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Statistical models for causal mediation in within-subject designs : dealing with unmeasured confounders and interactions

Haeike Josephy (UGent)
(2018)
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(UGent) and (UGent)
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Keywords
categorical data analysis, multilevel modeling, mixed models, structural equation modeling, causal mediation analysis

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Citation

Please use this url to cite or link to this publication:

Chicago
Josephy, Haeike. 2018. “Statistical Models for Causal Mediation in Within-subject Designs : Dealing with Unmeasured Confounders and Interactions”. Ghent, Belgium: Ghent University. Faculty of Psychology and Educational Sciences.
APA
Josephy, H. (2018). Statistical models for causal mediation in within-subject designs : dealing with unmeasured confounders and interactions. Ghent University. Faculty of Psychology and Educational Sciences, Ghent, Belgium.
Vancouver
1.
Josephy H. Statistical models for causal mediation in within-subject designs : dealing with unmeasured confounders and interactions. [Ghent, Belgium]: Ghent University. Faculty of Psychology and Educational Sciences; 2018.
MLA
Josephy, Haeike. “Statistical Models for Causal Mediation in Within-subject Designs : Dealing with Unmeasured Confounders and Interactions.” 2018 : n. pag. Print.
@phdthesis{8573997,
  author       = {Josephy, Haeike},
  keyword      = {categorical data analysis,multilevel modeling,mixed models,structural equation modeling,causal mediation analysis},
  language     = {eng},
  pages        = {XI, 227},
  publisher    = {Ghent University. Faculty of Psychology and Educational Sciences},
  school       = {Ghent University},
  title        = {Statistical models for causal mediation in within-subject designs : dealing with unmeasured confounders and interactions},
  year         = {2018},
}