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Chain graph models and their causal interpretations

Citations

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Cited by:

  1. Riccardo Borgoni & Ann Berrington & Peter Smith, 2012. "Selecting and fitting graphical chain models to longitudinal data," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(3), pages 715-738, April.
  2. Javier Pérez & A. Sánchez, 2011. "Is there a signalling role for public wages? Evidence for the euro area based on macro data," Empirical Economics, Springer, vol. 41(2), pages 421-445, October.
  3. Yunyi Shen & Claudia Solís-Lemus, 2025. "The Effect of the Prior and the Experimental Design on the Inference of the Precision Matrix in Gaussian Chain Graph Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 30(3), pages 800-869, September.
  4. Alberto Roverato, 2021. "On the interpretation of inflated correlation path weights in concentration graphs," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(5), pages 1485-1505, December.
  5. Hogun Chong & Mary Zey & David A. Bessler, 2010. "On corporate structure, strategy, and performance: a study with directed acyclic graphs and PC algorithm," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 31(1), pages 47-62.
  6. Yiran Zhang & Andrew Ying & Steve Edland & Lon White & Ronghui Xu, 2024. "Marginal Structural Illness-Death Models for Semi-competing Risks Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 16(3), pages 668-692, December.
  7. Elizabeth L. Ogburn & Ilya Shpitser & Youjin Lee, 2020. "Causal inference, social networks and chain graphs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1659-1676, October.
  8. Brathwaite, Timothy & Walker, Joan L., 2018. "Causal inference in travel demand modeling (and the lack thereof)," Journal of choice modelling, Elsevier, vol. 26(C), pages 1-18.
  9. Miljkovic, Dragan & Dalbec, Nathan & Zhang, Lei, 2016. "Estimating dynamics of US demand for major fossil fuels," Energy Economics, Elsevier, vol. 55(C), pages 284-291.
  10. Akyildirim, Erdinc & Cepni, Oguzhan & Pham, Linh & Uddin, Gazi Salah, 2022. "How connected is the agricultural commodity market to the news-based investor sentiment?," Energy Economics, Elsevier, vol. 113(C).
  11. Oxley, Les & Reale, Marco & Wilson, Granville Tunnicliffe, 2009. "Constructing structural VAR models with conditional independence graphs," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2910-2916.
  12. Heckman, James & Pinto, Rodrigo, 2015. "Causal Analysis After Haavelmo," Econometric Theory, Cambridge University Press, vol. 31(1), pages 115-151, February.
  13. Alessio Moneta, 2008. "Graphical causal models and VARs: an empirical assessment of the real business cycles hypothesis," Empirical Economics, Springer, vol. 35(2), pages 275-300, September.
  14. repec:jss:jstsof:15:i06 is not listed on IDEAS
  15. Geng, Zhi & Wang, Chi & Zhao, Qiang, 2005. "Decomposition of search for v-structures in DAGs," Journal of Multivariate Analysis, Elsevier, vol. 96(2), pages 282-294, October.
  16. David Greasley & Les Oxley, 2010. "Cliometrics And Time Series Econometrics: Some Theory And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 24(5), pages 970-1042, December.
  17. Tyler J. VanderWeele & James M. Robins, 2010. "Signed directed acyclic graphs for causal inference," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(1), pages 111-127, January.
  18. A. Charisse Farr & Kerrie Mengersen & Fabrizio Ruggeri & Daniel Simpson & Paul Wu & Prasad Yarlagadda, 2020. "Combining Opinions for Use in Bayesian Networks: A Measurement Error Approach," International Statistical Review, International Statistical Institute, vol. 88(2), pages 335-353, August.
  19. Zijun Wang, 2010. "Directed graphs, information structure and forecast combinations: an empirical examination of US unemployment rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(4), pages 353-366.
  20. Blom Tineke & Mooij Joris M., 2023. "Causality and independence in perfectly adapted dynamical systems," Journal of Causal Inference, De Gruyter, vol. 11(1), pages 1-35, January.
  21. Karim Chalak & Halbert White, 2008. "Causality, Conditional Independence, and Graphical Separation in Settable Systems," Boston College Working Papers in Economics 689, Boston College Department of Economics, revised 04 Jul 2010.
  22. Alessio Moneta, 2004. "Identification of Monetary Policy Shocks: A graphical causal approach," Notas Económicas, Faculty of Economics, University of Coimbra, issue 20, pages 39-62, December.
  23. Jonas Peters & Peter Bühlmann & Nicolai Meinshausen, 2016. "Causal inference by using invariant prediction: identification and confidence intervals," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(5), pages 947-1012, November.
  24. Daniel O. Scharfstein & Jon Steingrimsson & Aidan McDermott & Chenguang Wang & Souvik Ray & Aimee Campbell & Edward Nunes & Abigail Matthews, 2022. "Global sensitivity analysis of randomized trials with nonmonotone missing binary outcomes: Application to studies of substance use disorders," Biometrics, The International Biometric Society, vol. 78(2), pages 649-659, June.
  25. Soraggi, Samuele & Wiuf, Carsten, 2019. "General theory for stochastic admixture graphs and F-statistics," Theoretical Population Biology, Elsevier, vol. 125(C), pages 56-66.
  26. Federica Nicolussi & Manuela Cazzaro & Tamás Rudas, 2024. "Improving the power of hypothesis tests in sparse contingency tables," Statistical Papers, Springer, vol. 65(3), pages 1841-1867, May.
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