. Crump
Keyword(s):  
Measurement Error ◽  
Measurement Errors ◽  
Epidemiological Data ◽  
Epidemiological Studies ◽  
Random Errors ◽  
Exposure Measurement ◽  
Considerable Uncertainty ◽  
Exposure Response ◽  
Log Normal ◽  
Normally Distributed

Although statistical analyses of epidemiological data usually treat the exposure variable as being known without error, estimated exposures in epidemiological studies often involve considerable uncertainty. This paper investigates the theoretical effect of random errors in exposure measurement upon the observed shape of the exposure response. The model utilized assumes that true exposures are log-normally distributed, and multiplicative measurement errors are also log-normally distributed and independent of the true exposures. Under these conditions it is shown that whenever the true exposure response is proportional to exposure to a power r, the observed exposure response is proportional to exposure to a power K, where K < r. This implies that the observed exposure response exaggerates risk, and by arbitrarily large amounts, at sufficiently small exposures. It also follows that a truly linear exposure response will appear to be supra-linear—i.e., a linear function of exposure raised to the K-th power, where K is less than 1.0. These conclusions hold generally under the stated log-normal assumptions whenever there is any amount of measurement error, including, in particular, when the measurement error is unbiased either in the natural or log scales. Equations are provided that express the observed exposure response in terms of the parameters of the underlying log-normal distribution. A limited investigation suggests that these conclusions do not depend upon the log-normal assumptions, but hold more widely. Because of this problem, in addition to other problems in exposure measurement, shapes of exposure responses derived empirically from epidemiological data should be treated very cautiously. In particular, one should be cautious in concluding that the true exposure response is supra-linear on the basis of an observed supra-linear form.

scholarly journals ON THE UNIFORM CONVERGENCE OF DECONVOLUTION ESTIMATORS FROM REPEATED MEASUREMENTS

2021 ◽  
pp. 1-22
Author(s):  
Daisuke Kurisu ◽  
Taisuke Otsu
Keyword(s):  
Multivariate Analysis ◽  
Measurement Error ◽  
Uniform Convergence ◽  
Measurement Errors ◽  
Convergence Rates ◽  
Free Variable ◽  
Error Model ◽  
Repeated Measurements ◽  
Empirical Characteristic Function ◽  
Measurement Error Model

This paper studies the uniform convergence rates of Li and Vuong’s (1998, Journal of Multivariate Analysis 65, 139–165; hereafter LV) nonparametric deconvolution estimator and its regularized version by Comte and Kappus (2015, Journal of Multivariate Analysis 140, 31–46) for the classical measurement error model, where repeated noisy measurements on the error-free variable of interest are available. In contrast to LV, our assumptions allow unbounded supports for the error-free variable and measurement errors. Compared to Bonhomme and Robin (2010, Review of Economic Studies 77, 491–533) specialized to the measurement error model, our assumptions do not require existence of the moment generating functions of the square and product of repeated measurements. Furthermore, by utilizing a maximal inequality for the multivariate normalized empirical characteristic function process, we derive uniform convergence rates that are faster than the ones derived in these papers under such weaker conditions.

scholarly journals The influence of measurement error on the risks of the consumer and the manufacturer when completing connections

2020 ◽  
Vol 6 (1) ◽  
pp. 22-29
Author(s):  
Oleksandr Kupriyanov ◽  
Keyword(s):  
Measurement Error ◽  
Statistical Modeling ◽  
Measurement Errors ◽  
Repeated Measurements ◽  
Consumer’S Risk ◽  
Two Stage ◽  
Measuring Device ◽  
Manufactured Products ◽  
Tolerance Field ◽  
Laws Of Distribution

The influence of the measuring device error on the consumer’s and manufacturer’s risks was studied for three cases of the organization of completing: complete interchangeability, selective completing and completing with ranking. The presence of measurement error does not allow to avoid risks; however, their values must be estimated so that they do not have a significant impact on manufactured products. The study was carried out for a “shaft-hole” connection by statistical modeling, the laws of dimension distribution were accepted as normal, as well as the laws of distribution of measurement errors. For the case of completing with complete interchangeability, the accuracy of two-stage control was studied; it is recommended to establish the accuracy of the initial measurements at 20–25 % of the tolerance field, repeated measurements at 10–12 % of the tolerance field, while the manufacturer’s risk does not exceed 0.2 %, the consumer’s risk is practically zero. In the case of selective completing, the requirements for the accuracy of the measuring device are significantly higher than in the case of completing with complete interchangeability, since errors are possible not only at the limits of the tolerance field but also at the limits of the selection groups. Therefore, the measurement error should not exceed 5 % of the tolerance field width; it is also advisable to limit the number of selection groups. When completing with ranking, the accuracy of the measuring device has the least impact on risks, especially if the number of parts in the batch is large enough and the measurement error complies with the standards in mechanical engineering. It was established that for the number of sets greater than 10, almost complete assemblability is achieved and the risks associated with the measurement error become insignificant. Thus, if it is necessary to increase the accuracy of products at the assembly stage, it is recommended to use completing with ranking instead of selective completing.

Features of accumulation of amounts of measurement error

2017 ◽  
Vol 928 (10) ◽  
pp. 58-63 ◽  
Author(s):  
V.I. Salnikov
Keyword(s):  
Measurement Error ◽  
Confidence Interval ◽  
Normal Distribution ◽  
Confidence Level ◽  
Measurement Errors ◽  
Truncated Normal Distribution ◽  
Truncated Normal ◽  
The Law ◽  
Normal Law

The initial subject for study are consistent sums of the measurement errors. It is assumed that the latter are subject to the normal law, but with the limitation on the value of the marginal error Δpred = 2m. It is known that each amount ni corresponding to a confidence interval, which provides the value of the sum, is equal to zero. The paradox is that the probability of such an event is zero; therefore, it is impossible to determine the value ni of where the sum becomes zero. The article proposes to consider the event consisting in the fact that some amount of error will change value within 2m limits with a confidence level of 0,954. Within the group all the sums have a limit error. These tolerances are proposed to use for the discrepancies in geodesy instead of 2m*SQL(ni). The concept of “the law of the truncated normal distribution with Δpred = 2m” is suggested to be introduced.

Test–Retest Reliability of the Mini-BESTest in People With Mild to Moderate Multiple Sclerosis

2021 ◽  
Author(s):  
A Wallin ◽  
M Kierkegaard ◽  
E Franzén ◽  
S Johansson
Keyword(s):  
Multiple Sclerosis ◽  
Measurement Errors ◽  
Balance Control ◽  
Intraclass Correlation ◽  
Repeated Measurements ◽  
Minimal Detectable Change ◽  
Detectable Change ◽  
Limits Of Agreement ◽  
Retest Reliability ◽  
Test Retest Reliability

Abstract Objective The mini-BESTest is a balance measure for assessment of the underlying physiological systems for balance control in adults. Evaluations of test–retest reliability of the mini-BESTest in larger samples of people with multiple sclerosis (MS) are lacking. The purpose of this study was to investigate test–retest reliability of the mini-BESTest total and section sum scores and individual items in people with mild to moderate overall MS disability. Methods This study used a test–retest design in a movement laboratory setting. Fifty-four people with mild to moderate overall MS disability according to the Expanded Disability Status scale (EDSS) were included, with 28 in the mild subgroup (EDSS 2.0–3.5) and 26 in the moderate subgroup (EDSS 4.0–5.5). Test–retest reliability of the mini-BESTest was evaluated by repeated measurements taken 1 week apart. Reliability and measurement error were analyzed. Results Test–retest reliability for the total scores were considered good to excellent, with intraclass correlation coefficients of .88 for the whole sample, .83 for the mild MS subgroup, and .80 for the moderate MS subgroup. Measurement errors were small, with standard error of measurement and minimal detectable change of 1.3 and 3.5, respectively, in mild MS, and 1.7 and 4.7, respectively, in moderate MS. The limits of agreement were − 3.4 and 4.6. Test–retest reliability for the section scores were fair to good or excellent; weighted kappa values ranged from .62 to .83. All items but 1 showed fair to good or excellent test–retest reliability, and percentage agreement ranged from 61% to 100%. Conclusions The mini-BESTest demonstrated good to excellent test–retest reliability and small measurement errors and is recommended for use in people with mild to moderate MS. Impact Knowledge of limits of agreement and minimal detectable change contribute to interpretability of the mini-BESTest total score. The findings of this study enhance the clinical usefulness of the test for evaluation of balance control and for designing individually customized balance training with high precision and accuracy in people with MS.

Fetoplacental Blood Volume Estimation in Pregnancies with Rh Alloimmunization

1990 ◽  
Vol 5 (3-4) ◽  
pp. 138-146 ◽  
Author(s):  
Line Leduc ◽  
Kenneth J. Moise, Jr. ◽  
Robert J. Carpenter, Jr. ◽  
Lorraine E. Cano
Keyword(s):  
Blood Volume ◽  
Volume Estimation

Guidelines for choosing volume equations in the presence of measurement error in height

2000 ◽  
Vol 30 (2) ◽  
pp. 306-310 ◽  
Author(s):  
M S Williams ◽  
H T Schreuder
Keyword(s):  
Measurement Error ◽  
Tree Species ◽  
Measurement Errors ◽  
Tree Diameter ◽  
Total Height ◽  
Volume Equations

Assuming volume equations with multiplicative errors, we derive simple conditions for determining when measurement error in total height is large enough that only using tree diameter, rather than both diameter and height, is more reliable for predicting tree volumes. Based on data for different tree species of excurrent form, we conclude that measurement errors up to ±40% of the true height can be tolerated before inclusion of estimated height in volume prediction is no longer warranted.

scholarly journals An improved computational method to assess pituitary responsiveness to secretagogue stimuli

2002 ◽  
pp. 323-332 ◽  
Author(s):  
A Sartorio ◽  
G De Nicolao ◽  
D Liberati
Keyword(s):  
Measurement Error ◽  
Measurement Errors ◽  
Pituitary Hormones ◽  
Computational Method ◽  
Kinetics Parameters ◽  
Thyrotrophin Releasing Hormone ◽  
Deconvolution Analysis ◽  
Releasing Hormone ◽  
Sampling Protocols ◽  
Peak Value

OBJECTIVE: The quantitative assessment of gland responsiveness to exogenous stimuli is typically carried out using the peak value of the hormone concentrations in plasma, the area under its curve (AUC), or through deconvolution analysis. However, none of these methods is satisfactory, due to either sensitivity to measurement errors or various sources of bias. The objective was to introduce and validate an easy-to-compute responsiveness index, robust in the face of measurement errors and interindividual variability of kinetics parameters. DESIGN: The new method has been tested on responsiveness tests for the six pituitary hormones (using GH-releasing hormone, thyrotrophin-releasing hormone, gonadotrophin-releasing hormone and corticotrophin-releasing hormone as secretagogues), for a total of 174 tests. Hormone concentrations were assayed in six to eight samples between -30 min and 120 min from the stimulus. METHODS: An easy-to-compute direct formula has been worked out to assess the 'stimulated AUC', that is the part of the AUC of the response curve depending on the stimulus, as opposed to pre- and post-stimulus spontaneous secretion. The weights of the formula have been reported for the six pituitary hormones and some popular sampling protocols. RESULTS AND CONCLUSIONS: The new index is less sensitive to measurement error than the peak value. Moreover, it provides results that cannot be obtained from a simple scaling of either the peak value or the standard AUC. Future studies are needed to show whether the reduced sensitivity to measurement error and the proportionality to the amount of released hormone render the stimulated AUC indeed a valid alternative to the peak value for the diagnosis of the different pathophysiological states, such as, for instance, GH deficits.

scholarly journals BLOOD VOLUME ESTIMATION IN NEONATES USING 99m-TC-LABELLED ERYTHROCYTES AND EVANS BLUE

1987 ◽  
Vol 22 (2) ◽  
pp. 219-219
Author(s):  
O Linderkamp ◽  
K Lorenzen ◽  
C Schmid ◽  
H T Versmold ◽  
K P Riegel
Keyword(s):  
Blood Volume ◽  
Evans Blue ◽  
Volume Estimation

Cerebral blood volume estimation by ferumoxytol-enhanced steady-state MRI at 9.4 T reveals microvascular impact of α1 -adrenergic receptor antibodies

2014 ◽  
Vol 27 (9) ◽  
pp. 1085-1093 ◽  
Author(s):  
Andreas Pohlmann ◽  
Peter Karczewski ◽  
Min-Chi Ku ◽  
Babette Dieringer ◽  
Helmar Waiczies ◽  
...  
Keyword(s):  
Steady State ◽  
Blood Volume ◽  
Adrenergic Receptor ◽  
Cerebral Blood Volume ◽  
Volume Estimation ◽  
Receptor Antibodies
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