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偏差对大小和比率估计幂函数指数的影响。

Bias effects on magnitude and ratio estimation power function exponents.

作者信息

Fagot R F, Pokorny R

出版信息

Percept Psychophys. 1989 Mar;45(3):221-30. doi: 10.3758/bf03210701.

Abstract

A bias model of relative judgment was used to derive a ratio estimation (RE) power function, and its effectiveness in providing estimates of exponents free of the effects of standards was evaluated. The RE bias model was compared with the simple RE power function that ignores bias. Results showed that when bias was not taken into account, estimates of exponents exhibited the usual effects of standards observed in previous research. However, the introduction of bias parameters into the RE power function virtually eliminated these effects. Exponents calculated from "equal-range segments" (e.g., low stimulus range vs. high stimulus range) judged by magnitude estimation (ME) were examined: the effects of equal-range segments on exponents were much stronger for ME than standards were for RE, using the bias model.

摘要

使用相对判断的偏差模型来推导比率估计(RE)幂函数,并评估其在提供不受标准影响的指数估计方面的有效性。将RE偏差模型与忽略偏差的简单RE幂函数进行比较。结果表明,当不考虑偏差时,指数估计表现出先前研究中观察到的标准的常见影响。然而,在RE幂函数中引入偏差参数实际上消除了这些影响。研究了通过数量估计(ME)判断的“等范围段”(例如,低刺激范围与高刺激范围)计算出的指数:使用偏差模型,等范围段对ME指数的影响比对RE标准的影响要强得多。

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