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Testing Process Factor Analysis Models Using the Parametric Bootstrap
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DOI：10.1080/00273171.2017.1415123.png)
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Abstract
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Process factor analysis (PFA) is a latent variable model for intensive longitudinal data. It combines P-technique factor analysis and time series analysis. The goodness-of-fit test in PFA is currently unavailable. In the paper, we propose a parametric bootstrap method for assessing model fit in PFA. We illustrate the test with an empirical data set in which 22 participants rated their effects everyday over a period of 90 days. We also explore Type I error and power of the parametric bootstrap test with simulated data.
Keywords:
Dynamic factor analysis
time series analysis
parametric bootstrap
intensive longitudinal data
model testing
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