1.1本试验方法描述了将单极幅度估计应用于感官属性幅度评估的程序。该测试方法涵盖了评估员培训程序，以产生震级估计和估计的统计评估。 1.2震级估计是一种心理物理标度技术，其中评估员为属性的震级指定数值。对评估员的唯一约束是分配的值应符合比率原则。例如，如果与样本A相比，样本B中的属性强度似乎是样本A的两倍，则样本B应收到一个值，该值是分配给样本A的值的两倍。 1.3可以使用幅度估计来评估属性的强度，如愉悦度、甜度、咸度或柔软度。 1.4震级估计可能比其他定标方法具有优势，尤其是在评估人员数量和可用培训时间有限的情况下。通过大约1小时的训练，一个由15到20名未成年人组成的小组可以产生足够精度和再现性的数据。为确保评估员能够正确识别正在评估的属性而可能需要的任何额外培训都不在本测试方法的范围内。 ====意义和用途====== 震级估计可用于测量和比较各种产品的属性强度。 幅度估计为实验者和评估者提供了很大程度的灵活性。一旦接受了震级估计方面的培训，评估人员通常能够将其技能应用于各种样本类型和属性，只需最少的额外培训。 震级估计不像区间缩放技术那样容易受到末端效应的影响。当评估人员不熟悉所呈现的整个感觉范围时，可能会发生这种情况。在这种情况下，评估员可以将早期样本分配给过于接近量表一端的类别。随后，他们可能会 “ 超出比例 ” 并被迫将感知不同的样本分配给同一类别。 这不应该发生在震级估计中，因为在理论上，有无限多的类别。 震级估计是一种常用的技术，允许根据史蒂文斯幂律表示数据。 震级估计的缺点主要来自数据分析的要求。 允许每个评估员选择不同的数字量表可能会产生显著的评估员效应。这一缺点可以通过以下几种方式克服。实验者必须选择最适合环境的方法。 可以设计实验，以便使用方差分析来消除评估者效应和相互作用。 或者，可以通过培训或使用具有指定值（模数）的外部参考样本，迫使评估员使用通用量表。 最后，可以通过多种规范化方法之一将每个评估员的数据带到一个通用的尺度。 在进行数据分析之前，必须应用对数。如果数值接近阈值，则会出现问题，因为无法取零的对数（见11.2.1）。 应使用震级估计: 当终端效应是一个问题时，例如当评估人员不熟悉所呈现的整个感觉范围时。 当史蒂文斯幂定律应用于数据时。 一般来说，在中央位置测试中，评估员接受过该技术的培训。它不适用于家用或商场拦截测试。 该测试方法仅适用于在震级估计方面受过专门培训的评估员。不要对未经培训的评估员或未经培训的消费者使用此方法。

1.1 This test method describes a procedure for the application of unipolar magnitude estimation to the evaluation of the magnitude of sensory attributes. The test method covers procedures for the training of assessors to produce magnitude estimations and statistical evaluation of the estimations. 1.2 Magnitude estimation is a psychophysical scaling technique in which assessors assign numeric values to the magnitude of an attribute. The only constraint placed upon the assessor is that the values assigned should conform to a ratio principle. For example, if the attribute seems twice as strong in sample B when compared to sample A, sample B should receive a value which is twice the value assigned to sample A. 1.3 The intensity of attributes such as pleasantness, sweetness, saltiness or softness can be evaluated using magnitude estimation. 1.4 Magnitude estimation may provide advantages over other scaling methods, particularly when the number of assessors and the time available for training are limited. With approximately 1 h of training, a panel of 15 to 20 naive individuals can produce data of adequate precision and reproducibility. Any additional training that may be required to ensure that the assessors can properly identify the attribute being evaluated is beyond the scope of this test method. ====== Significance And Use ====== Magnitude estimation may be used to measure and compare the intensities of attributes of a wide variety of products. Magnitude estimation provides a large degree of flexibility for both the experimenter and the assessor. Once trained in magnitude estimation, assessors are generally able to apply their skill to a wide variety of sample types and attributes, with minimal additional training. Magnitude estimation is not as susceptible to end-effects as interval scaling techniques. These can occur when assessors are not familiar with the entire range of sensations being presented. Under these circumstances, assessors may assign an early sample to a category which is too close to one end of the scale. Subsequently, they may “ run out of scale ” and be forced to assign perceptually different samples to the same category. This should not occur with magnitude estimation, as, in theory, there are an infinite number of categories. Magnitude estimation is one frequently used technique that permits the representation of data in terms of Stevens' Power Law. The disadvantages of magnitude estimation arise primarily from the requirements of the data analysis. Permitting each assessor to choose a different numerical scale may produce significant assessor effects. This disadvantage can be overcome in a number of ways, as follows. The experimenter must choose the approach most appropriate for the circumstances. Experiments can be designed such that analysis of variance can be used to remove the assessor effects and interactions. Alternatively, assessors can be forced to a common scale, either by training or by use of external reference samples with assigned values (modulus). Finally, each assessor's data can be brought to a common scale by one of a variety of normalizing methods. Logarithms must be applied before carrying out data analysis. This becomes problematic if values are near threshold, as a logarithm of zero cannot be taken (see 11.2.1). Magnitude estimation should be used: When end-effects are a concern, for example when assessors are not familiar with the entire range of sensations being presented. When Stevens' Power Law is to be applied to the data. Generally, in central location testing with assessors trained in the technique. It is not appropriate for home use or mall intercept testing with consumers. This test method is only meant to be used with assessors who are specifically trained in magnitude estimation. Do not use this method with untrained assessors or untrained consumers.