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      Psychophysical Validation of a Novel Active Learning Approach for Measuring the Visual Acuity Behavioral Function

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          Abstract

          Purpose

          To evaluate the performance of the quantitative visual acuity (qVA) method in measuring the visual acuity (VA) behavioral function.

          Methods

          We evaluated qVA performance in terms of the accuracy, precision, and efficiency of the estimated VA threshold and range in Monte Carlo simulations and a psychophysical experiment. We also compared the estimated VA threshold from the qVA method with that from the Electronic Early Treatment Diabetic Retinopathy Study (E-ETDRS) and Freiburg Visual Acuity Text (FrACT) methods. Four repeated measures with all three methods were conducted in four Bangerter foil conditions in 14 eyes.

          Results

          In both simulations and psychophysical experiment, the qVA method quantified the full acuity behavioral function with two psychometric parameters (VA threshold and VA range) with virtually no bias and with high precision and efficiency. There was a significant correlation between qVA estimates of VA threshold and range in the psychophysical experiment. In addition, qVA threshold estimates were highly correlated with those from the E-ETDRS and FrACT methods.

          Conclusions

          The qVA method can provide an accurate, precise, and efficient assessment of the full acuity behavioral function with both VA threshold and range.

          Translational Relevance

          The qVA method can accurately, precisely, and efficiently assess the full VA behavioral function. Further research will evaluate the potential value of these rich measures for both clinical research and patient care.

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          Most cited references87

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          STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT

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            Measuring agreement in method comparison studies.

            Agreement between two methods of clinical measurement can be quantified using the differences between observations made using the two methods on the same subjects. The 95% limits of agreement, estimated by mean difference +/- 1.96 standard deviation of the differences, provide an interval within which 95% of differences between measurements by the two methods are expected to lie. We describe how graphical methods can be used to investigate the assumptions of the method and we also give confidence intervals. We extend the basic approach to data where there is a relationship between difference and magnitude, both with a simple logarithmic transformation approach and a new, more general, regression approach. We discuss the importance of the repeatability of each method separately and compare an estimate of this to the limits of agreement. We extend the limits of agreement approach to data with repeated measurements, proposing new estimates for equal numbers of replicates by each method on each subject, for unequal numbers of replicates, and for replicated data collected in pairs, where the underlying value of the quantity being measured is changing. Finally, we describe a nonparametric approach to comparing methods.
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              QUEST: a Bayesian adaptive psychometric method.

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                Author and article information

                Journal
                Transl Vis Sci Technol
                Transl Vis Sci Technol
                tvst
                TVST
                Translational Vision Science & Technology
                The Association for Research in Vision and Ophthalmology
                2164-2591
                04 January 2021
                January 2021
                : 10
                : 1
                : 1
                Affiliations
                [1 ]Center for Neural Science, New York University, New York, NY, USA
                [2 ]Adaptive Sensory Technology, San Diego, CA, USA
                [3 ]Technical University of Munich, Munich, Germany
                [4 ]Department of Psychology, Northeastern University, Boston, MA, USA
                [5 ]Division of Arts and Sciences, NYU Shanghai, Shanghai, China
                [6 ]Department of Psychology, New York University, New York, NY, USA
                [7 ]NYU-ECNU Institute of Brain and Cognitive Neuroscience, Shanghai, China
                Author notes
                Correspondence: Zhong-Lin Lu, Center for Neural Science, New York University, 4 Washington Place, Room 621, New York, NY 10003, USA. e-mail: zhonglin@ 123456nyu.edu
                Article
                TVST-20-2251
                10.1167/tvst.10.1.1
                7794273
                33505768
                af743239-67e3-481d-9f25-3506408b3bd1
                Copyright 2021 The Authors

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

                History
                : 01 December 2020
                : 10 January 2020
                Page count
                Pages: 20
                Categories
                Methods
                Methods

                visual acuity,qva,precision,accuracy,efficiency
                visual acuity, qva, precision, accuracy, efficiency

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