We tried to cover a lot of ground, but the main aims were: 1) Are there meaningful individual differences in longitudinal within-person variability? 2) How do they relate to variables important for other trait metrics? 3) Can we do an initial test of their utility? (2/8)

For Aim 1, the answer was a resounding YES 🫡 Substantial heterogeneity in within-person variability around Big Five trajectories emerged across all datasets & traits Variability in sigma was comparable to - & sometimes even surpassed - variability in intercepts & slopes (3/8)

For Aim 2, they do relate & do so in expected ways! Individual differences in within-person variability were related to variables like age, gender, cognitive ability, & other trait levels All effects emerged independent of effects rather due to trait levels or changes (4/8)

For Aim 3, it appears that within-person variability has the potential to be a metric with valuable predictive utility! This individual difference predicted health status by itself, over & above people’s trait levels and changes, and had some notable interactions as well (5/8)

There are so many other (in my opinion) super cool findings in the paper, so hopefully the brief summary piqued your interests Also, basically any random parameters or estimates you could want to know are in the supplementary materials - a lot of neat stuff ended up there! (6/8)

This paper is the bulk of my dissertation & my last main project I did in grad school, so it has a special place in my heart :’-) It also completely took over my life for those final 5 months of grad school, so I hope at least one other person enjoys it! (7/8)