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A Monte Carlo comparison of measures of relative end albsolute monitoring accuracy

机译：相对末端绝对监测精度的测量值的蒙特卡罗比较

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摘要

Researchers studying monitoring accuracy currently use two different indexes to estimate accuracy: relative accuracy and absolute accuracy. The authors compared the distributional properties of two measures of monitoring accuracy using Monte Carlo procedures that fit within these categories. They manipulated the accuracy of judgments (i.e., chance level or 60% and above) and the number of items per test (i.e., 20, 50, or 1,000) using 10,000 computer-generated cases. Gamma, an estimate of relative accuracy, yielded a skewed, leptokurtic distribution under the 50-item, 60% accuracy conditions. The Hamann coefficient, an estimate of absolute accuracy, yielded a normal distribution under the same conditions. Both statistics yielded normal distributions under the 1,000item, 60% conditions, although parameter estimates differed widely. The two statistics were similar, and normally distributed, under the 50- and 1,000-item, chance conditions. Recommendations are made regarding the use of each measure in applied monitoring accuracy research.
机译：目前，研究监视精度的研究人员使用两个不同的指标来估计精度：相对精度和绝对精度。作者使用适合这些类别的蒙特卡洛方法比较了两种监测精度的分布特性。他们使用10,000台计算机生成的案例来操纵判断的准确性（即机会级别或60％或更高）和每次测试的项目数（即20、50或1,000）。相对准确度的估算值Gamma在50个项目，60％准确度条件下产生了偏态的瘦角质子分布。 Hamann系数（绝对精度的估计值）在相同条件下产生正态分布。尽管参数估计值相差很大，但两种统计都在1000个项目，60％的条件下得出正态分布。这两个统计量相似，并且在50和1,000个项目的机会条件下呈正态分布。建议在应用的监视精度研究中使用每种度量。

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