With the growing popularity of intensive longitudinal research, the modeling techniques and software options for such data are also expanding rapidly. Here we use dynamic multilevel modeling, as it is incorporated in the new dynamic structural equation modeling (DSEM) toolbox in Mplus, to analyze the affective data from the COGITO study. These data consist of two samples of over 100 individuals each who were measured for about 100 days. We use composite scores of positive and negative affect and apply a multilevel vector autoregressive model to allow for individual differences in means, autoregressions, and cross-lagged effects. Then we extend the model to include random residual variances and covariance, and finally we investigate whether prior depression affects later depression scores through the random effects of the daily diary measures. We end with discussing several urgent-but mostly unresolved-issues in the area of dynamic multilevel modeling.
We thank our student research assistants and interns for their help with the data collection. We would also like to express our gratitude to our participants. This is a study containing multiple data sets from different laboratories. Results from these datasets were previously published to test different research questions. A list of the publications pertaining to each data set is provided in the Method section of the manuscript.We report how we determined our sample sizes, all exclusions of participants, and all measures as relevant for the research questions. There were no manipulations. Results reported in this manuscript were previously presented as a flash talk at the Annual Conference of the Society for Affective Science 2017 in Boston, MA, USA.
Across days, individuals experience varying levels of negative affect, control of attention, and motivation. We investigated whether this intraindividual variability was coupled with daily fluctuations in working memory (WM) performance. In 100 days, 101 younger individuals worked on a spatial N-back task and rated negative affect, control of attention, and motivation. Results showed that individuals differed in how reliably WM performance fluctuated across days, and that subjective experiences were primarily linked to performance accuracy. WM performance was lower on days with higher levels of negative affect, reduced control of attention, and reduced task-related motivation. Thus, variables that were found to predict WM in betweensubjects designs showed important relationships to WM at the within-person level. In addition, there was shared predictive variance among predictors of WM. Days with increased negative affect and reduced performance were also days with reduced control of attention and reduced motivation to work on tasks. These findings are in line with proposed mechanisms linking negative affect and cognitive performance.
This study tested whether the structure of affect observed on the basis of between-person (BP) differences is equivalent to the affect structures that organize the variability of affective states within persons (WP) over time. Further aims were to identify individual differences in the degree of divergence between the WP and BP structure and examine its association to dispositional and contextual variables (neuroticism, extraversion, well-being and stress). In 100 daily sessions, 101 younger adults rated their mood on the Positive and Negative Affect Schedule. Variability of five negative affect items across time was so low that they were excluded from the analyses. We thus worked with a modified negative affect subscale. WP affect structures diverged reliably from the BP structure, with individual differences in the degree of divergence. Differences in the WP structural characteristics and the degree of divergence could be predicted by well-being and stress. We conclude that BP and WP structures of affect are not equivalent and that BP and WP variation should be considered as distinct phenomena. It would be wrong, for example, to conceive of positive and negative affect as independent at the WP level, as suggested by BP findings. Yet, individual differences in WP structural characteristics are related to stable BP differences, and the degree to which individuals' affect structures diverge from the BP structure can provide important insights into intraindividual functioning.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.