University of Notre Dame.
Multivariate Behav Res. 2021 Jan-Feb;56(1):41-56. doi: 10.1080/00273171.2020.1717414. Epub 2020 Jan 30.
P-technique factor analysis is an exploratory factor model for multivariate time series data. Assessing model fit of P-technique factor models is non-trivial because time series data are correlated at nearby time points. We present a test statistic that is appropriate for P-technique factor analysis. In addition, the test statistic allows researchers to quantify the amount of model error. We explore the statistical properties of the test statistic with simulated data and we illustrate its use with an empirical study of personality states. Results of the simulation study include (1) the empirical distributions of the test statistic approximately followed their respective theoretical chi-square distributions, (2) the empirical Type I error rates of the test of perfect fit are close to the nominal level and the empirical Type I error rates of the test of close fit are slightly lower than the nominal level, and (3) the empirical power rates of the test of perfect fit are satisfactory but the empirical power rates of the test of close fit are only satisfactory for small models.
P 技术因子分析是一种用于多变量时间序列数据的探索性因子模型。评估 P 技术因子模型的拟合度并不简单，因为时间序列数据在附近的时间点是相关的。我们提出了一个适合 P 技术因子分析的检验统计量。此外，该检验统计量允许研究人员量化模型误差的程度。我们使用模拟数据探索了检验统计量的统计性质，并通过人格状态的实证研究说明了其使用方法。模拟研究的结果包括：（1）检验统计量的经验分布近似遵循各自的理论卡方分布；（2）完全拟合检验的经验Ⅰ型错误率接近名义水平，而接近拟合检验的经验Ⅰ型错误率略低于名义水平；（3）完全拟合检验的经验功效率令人满意，但接近拟合检验的经验功效率仅对小模型令人满意。
