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European Journal of Psychotraumatology Volume 6, 2015 - Issue 1
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Supplement 2, 2015: Estimating PTSD trajectories - selected abstracts

Using Bayesian statistics for modeling PTSD through Latent Growth Mixture Modeling: implementation and discussion

Sarah DepaoliPsychological Sciences, University of California, Merced, CA, USACorrespondence[email protected]
,
Rens van de SchootDepartment of Methods and Statistics, Utrecht University, Utrecht, The Netherlands;Optentia Research Program, Faculty of Humanities, North-West University, Mahikeng, South Africa
,
Nancy van LoeyDepartment of Clinical and Health Psychology, Utrecht University, Utrecht, The Netherlands;Department of Behavioral Research, Association of Dutch Burns Centres, AJ Beverwijk, The Netherlands
&
Marit SijbrandijClinical Psychology, VU University, Amsterdam, The Netherlands;EMGO Institute for Health and Care Research, Amsterdam, The Netherlands
Article: 27516 | Received 06 Feb 2015, Accepted 06 Feb 2015, Published online: 02 Mar 2015

References

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  • Galatzer-Levy I. Applications of Latent Growth Mixture Modeling and allied methods to posttraumatic stress response data. European Journal of Psychotraumatology. 2015; 6: 27515. http://dx.doi.org/10.3402/ejpt.v6.27515.
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  • Van de Schoot R. Latent Growth Mixture Models to estimate PTSD trajectories. European Journal of Psychotraumatology. 2015a; 6: 27503. http://dx.doi.org/10.3402/ejpt.v6.27503.
  • Van de Schoot R. Latent trajectory studies: The basics, how to interpret the results, and what to report. European Journal of Psychotraumatology. 2015b; 6: 27514. http://dx.doi.org/10.3402/ejpt.v6.27514.
  • Van de Schoot R., Broere J. J., Perryck K., Zondervan-Zwijnenburg M., Van Loey N. Analyzing small data sets using Bayesian estimation: The case of posttraumatic stress symptoms following mechanical ventilation in burn survivors. European Journal of Psychotraumatology. 2015; 6: 25216. http://dx.doi.org/10.3402/ejpt.v6.25216.

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