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Threshold estimation in two-alternative forced-choice (2AFC) tasks: The Spearman–K?rber method

机译:两种选择的强制选择(2AFC)任务中的阈值估计:Spearman–K?rber方法

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The Spearman–K?rber method can be used to estimate the threshold value or difference limen in two-alternative forced-choice tasks. This method yields a simple estimator for the difference limen and its standard error, so that both can be calculated with a pocket calculator. In contrast to previous estimators, the present approach does not require any assumptions about the shape of the true underlying psychometric function. The performance of this new nonparametric estimator is compared with the standard technique of probit analysis. The Spearman–K?rber method appears to be a valuable addition to the toolbox of psychophysical methods, because it is most accurate for estimating the mean (i.e., absolute and difference thresholds) and dispersion of the psychometric function, although it is not optimal for estimating percentile-based parameters of this function.
机译:Spearman–K?rber方法可用于估计两个备选强制选择任务中的阈值或差异。此方法可得出差值灰阶及其标准误差的简单估算器,因此两者都可以使用袖珍计算器进行计算。与先前的估计方法相比,本方法不需要对真实的基础心理测量函数的形状进行任何假设。将该新的非参数估计器的性能与概率分析的标准技术进行了比较。 Spearman-K?rber方法似乎是心理物理方法工具箱的重要补充,因为它对于估计心理测量函数的平均值(即绝对阈值和差异阈值)和离散度最为准确,尽管它并非最佳方法。估计此函数基于百分位数的参数。

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