ArticleSchizophrenia bulletin2022
Symptom Structure in Schizophrenia: Implications of Latent Variable Modeling vs Network Analysis.
Article in Schizophrenia bulletin, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Applying advanced psychometrics to antipsychotic treatment trials: A protocol comparing effect estimates.Open research Europe · 2026Article
- Comparison of Negative Symptom Network Structures Between Patients With Early and Chronic Schizophrenia: A Network and Exploratory Graph Analysis.Schizophrenia bulletin · 2025Article
- Impacts of risk thresholds and age on clinical high risk for psychosis: a comparative network analysis.European archives of psychiatry and clinical neuroscience · 2025Article
- Psychological consistency network characteristics and influencing factors in patients after percutaneous coronary intervention treatment.World journal of psychiatry · 2025Article
- Deciphering the interplay between psychopathological symptoms, sensorimotor, cognitive and global functioning: a transdiagnostic network analysis.European archives of psychiatry and clinical neuroscience · 2024Article
- The dimensional structure of the Positive and Negative Syndrome Scale in first-episode schizophrenia spectrum disorders: an Exploratory Graph Analysis from the OPTiMiSE trial.Schizophrenia (Heidelberg, Germany) · 2024Article
- Longitudinal relationship between oppositional defiant disorder symptoms and attention-deficit/hyperactivity disorder symptoms in Chinese children: insights from cross-lagged panel network analyses.European child & adolescent psychiatry · 2024Article
- Clarifying directional dependence among measures of early auditory processing and cognition in schizophrenia: leveraging Gaussian graphical models and Bayesian networks.Psychological medicine · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The structure of schizophrenia symptoms has a substantial impact on the development of pharmacological and psychosocial interventions. Typically, reflective latent variable models (eg, confirmatory factor analysis) or formative latent variable models (eg, principal component analysis) have been used to examine the structure of schizophrenia symptoms. More recently, network analysis is appearing as a method to examine symptom structure. However, latent variable modeling and network analysis results can lead to different inferences about the nature of symptoms. Given the critical role of correctly identifying symptom structure in schizophrenia treatment and research, we present an introduction to latent variable modeling and network analysis, along with their distinctions and implications for examining the structure of schizophrenia symptoms. We also provide a simulation demonstration highlighting the statistical equivalence between these models and the subsequent importance of an a priori rationale that should help guide model selection.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.