Search results
Jun 8, 2015 · Second, different time series modeling techniques are surveyed that can address various topics of interest to psychological researchers, including describing the pattern of change in a variable, modeling seasonal effects, assessing the immediate and long-term impact of a salient event, and forecasting future values.
Jun 9, 2015 · Second, different time series modeling techniques are surveyed that can address various topics of interest to psychological researchers, including describing the pattern of change in a variable, modeling seasonal effects, assessing the immediate and long-term impact of a salient event, and forecasting future values.
- Andrew T. Jebb, Louis Tay, Wei Wang, Qiming Huang
- 10.3389/fpsyg.2015.00727
- 2015
- Front Psychol. 2015; 6: 727.
People also ask
Can time series be used in psychological research?
Why is time series analysis important in psychology?
Should time-series methods be used in psychological research?
What are the characteristics of a time series?
- Measuring Behavior as A Time Series
- Analyzing Time-Series Data
- Applying These Techniques to Your Research
- References and Further Reading
According to Daniel T. Kaplan and Leon Glass (1995), there are two critical features of a time series that differentiate it from cross-sectional data-collection procedures: 1. Repeated measurements of a given behavior are taken across time at equally spaced intervals.Taking multiple measurements is essential for understanding how any given behavior...
Once you’ve collected a series of behavioral measurements on your variable(s) of interest, there are a variety of ways to explore and quantify the observed dynamics. Here are a few techniques that can be used to investigate patterns within time-series data: Autocorrelation/Cross-correlation. An autocorrelation reflects the magnitude of time depende...
Though these methods may appear foreign and somewhat challenging at first, they quickly become more intuitive once seen in an applied context. The above list represents only some of the more common techniques used in time-series analysis, especially those that have been applied successfully within the psychological sciences.
Deboeck, P. R., & Bergeman, C. S. (2013). The reservoir model: A differential equation model of psychological regulation. Psychological Methods, 18, 237–256. Deboeck, P. R., Montpetit, M. A., Bergeman, C. S., & Boker, S. M. (2009). Using derivative estimates to describe intraindividual variability at multiple time scales. Psychological Methods, 14,...
- Trevor Swanson
- 2016
A cross-correlation involves relating two time series that are shifted in time at lag n (i.e., Xt and Yt+n), and can reveal, for example, whether one process tends to “lead” the other’s behavior or whether they oscillate together. Recurrence quantification analysis (RQA). RQA begins by simply plotting a time series against itself
Mar 19, 2015 · Second, different time series modeling techniques are surveyed that can address various topics of interest to psychological researchers, including describing the pattern of change in a variable, modeling seasonal effects, assessing the immediate and long-term impact of a salient event, and forecasting future values.
- Andrew T. Jebb, Louis Tay, Wei Wang, Qiming Huang
- 2015
Apr 16, 2020 · Multivariate time series techniques that treat variables as an interacting dynamic system, revealing their internal dynamics, represent relevant tools for understanding behavior or other psychological phenomena.
Jul 23, 2020 · In this paper, we will introduce four techniques to interpret and analyze high-density multi-modal behavior data, namely, to: (1) visualize the raw time series, (2) describe the overall distributional structure of temporal events (Burstiness calculation), (3) characterize the non-linear dynamics over multiple timescales with Chromatic and Anisot...
