How do statistical methods compare the accuracy of eye tracking coordinates over time?
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Statistical methods for comparing the accuracy of eye tracking coordinates over time involve measures such as the standard deviation (SD) and the root mean square (RMS) of the sample-to-sample differences (StoS) signal during fixation. These measures assume certain statistical assumptions, including unimodal distributions, stationarity of the signals, and independence of samples. However, studies have shown that these assumptions are often not met. Position signal distributions are frequently multimodal, position signals are not stationary, and all position signals are statistically significantly autocorrelated. Similarly, StoS signals are often not stationary and are also statistically significantly autocorrelated. These findings call into question the appropriateness of using SD or RMS-StoS as metrics of precision for eye trackers .
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| Papers (4) | Insight |
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28 Mar 2012 27 Citations | The paper discusses the use of statistical measures such as standard deviation, RMS, and BCEA to compare the precision of eye-trackers over time. |
| The paper questions the appropriateness of using statistical methods, such as the standard deviation and RMS error, to measure the accuracy of eye tracking coordinates over time. | |
| The paper does not directly compare the accuracy of eye tracking coordinates over time. It focuses on testing the statistical assumptions underlying the use of standard deviation and RMS as measures of precision for eye-movement fixation. | |
| The provided paper does not specifically compare the accuracy of eye tracking coordinates over time using statistical methods. The paper focuses on analyzing eye tracking scanpaths on web pages. |
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