Greenwood A C, Landaw E M, Brown T H
Department of Cellular and Molecular Physiology, Yale University, New Haven, Connecticut 06510, USA.
Biophys J. 1999 Apr;76(4):1847-55. doi: 10.1016/S0006-3495(99)77344-3.
Many studies of synaptic transmission have assumed a parametric model to estimate the mean quantal content and size or the effect upon them of manipulations such as the induction of long-term potentiation. Classical tests of fit usually assume that model parameters have been selected independently of the data. Therefore, their use is problematic after parameters have been estimated. We hypothesized that Monte Carlo (MC) simulations of a quantal model could provide a table of parameter-independent critical values with which to test the fit after parameter estimation, emulating Lilliefors's tests. However, when we tested this hypothesis within a conventional quantal model, the empirical distributions of two conventional goodness-of-fit statistics were affected by the values of the quantal parameters, falsifying the hypothesis. Notably, the tests' critical values increased when the combined variances of the noise and quantal-size distributions were reduced, increasing the distinctness of quantal peaks. Our results support two conclusions. First, tests that use a predetermined critical value to assess the fit of a quantal model after parameter estimation may operate at a differing unknown level of significance for each experiment. Second, a MC test enables a valid assessment of the fit of a quantal model after parameter estimation.
许多关于突触传递的研究都采用参数模型来估计平均量子含量和大小，或者诸如长期增强诱导等操作对它们的影响。经典的拟合检验通常假设模型参数是独立于数据选择的。因此，在参数估计之后使用这些检验会存在问题。我们假设量子模型的蒙特卡罗（MC）模拟可以提供一个与参数无关的临界值表，用于在参数估计后检验拟合情况，类似于利利福斯检验。然而，当我们在传统量子模型中检验这个假设时，两个传统拟合优度统计量的经验分布受到量子参数值的影响，从而证伪了这个假设。值得注意的是，当噪声和量子大小分布的组合方差减小时，检验的临界值会增加，这使得量子峰的区别更加明显。我们的结果支持两个结论。第一，在参数估计后使用预定临界值来评估量子模型拟合情况的检验，对于每个实验可能在不同的未知显著性水平下运行。第二，MC检验能够在参数估计后对量子模型的拟合情况进行有效评估。
