Brief Report on Estimating Regularized Gaussian Networks from Continuous and Ordinal Data
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Summary
Simulation results indicate that GeLasso works well as an out-of-the-box method to estimate network structures and asses its performance using a plausible psychological network structure with both continuous and ordinal datasets.
- Type
- preprint
- Published
- 2016-06-18
- Cited by
- 36
- References
- 42
- Access
- Open access
- OpenAlex
- https://openalex.org/W2758589867
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:88521212
Keywords
Ordinal data, Gaussian, Computer science, Regularization (linguistics), Graphical model
References
- Social Network Analysis: Methods and Applications
- The application of a network approach to Health-Related Quality of Life (HRQoL): introducing a new method for assessing HRQoL in healthy adults and cancer patients
- Networks: An Introduction
- lavaan: An R Package for Structural Equation Modeling
- Variations of Box Plots
- The structure of phenotypic personality traits.
- An alternative "description of personality": The Big-Five factor structure.
- State of the aRt personality research: A tutorial on network analysis of personality data in R
- Maximum likelihood estimation of the polychoric correlation coefficient
- A new method for constructing networks from binary data
- Personality trait structure as a human universal.
- Los Cinco Grandes across cultures and ethnic groups: multitrait multimethod analyses of the Big Five in Spanish and English.
- Extended Bayesian information criteria for model selection with large model spaces
- High-dimensional Ising model selection with Bayesian information criteria
- Deconstructing the construct: A network perspective on psychological phenomena
- The polyserial correlation coefficient
- Model selection for Gaussian concentration graphs
- What are 'good' depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis.
- Extended Bayesian Information Criteria for Gaussian Graphical Models
- Five robust trait dimensions: development, stability, and utility.
Cited by
- A Primer on Estimating Regularized Psychological Networks
- Moderated Network Models
- A network analysis of female sexual function: comparing symptom networks in women with decreased, increased, and stable sexual desire
- On Penalty Parameter Selection for Estimating Network Models
- A Partial Correlation Screening Approach for Controlling the False Positive Rate in Sparse Gaussian Graphical Models
- Feasibility and Utility of Idiographic Models in the Clinic: A Pilot Study
- Human disease clinical treatment network for the elderly: The analysis of medicare inpatient length of stay data
- Comparison of depression and anxiety symptom networks in reporters and non-reporters of lifetime trauma in two samples of differing severity
- Network analysis of anxiety and depressive symptoms among quarantined individuals: cross-sectional study
- Estructura de los síntomas de depresión según el CES-D y la ZDS en pacientes ambulatorios de un hospital general de Lima, Perú
- The network of the subjective experience in embodiment phenomena
- Application of Network Analysis to Uncover Variables Contributing to Functional Recovery after Stroke
- Understanding change in COVID-19 vaccination intention with network analysis of longitudinal data from Dutch adults
- How compliance with behavioural measures during the initial phase of a pandemic develops over time: A longitudinal COVID‐19 study
- Tailored interventions into broad attitude networks towards the COVID-19 pandemic
- Exploring cognitive, behavioral and autistic trait network topology in very preterm and term-born children
- Resilience Among Older Individuals in the Face of Adversity: How Demographic and Trait Factors Affect Mental-Health Constructs and Their Temporal Dynamics
- Understanding public perceptions toward sustainable healthcare through psychological network analysis of material preference and attitudes toward plastic medical devices
- Network analysis of multimorbidity and health outcomes among persons with spinal cord injury in Canada
- Developmental structure of digital maturity
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