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Comparison of Methods to Predict Visual Field Progression in Glaucoma
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Spatial Characteristics of Visual Field Progression Determined by Monte Carlo Simulation: Diagnostic Innovations in Glaucoma Study
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IOVS 2007;48:1642-1650.
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Visual Field Progression in Glaucoma: Total Versus Pattern Deviation Analyses
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Normal Visual Field Test Results Following Glaucomatous Visual Field End Points in the Ocular Hypertension Treatment Study
Keltner et al.
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Appearance of the Pattern Deviation Map as a Function of Change in Area of Localized Field Loss
Asman et al.
IOVS 2004;45:3099-3106.
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Normal Intersubject Threshold Variability and Normal Limits of the SITA SWAP and Full Threshold SWAP Perimetric Programs
Bengtsson and Heijl
IOVS 2003;44:5029-5034.
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The Collaborative Initial Glaucoma Treatment Study: Baseline Visual Field and Test-Retest Variability
Gillespie et al.
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A New Rapid Threshold Algorithm for Short-Wavelength Automated Perimetry
Bengtsson
IOVS 2003;44:1388-1394.
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The Long-Term Fluctuation of the Visual Field in Stable Glaucoma
Hutchings et al.
IOVS 2000;41:3429-3436.
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A Comparison of the Pattern- and Total Deviation-Based Glaucoma Change Probability Programs
Katz
IOVS 2000;41:1012-1016.
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Multivariate Approach for Quantification of Morphologic and Functional Damage in Glaucoma
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IOVS 2000;41:1099-1110.
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Open-Angle Glaucoma
Quigley
NEJM 1993;328:1097-1106.
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Comparison of Analytic Algorithms for Detecting Glaucomatous Visual Field Loss
Katz et al.
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Visual Field Interpretation With Empiric Probability Maps
Johnson
Arch Ophthalmol 1989;107:1423-1423.
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Automated Perimetry: How Do We Interpret the Results?
Wilensky
Arch Ophthalmol 1989;107:185-186.
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