a Neuropsychology , Cleveland Clinic Lou Ruvo Center for Brain Health , Las Vegas , NV , USA.
b Department of Neurology , Center for Alzheimer's Care, Imaging, and Research University of Utah , Salt Lake City , UT , USA.
J Clin Exp Neuropsychol. 2019 Jul;41(5):460-468. doi: 10.1080/13803395.2019.1571169. Epub 2019 Feb 5.
Standardized regression based (SRB) methods can be used to determine whether meaningful changes in performance on cognitive assessments occur over time. Both raw and standardized scores have been used in SRB models but it is unclear which score metric is most appropriate for predicting follow-up performance. The aim of the present study was to examine differences in SRB prediction formulas using raw versus standard scores on two memory tests commonly used in assessment of older adults.
The sample consisted of 135 healthy older adults who underwent baseline and 1-year follow-up neuropsychological assessment including the Hopkins Verbal Learning Test-Revised and Brief Visuospatial Memory Test-Revised. Regression models were fit to predict Time 2 scores from Time 1 scores and demographic variables. Separate models were fit using raw scores and standardized scores. Akaike's information criterion (AIC) was used to determine whether models using raw or standardized scores resulted in best fit. Pearson correlation and intraclass correlation coefficients were calculated between observed and predicted scores. Mean differences between observed and predicted scores were examined using pairwise t tests. To investigate whether a similar pattern of results would be evident using prediction formulas for nonmemory tests, all analyses were also conducted for nonmemory tests.
All regression models were significant, and R values for memory test raw score models were larger than those generated by standardized score models. Memory test raw score models were also a better fit based on smaller AIC values. For nonmemory tests, raw score models did not consistently outperform standardized score models. All correlations between observed and predicted Time 2 scores were significant, and none of the predicted scores significantly differed from their respective observed score.
For each memory measure, raw score models outperformed standardized score models. For nonmemory tests, neither score metric model consistently outperformed the other.
基于标准化回归（SRB）的方法可用于确定认知评估的表现是否随着时间的推移而发生有意义的变化。SRB 模型中既使用了原始分数又使用了标准化分数，但尚不清楚哪种分数指标最适合预测随访表现。本研究的目的是检查在使用两种常用于评估老年人的记忆测试的原始分数和标准分数时，SRB 预测公式的差异。
该样本包括 135 名健康的老年人，他们接受了基线和 1 年随访的神经心理学评估，包括霍普金斯言语学习测试修订版和简要视觉空间记忆测试修订版。使用时间 1 分数和人口统计学变量拟合回归模型以预测时间 2 分数。使用原始分数和标准化分数分别拟合模型。使用赤池信息量准则（AIC）来确定使用原始分数或标准化分数的模型是否导致最佳拟合。计算了观察得分和预测得分之间的 Pearson 相关系数和组内相关系数。使用配对 t 检验检查观察得分和预测得分之间的平均差异。为了研究使用非记忆测试的预测公式是否会出现类似的结果模式，所有分析也针对非记忆测试进行了。
所有回归模型均具有统计学意义，并且记忆测试原始分数模型的 R 值大于标准化分数模型。基于较小的 AIC 值，记忆测试原始分数模型的拟合效果也更好。对于非记忆测试，原始分数模型并不总是优于标准化分数模型。观察得分和预测得分之间的所有相关性均具有统计学意义，且没有一个预测得分与其各自的观察得分显著不同。
对于每种记忆测量，原始分数模型均优于标准化分数模型。对于非记忆测试，两种分数指标模型均未始终优于另一种。
