Chapter 26: Time Series Models for Examining Psychological Processes: Applications and New Developments

Emilio Ferrer & Guangjian Zhang

Time series models for examining psychological processes: Applications and new developments Psychological processes are dynamic phenomena. They unfold over time and involve time-lagged sequences. To capture this dynamic nature, there is an unavoidable need for intensive data that reflect the changes (e.g., fluctuations, trends) and the time dependency embedded in the processes. Similarly, the analysis of such intense repeated measurement needs statisticaltools that can adequately identify the psychological mechanisms underlying the observed data. One type of statistical techniques suited for modeling psychological processes is time series analysis. Time series models were developed to deal with intense data repeated over time. They have been a primary tool in areas as diverse as economics, epidemiology and, particularly, the physical and environmental sciences. In most of these disciplines, the exact nature of the system is often predetermined and known, and the attribute to be measured can be directly observable. In psychology, however, the ...

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