Specifying Piecewise Latent Trajectory Models for Longitudinal Data

2008 ◽  
Vol 15 (3) ◽  
pp. 513-533 ◽  
Author(s):  
David B. Flora
Keyword(s):  
Longitudinal Data ◽  
Latent Trajectory ◽  
Trajectory Models

Developmental relations between ADHD symptoms and bullying perpetration and victimisation in adolescence

2020 ◽  
Author(s):  
Aja Louise Murray ◽  
Izabela Zych ◽  
Denis Ribeaud ◽  
Manuel Eisner
Keyword(s):  
Longitudinal Data ◽  
Future Research ◽  
Reciprocal Effects ◽  
Typically Developing ◽  
Adhd Symptoms ◽  
Bullying Perpetration ◽  
Latent Trajectory ◽  
Instrumental Aggression ◽  
Blinded Study ◽  
Trajectory Models

It has previously been hypothesised that individuals with elevated ADHD symptoms are at greater risk of bullying perpetration and victimization; however, a lack of high-quality longitudinal data has meant that this hypothesis is yet to be adequately tested. Using autoregressive latent trajectory models with structured residuals (ALT-SR) and four waves (ages 11, 13, 15 and 17) of longitudinal data from the BLINDED STUDY NAME (n=1526, 52% male), we evaluated the developmental relations between ADHD and bullying using both self- and teacher-reported ADHD symptom data. Analyses suggested that ADHD symptoms primarily increase the risk of bullying perpetration, with a within-person effect of ADHD symptoms on bullying perpetration symptoms identified across ages 13 to 15 (β=.13) and ages 15 to 17 (β=.19) based on self-reported ADHD symptoms; and a similar effect identified across ages 11 to 13 (β=.24) and 13 to 15 (β=.29) based on teacher-reported inattention symptoms. There were also some indications of reciprocal effects and effects involving victimization that merit further exploration in future research. Results imply that the content of bullying intervention and prevention programs should take account of ADHD symptoms in order to ensure that those with elevated ADHD symptoms can benefit from these interventions as much as their typically developing peers. This will involve addressing bullying perpetration that may reflect impulsive/reactive aggression and impaired social skills rather than instrumental aggression. Further, programs should go beyond classical curriculum/classroom-based delivery to ensure that individuals with elevated ADHD symptoms can be successfully engaged.

Methodological Approaches to Modeling Criminal Trajectories

2019 ◽  
pp. 60-100
Author(s):  
David M. Day ◽  
Margit Wiesner
Keyword(s):  
Longitudinal Data ◽  
Growth Curve ◽  
Growth Mixture Modeling ◽  
Statistical Technique ◽  
Heterogeneous Population ◽  
Growth Curve Modeling ◽  
Latent Growth ◽  
Growth Mixture ◽  
Curve Modeling ◽  
Trajectory Models

Criminal offenders compose a heterogeneous population. Criminal trajectory research aims to capture this heterogeneity in terms of the frequency or severity of offending. This chapter describes the concept a criminal trajectory and the statistical technique used to derive trajectories from longitudinal data. Both the semiparametric group-based trajectory modeling (SGBTM) and latent growth mixture modeling (GMM) approaches are described in nontechnical terms, and the differences between them are noted. Despite some similarities, these approaches are also distinguished from conventional growth curve modeling. Guidelines and factors to consider in building and testing trajectory models are discussed. Last, extensions of SGBTM and GMM are presented.

Trajectories of Symbol Digit Modalities Test performance in individuals with multiple sclerosis

2020 ◽  
pp. 135245852091343 ◽  
Author(s):  
Brian C Healy ◽  
Lindsay Barker ◽  
Rohit Bakshi ◽  
Ralph H B Benedict ◽  
Cindy T Gonzalez ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Cognitive Functioning ◽  
Test Performance ◽  
Disease Duration ◽  
Longitudinal Change ◽  
Latent Trajectory ◽  
Lower Baseline ◽  
Term Change ◽  
Baseline Values ◽  
Trajectory Models

Background: Although cognitive problems have been identified in people with multiple sclerosis (PwMS), few studies have investigated the long-term change in cognitive functioning. Objective: To identify trajectories of change in cognitive functioning for PwMS. Methods: Participants enrolled in the quality-of-life subgroup from the Comprehensive Longitudinal Investigation of Multiple Sclerosis at Brigham and Women’s Hospital (CLIMB) were eligible for our analysis. In 2006, participants in this group began to complete the Symbol Digit Modalities Test (SDMT) annually. Latent trajectory models were used to identify groups of participants with similar longitudinal change in SDMT scores. Linear and quadratic trajectory models were fit, and the models were compared. Latent trajectory models were also fit adjusting for baseline age and disease duration as well as using normalized SDMT scores. The groups identified across the approaches were compared. Results: We found that classes with higher-than-average baseline values improved, classes with average baseline values remained relatively constant, and classes with lower baseline values experienced cognitive worsening. Similar results were observed in the alternative latent trajectory models accounting for other variables. Conclusion: Our models show that subjects with higher SDMT scores at baseline showed improvement, while subjects with lower SDMT scores at baseline showed worsening. Baseline age and disease duration were also associated with SDMT performance.

Implications of latent trajectory models for the study of developmental psychopathology

2003 ◽  
Vol 15 (3) ◽  
pp. 581-612 ◽  
Author(s):  
PATRICK J. CURRAN ◽  
MICHAEL T. WILLOUGHBY
Keyword(s):  
Developmental Psychopathology ◽  
Broad Class ◽  
Theoretical Models ◽  
Developmental Theory ◽  
Empirical Science ◽  
Quantitative Methodology ◽  
Growth Curve Models ◽  
Latent Trajectory ◽  
Trajectory Models ◽  
The One

The field of developmental psychopathology is faced with a dual challenge. On the one hand, we must build interdisciplinary theoretical models that adequately reflect the complexity of normal and abnormal human development over time. On the other hand, to remain a viable empirical science, we must rigorously evaluate these theories using statistical methods that fully capture this complexity. The degree to which our statistical models fail to correspond to our theoretical models undermines our ability to validly test developmental theory. The broad class of random coefficient trajectory (or growth curve) models allow us to test our theories in ways not previously possible. Despite these advantages, there remain certain limits with regard to the types of questions these models can currently evaluate. We explore these issues through the pursuit of three goals. First, we provide an overview of a variety of trajectory models that can be used for rigorously testing many hypotheses in developmental psychopathology. Second, we highlight what types of research questions are well tested using these methods and what types of questions currently are not. Third, we describe areas for future statistical development and encourage the ongoing interchange between developmental theory and quantitative methodology.

scholarly journals The Use of Latent Trajectory Models in Psychopathology Research.

2003 ◽  
Vol 112 (4) ◽  
pp. 526-544 ◽  
Author(s):  
Patrick J. Curran ◽  
Andrea M. Hussong
Keyword(s):  
Latent Trajectory ◽  
Trajectory Models

Unobtrusive Sensing Technology Detects Ecologically Valid Spatiotemporal Patterns of Daily Routines Distinctive to Persons with Mild Cognitive Impairment

2021 ◽  
Author(s):  
Chao-Yi Wu ◽  
Hiroko H Dodge ◽  
Sarah Gothard ◽  
Nora Mattek ◽  
Kirsten Wright ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Spatiotemporal Patterns ◽  
Living Room ◽  
Aging Research ◽  
Activity Group ◽  
Latent Trajectory ◽  
Diurnal Patterns ◽  
Trajectory Models ◽  
Unobtrusive Sensing

Abstract Background The ability to capture people’s movement throughout their home is a powerful approach to inform spatiotemporal patterns of routines associated with cognitive impairment. The study estimated indoor room activities over 24 hours and investigated relationships between diurnal activity patterns and mild cognitive impairment (MCI). Methods 161 older adults (26 with MCI) living alone (age=78.9±9.2) were included from two study cohorts–the Oregon Center for Aging & Technology and the Minority Aging Research Study. Indoor room activities were measured by the number of trips made to rooms (bathroom, bedroom, kitchen, living room). Trips made to rooms (transitions) were detected using passive infrared motion sensors fixed on the walls for a month. Latent trajectory models were used to identify distinct diurnal patterns of room activities and characteristics associated with each trajectory. Results Latent trajectory models identified two diurnal patterns of bathroom usage (high; low usage). Participants with MCI were more likely to be in the high bathroom usage group that exhibited more trips to the bathroom than the low usage group (OR=4.1,95%CI [1.3-13.5],p=0.02). For kitchen activity, two diurnal patterns were identified (high; low activity). Participants with MCI were more likely to be in the high kitchen activity group that exhibited more transitions to the kitchen throughout the day and night than the low kitchen activity group (OR=3.2,95%CI [1.1-9.1],p=0.03). Conclusions The linkage between bathroom and kitchen activities with MCI may be the result of biological, health, and environmental factors in play. In-home, real-time unobtrusive-sensing offers a novel way of delineating cognitive health with chronologically-ordered movement across indoor locations.

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