ArticleEuropean journal of psychotraumatology2015
Latent trajectory studies: the basics, how to interpret the results, and what to report.
Article in European journal of psychotraumatology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Association between serum lactate trajectories and short-term mortality in pediatric acute kidney injury patients.Jornal de pediatria · 2026Article
- Methodological Considerations in Interpreting Joint Trajectories of Frailty and Cognition in Older Koreans.Geriatrics & gerontology international · 2026Article
- Pediatric precision sleep network: a study protocol for identifying sleep signatures of mental health risk in peri-adolescents.BMC pediatrics · 2026Article
- Lactate trajectories and outcomes in critically ill patients with septic shock: a retrospective analysis of the MIMIC-IV database.BMC medical informatics and decision making · 2026Article
- Trajectories and predictors of self-care from pre-discharge to 12 months after discharge in people with spinal cord injury: a longitudinal study using growth mixture modeling.Frontiers in neuroscience · 2026Article
- Dynamic survival prediction using longitudinal AGR in unresectable locally advanced esophageal squamous cell carcinoma.Frontiers in immunology · 2026Article
- Association between early blood lactate trajectories and mortality in neonates: a retrospective cohort study.Frontiers in pediatrics · 2026Article
- Research on fatigue symptom trajectories and influencing factors among nursing undergraduates.BMC nursing · 2025Article
- Association between serum sodium trajectories and all-cause mortality in critically ill patients with ischemic stroke: a retrospective analysis of the MIMIC-IV database.European journal of medical research · 2025Article
- Prospective trajectories of depression predict mortality in cancer patients.Journal of behavioral medicine · 2024Article
- Identification of four latent classes of acute respiratory distress syndrome using PaOScientific reports · 2024Observational
- Comorbid Prolonged Grief, PTSD, and Depression Trajectories for Bereaved Family Surrogates.JAMA network open · 2023Article
- Ageing and physical resilience after health stressors.Stress and health : journal of the International Society for the Investigation of Stress · 2023Article
- Maximizing Realism: Mapping Plastic Particles at the Ocean Surface Using Mixtures of Normal Distributions.Environmental science & technology · 2022Article
- Promoting Daily Well-being in Adolescents using mHealth.Journal of youth and adolescence · 2022Article
- Longitudinal changes in COVID-19 concern and stress: Pandemic fatigue overrides individual differences in caution.Journal of public health research · 2022Article
- The course of symptoms in the first 27 months following bereavement: A latent trajectory analysis of prolonged grief, posttraumatic stress, and depression.Psychiatry research · 2022Article
- Two Approaches to Classifying and Quantifying Physical Resilience in Longitudinal Data.The journals of gerontology. Series A, Biological sciences and medical sciences · 2020Article
- A decennial review of psychotraumatology: what did we learn and where are we going?European journal of psychotraumatology · 2019Article
- Smartphone-based safety planning and self-monitoring for suicidal patients: Rationale and study protocol of the CASPAR (Continuous Assessment for Suicide Prevention And Research) study.Internet interventions · 2018Article
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Abstract
backgroundIn statistics, tools have been developed to estimate individual change over time. Also, the existence of latent trajectories, where individuals are captured by trajectories that are unobserved (latent), can be evaluated (Muthén & Muthén, 2000). The method used to evaluate such trajectories is called Latent Growth Mixture Modeling (LGMM) or Latent Class Growth Modeling (LCGA). The difference between the two models is whether variance within latent classes is allowed for (Jung & Wickrama, 2008). The default approach most often used when estimating such models begins with estimating a single cluster model, where only a single underlying group is presumed. Next, several additional models are estimated with an increasing number of clusters (latent groups or classes). For each of these models, the software is allowed to estimate all parameters without any restrictions. A final model is chosen based on model comparison tools, for example, using the BIC, the bootstrapped chi-square test, or the Lo-Mendell-Rubin test.
methodTo ease the use of LGMM/LCGA step by step in this symposium (Van de Schoot, 2015) guidelines are presented which can be used for researchers applying the methods to longitudinal data, for example, the development of posttraumatic stress disorder (PTSD) after trauma (Depaoli, van de Schoot, van Loey, & Sijbrandij, 2015; Galatzer-Levy, 2015). The guidelines include how to use the software Mplus (Muthén & Muthén, 1998-2012) to run the set of models needed to answer the research question: how many latent classes exist in the data? The next step described in the guidelines is how to add covariates/predictors to predict class membership using the three-step approach (Vermunt, 2010). Lastly, it described what essentials to report in the paper.
conclusionsWhen applying LGMM/LCGA models for the first time, the guidelines presented can be used to guide what models to run and what to report.
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