The Hitchhiker’s Guide to Longitudinal Models: A Primer on Model Selection for Repeated-Measures Methods

Longitudinal data is becoming increasingly available in developmental neuroimaging. To maximize the promise of this wealth of information on how biology, behavior, and cognition change over time, there is a need to incorporate broad and rigorous training in longitudinal methods into the repertoire of developmental neuroscientists. Fortunately, these models have an incredibly rich tradition in the broader developmental sciences that we can draw from. Here, we provide a primer on longitudinal models, written in a beginner-friendly (and slightly irreverent) manner, with a particular focus on selecting among different modeling frameworks (e.g., multilevel versus latent curve models) to build the theoretical model of development a researcher wishes to test. Our aims are three-fold: 1) lay out a heuristic framework for longitudinal model selection, 2) build a repository of references that ground each model in its tradition of methodological development and practical implementation with a focus on connecting researchers to resources outside traditional neuroimaging journals, and 3) provide practical resources in the form of a codebook companion demonstrating how to fit these models. These resources together aim to enhance training for the next generation of developmental neuroscientists by providing a solid foundation for future forays into advanced modeling applications.

A Guide to Visualizing Trajectories of Change With Confidence Bands and Raw Data

This tutorial is aimed at researchers working with repeated measures or longitudinal data who are interested in enhancing their visualizations of model-implied mean-level trajectories plotted over time with confidence bands and raw data. The intended audience is researchers who are already modeling their experimental, observational, or other repeated measures data over time using random-effects regression or latent curve modeling but who lack a comprehensive guide to visualize trajectories over time. This tutorial uses an example plotting trajectories from two groups, as seen in random-effects models that include Time × Group interactions and latent curve models that regress the latent time slope factor onto a grouping variable. This tutorial is also geared toward researchers who are satisfied with their current software environment for modeling repeated measures data but who want to make graphics using R software. Prior knowledge of R is not assumed, and readers can follow along using data and other supporting materials available via OSF at https://osf.io/78bk5/ . Readers should come away from this tutorial with the tools needed to begin visualizing mean trajectories over time from their own models and enhancing those plots with graphical estimates of uncertainty and raw data that adhere to transparent practices in research reporting.

Changes in Size and Interpretation of Parameter Estimates in Within-Person Models in the Presence of Time-Invariant and Time-Varying Covariates

For several decades, cross-lagged panel models (CLPM) have been the dominant statistical model in relationship research for investigating reciprocal associations between two (or more) constructs over time. However, recent methodological research has questioned the frequent usage of the CLPM because, amongst other things, the model commingles within-person associations with between-person associations, while most developmental research questions pertain to within-person processes. Furthermore, the model presumes that there are no third variables that confound the relationships between the longitudinally assessed variables. Therefore, the usage of alternative models such as the Random-Intercept Cross-Lagged Panel Model (RI-CLPM) or the Latent Curve Model with Structured Residuals (LCM-SR) has been suggested. These models separate between-person from within-person variation and they also control for time constant covariates. However, there might also be third variables that are not stable but rather change across time and that can confound the relationships between the variables studied in these models. In the present article, we explain the differences between the two types of confounders and investigate how they affect the parameter estimates of within-person models such as the RI-CLPM and the LCM-SR.

A guide to visualizing trajectories of change with confidence bands and raw data

This tutorial is aimed at researchers working with repeated measures or longitudinal data who are interested in enhancing their visualizations of model-implied mean-level trajectories plotted over time with confidence bands and raw data. The intended audience is researchers who are already modeling their experimental, observational, or other repeated measures data over time using random effects regression or latent curve modeling, but who lack a comprehensive guide to visualize trajectories over time. This tutorial uses an example plotting trajectories from two groups, as seen in random effects models that include time × group interactions and latent curve models that regress the latent time slope factor onto a grouping variable. This tutorial is also geared toward researchers who are satisfied with their current software environment for modeling repeated measures data but who want to make graphics using R software. Prior knowledge of R is not assumed, and readers can follow along using data and other supporting materials available via OSF at https://osf.io/78bk5/. Readers should come away from this tutorial with the tools needed to begin visualizing mean trajectories over time from their own models and enhancing those plots with graphical estimates of uncertainty and raw data that adhere to transparent practices in research reporting.

Autonomy and loneliness – longitudinal within- and between-person associations among Swedish older adults

Objectives. Loneliness is an important risk factor for mental and physical health over the lifespan. So far, too little is known about psychosocial predictors and consequences of loneliness apart from social network characteristics. One important factor which may both prevent from, but also be affected by loneliness, is perceived autonomy. Method. In the present study, we investigated the longitudinal association of loneliness and autonomy over four years among participants of the Swedish HEARTS study (n = 5,718, age 60-66 at baseline). We used a latent curve model with structured residuals, which distinguishes within- and between person associations and includes cross-lagged parameters. Results. Between persons, higher levels of autonomy and baseline were associated with lower levels of loneliness, and increases in autonomy were associated with decreases in loneliness. When individuals felt more autonomous than usual, they also reported less loneliness. However, feeling more autonomous than usual was not associated with increases in loneliness or vice versa. Conclusion. Our findings show that low autonomy and high loneliness are related crosssectionally and longitudinally, as well as within and between persons, but the direction of effects is unclear. More research is needed to understand the development of this association over the lifespan.

Longitudinal associations between borderline personality disorder and five-factor model traits over 24 years

Are five-factor traits and borderline personality symptoms the same features with different names? The existing literature offers reasons to think they are the same and reasons to think they are different. We examined longitudinal associations between these variables in a sample of patients assessed 12 times over 24 years using latent curve models with structured residuals. Mean trajectories for all variables were in the direction of symptom reduction/personality maturation and could be parsed into an initial, rapid improvement phase and a subsequent, gradual improvement phase. We found robust between-person associations among intercepts and long-term slopes of traits and symptoms. Specifically, higher levels of neuroticism as well as lower levels of extraversion, agreeableness, and conscientiousness were associated with higher levels of borderline personality symptoms, and changes in these traits were correlated with reduction in symptoms over time. Associations among time-structured residuals allowed for examinations of within-person deflections from these general trends at briefer (two year) intervals. All variables exhibited robust within-person carry-over effects. Other within-person effects were more specific to certain traits. These results suggest that, despite their distinct theoretical and methodological bases, normal trait and psychiatric diagnostic approaches largely converged on a similar conception of borderline personality.

Evaluating the association of preoperative parecoxib with acute pain trajectories after video-assisted thoracoscopic surgery: a single-centre cohort study in Taiwan

ObjectiveThe efficacy of parecoxib as pre-emptive analgesia still remains controversial. This study aimed to investigate how pre-emptive analgesia with parecoxib affected postoperative pain trajectories over time in patients undergoing thoracic surgery.DesignRetrospective cohort study.SettingA single medical centre in Taiwan.ParticipantsWe collected 515 patients undergoing video-assisted thoracoscopic surgery at a tertiary medical centre between September 2016 and August 2017.InterventionsPre-emptive parecoxib before surgery.Primary and secondary outcome measuresDaily numeric rating pain scores in the first postoperative week.ResultsA total of 196 (38.1%) of the recruited patients received parecoxib preoperatively. The latent curve analysis revealed that woman, higher body weight and postoperative use of parecoxib were associated with increased baseline level of pain scores over time (p=0.035, 0.005 and 0.048, respectively) but epidural analgesia and preoperative use of parecoxib were inclined to decrease it (both p<0.001). Regarding the decreasing trends of changes in daily pain scores, older age and epidural analgesia tended to steepen the slope (p=0.014 and <0.001, respectively). Preoperative use of parecoxib were also related to decreased frequency of rescue morphine medication (HR=0.4; 95% CI 0.25 to 0.65).ConclusionsPre-emptive analgesia with parecoxib was associated with decreased baseline pain scores but had no connection with pain decreasing trends over time. Latent curve analysis provided insights into the dynamic relationships among the analgesic modalities, patient characteristics and postoperative pain trajectories.

Longitudinal associations between borderline personality disorder and five factor model traits over 24 years

Are five factor traits and borderline personality symptoms the same features with different names? The existing literature offers reasons to think they are the same and reasons to think they are different. We examined longitudinal associations between these variables in a sample of patients assessed 12 times over 24 years using latent curve models with structured residuals (LCM-SR). Mean trajectories for all variables were in the direction of symptom reduction/personality maturation, and could be parsed into an initial, rapid improvement phase and a subsequent, gradual improvement phase. We found robust between-person associations among intercepts and long-term slopes of traits and symptoms. Specifically, higher levels of neuroticism as well as lower levels of extraversion, agreeableness, and conscientiousness were associated with lower levels of borderline personality symptoms, and changes in these traits were correlated with reduction in symptoms over time. Associations among time-structured residuals allowed for examinations of within-person deflections from these general trends at briefer (two year) intervals. All variables exhibited robust within-person carry-over effects. Other within-person effects were more specific to certain traits. These results suggest that, despite their distinct theoretical and methodological bases, normal trait and psychiatric diagnostic approaches largely converged on a similar conception of borderline personality.