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Applications: Network Models Network Models I Latent factors - PowerPoint PPT Presentation

Applications: Network Models Network Models I Latent factors reflect disease model Single underlying cause Requires conditional independence Symptoms/behaviors (likely) causally-related Network models provide an alternative


  1. Applications: Network Models

  2. Network Models I • Latent factors reflect disease model – Single underlying cause • Requires conditional independence – Symptoms/behaviors (likely) causally-related • Network models provide an alternative

  3. Network Models II • Contemporaneous and directed models are estimated separately • Directed networks are estimated by running k univariate VARs for k variables. • Model imprecision is not taken into account • No model fit • Almost no idiographic work

  4. Integrated Network Model • Utilizes SEM framework – Automatic search procedure via Lagrange multiplier test (modification indices) – Bottom-up, data-driven model construction • Provides – Unconditional correlations (time t) – Directional, time-lagged relationships – Residual correlations (time t+1 )

  5. To what degree have you: 1. Felt down or depressed tension 2. Felt hopeless 12. Felt fatigued 3. Experienced loss of 13. Avoided people interest or pleasure 14. Avoided activities 4. Felt worthless or guilty 15. Procrastinated 5. Felt worried 16. Sought reassurance 6. Felt restless 17. Dwelled on the past 7. Felt irritable 18. Felt positive 8. Felt angry 19. Felt content 9. Felt afraid 20. Felt enthusiastic 10. Had difficulty 21. Felt energetic concentrating 11. Experienced muscle

  6. P025 Unconditional Model

  7. P025 Directed Model

  8. P025 Residual Model

  9. P025 Integrated Model

  10. Expected Force • Centrality measures are poorly equipped for flow characteristics of weighted networks (Borgatti, 2005) – Not designed to quantify spreading power – Underestimate influence of non-hub nodes • Expected Force quantifies the spreading power of each node in a network (Lawyer, 2015, Nature) – Spreading power is determined by the influence of the node and the influence of its neighbors – Provides a normal, continuous metric

  11. Expected Force Uncondi4onal ¡ Directed ¡ Integrated ¡

  12. InStrength 1 ¡ 0.9 ¡ 0.8 ¡ 0.7 ¡ 0.6 ¡ 0.5 ¡ 0.4 ¡

  13. P068 Directed Model

  14. P111 Directed Model

  15. P072 Directed Model

  16. P048 Directed Model

  17. P014 Directed Model

  18. P023 Directed Model

  19. P075 Directed Model

  20. P115 Directed Model

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