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Titlebook: Seventh International Visual Field Symposium, Amsterdam, September 1986; E. L. Greve,A. Heijl Book 1987 Martinus Nijhoff Publishers/Dr W.

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Total variance of serial Octopus visual fields in glaucomatous eyestributed to this disease. A series of eight static threshold fields were performed on each eye over a one month period. For each series, two-way analysis of variance (ANOVA) employing a random-effects model was applied [8,10]. The components of variance were estimated from the ten duplicate threshol
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Estimates of variance in visual field data a visual field in which threshold was determined only once, consderable test time could be-saved. Meridional threshold data from 40 patients and 18 normals was used to test empirically various methods of estimating variance. A variety of time-series analyses, including combinations of moving averag
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Fluctuation and population differences in automated perimetry and the influence on defect volume ests. Our goal was to optimize the determination of the reference field used in our evaluation program for visual fields. We found true interindividual differences in the gradient of sensitivity of the normal visual field. These findings emphasize the importance of individual determination of the refer
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Short-term and long-term fluctuation of thresholds in automated perimetry in normals, ocular hyperteeshold was around 1.5 dB (sd). We broke the Mean Threshold down in two components: the Individual General Sensitivity and the Mean Defect. The Mean Defect proved to be the most stable parameter over time. Thus, for assessment of the pathological state of the visual field the Mean Defect seems to be the better choice.
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Estimates of variance in visual field datadeveloped which produced variance estimates which correlated well with standard mean square calculations. Increases in variance attributed to subject fatigue were observed at the end of a 60 minutes test session in normal subjects.
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