Valentine John, Simpson Janet M
Department of Psychology, Royal Holloway University of London, Surrey, UK.
Clin Rehabil. 2002 Dec;16(8):837-42. doi: 10.1191/0269215502cr568oa.
Our purpose is to help clinicians decide whether a measured change in a patient's performance, usually in the direction of improvement, is likely to represent a true change. We set out the calculations to derive a minimal statistically significant change in certain measures commonly used in evaluating the outcome of rehabilitation. Many of these test measurements, e.g. walking time, are likely to show increased variability within patients as the mean level of performance increases in magnitude. We pay particular attention to the calculations in this case as the data should be transformed to remove the relationship by taking their natural logarithm. Confidence interval calculations for single measurements and for differences between two measurements (using the repeatability coefficient) are given both for data that show and for data that do not show a relation between variation and level of performance.
我们的目的是帮助临床医生判断患者表现的测量变化（通常朝着改善的方向）是否可能代表真正的变化。我们列出了计算方法，以得出在评估康复结果时常用的某些测量指标中具有统计学意义的最小变化值。随着表现平均水平在数值上的增加，许多这些测试测量值，例如步行时间，在患者体内可能会显示出更大的变异性。在这种情况下，我们特别关注计算，因为数据应通过取自然对数进行转换以消除这种关系。对于显示和未显示变异与表现水平之间关系的数据，都给出了单次测量以及两次测量之间差异（使用重复性系数）的置信区间计算。
