THE AUTO-REGRESSIVE INTEGRATED MOVING AVERAGE PROCEDURES:

The aims of this tutorial are three-fold: (i) to clarify the meaning of variability measurement in personality and social psychology, (ii) to demonstrate the relevance of and the need for time series analysis in investigations into the dynamics of psychological phenomena, and (iii) to provide specific methods to analyze time series. This paper first presents a step-by-step description of univariate Auto-Regressive-Integrated-Moving-average (ARIMA) procedures, which are useful tools for building iterative models from empirical time series. We then develop two empirical examples in detail, based on the analysis of selfesteem and behavioral data. These examples allow us to present the two most often used models in the psychological literature.

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