| Abstract: | Many researchers index mood variability by a within-Ss standard deviation computed from mood ratings provided by single Ss on several occasions. I argue that this index is theoretically limited because it refers mainly to the average extremity of mood change and not the frequency of change and that time-series techniques be used to better represent emotional variability. The studies here illustrate how one class of time-series techniques—spectral analysis—can be applied to daily mood measures to index the frequency of mood shifts. The convergent validity of spectral estimates of mood change frequency is assessed relative to self-report and parental-report measures of emotional reactivity. The divergent validity of the spectral estimates of mood change frequency is assessed by examining their relation to the within-subjects standard deviation computed from daily mood assessments. Results suggest that the spectral approach provides an adequate index of mood change frequency that is independent of mood change extremity, helps clarify the meaning of emotional variability, and provides a new class of analytic strategies for inclusion in the idiographic-nomothetic paradigm. (PsycINFO Database Record (c) 2010 APA, all rights reserved) |
