Time series analysis for psychological research: examining and forecasting change.

The results of the analysis indicated that there was a practically significant effect of the crisis: The parameter representing an immediate change in the post-event level was b 2 = 8.66, p < 0.001.

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Along with a marked trend, the series in Figure 1 exhibits noticeable seasonal fluctuations as well; at the beginning of each year (i.e., after the holiday months), online job searches spike and then fall significantly in February.

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Globally, the illustrative time series shown in Figure 1 exhibits a positive trend: The level of the series at the end is systematically higher than at its beginning.

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It is more likely that either (a) a negative trend will return the series back to more moderate levels or (b) the series will simply continue at a generally high level.

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Modeling trends through regression Modeling an observed trend in a time series through regression is appropriate when the trend is deterministic —i.e., the trend is due to the constant, deterministic effects of a few causal forces (McCleary et al., 1980 , p. 34).

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