Swanson W H, Birch E E
Retina Foundation of the Southwest, Dallas, Texas 75231.
Percept Psychophys. 1992 May;51(5):409-22. doi: 10.3758/bf03211637.
Psychophysical studies with infants or with patients often are unable to use pilot data, training, or large numbers of trials. To evaluate threshold estimates under these conditions, computer simulations of experiments with small numbers of trials were performed by using psychometric functions based on a model of two types of noise: stimulus-related noise (affecting slope) and extraneous noise (affecting upper asymptote). Threshold estimates were biased and imprecise when extraneous noise was high, as were the estimates of extraneous noise. Strategies were developed for rejecting data sets as too noisy for unbiased and precise threshold estimation; these strategies were most successful when extraneous noise was low for most of the data sets. An analysis of 1,026 data sets from visual function tests of infants and toddlers showed that extraneous noise is often considerable, that experimental paradigms can be developed that minimize extraneous noise, and that data analysis that does not consider the effects of extraneous noise may underestimate test-retest reliability and overestimate interocular differences.
针对婴儿或患者的心理物理学研究通常无法使用预试验数据、培训或大量试验。为了评估在这些条件下的阈值估计，通过使用基于两种噪声模型的心理测量函数，对少量试验的实验进行了计算机模拟：与刺激相关的噪声（影响斜率）和外部噪声（影响上渐近线）。当外部噪声较高时，阈值估计存在偏差且不精确，外部噪声的估计也是如此。开发了一些策略来拒绝那些因噪声过大而无法进行无偏且精确阈值估计的数据集；当大多数数据集的外部噪声较低时，这些策略最为成功。对1026例婴幼儿视觉功能测试数据集的分析表明，外部噪声通常相当可观，可以开发出将外部噪声降至最低的实验范式，并且不考虑外部噪声影响的数据分析可能会低估重测信度并高估两眼间差异。
