Advances in Bayesian Modeling in Educational Research

Educational Psychologist

Volumn 51, Issue 3-4, 2016, Pages 368-380

  Levy, Roy ^a  

^a ARIZONA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84985031030     PISSN: 00461520     EISSN: None     Source Type: Journal    
DOI: 10.1080/00461520.2016.1207540     Document Type: Article

References (30)

1. Almond, R. G., Mislevy, R. J., Steinberg, L. S., Yan, D., & Williamson, D. M. (2015). Bayesian networks in educational assessment. New York, NY:Springer.
2. G.E.P.Box, & G.C.Tiao, (1973). Bayesian inference in statistical analysis. Reading, MA:Addison-Wesley.
3. G.K.W.K.Chung, E.L.Baker, T.P.Vendlinski, R.E.Buschang, G.C.Delacruz, J.K.Michiuye, & S.J.Bittick, (2010, May). Testing instructional design variations in a prototype math game. Paper presented at the annual meeting of the American Educational Research Association, Denver, CO.
4. L.M.Collins, & S.T.Lanza, (2010). Latent class and latent transition analysis:With applications in the social, behavioral, and health sciences. Hoboken, NJ:Wiley.
5. C.M.Dayton, (1999). Latent class scaling analysis. Thousand Oaks, CA:Sage.
6. de Finetti, B. (1974). Theory of probability, Volume 1. New York, NY:Wiley.
7. C.K.Enders, A.J.Fairchild, & D.P.MacKinnon, (2013). A Bayesian approach for estimating mediation effects with missing data. Multivariate Behavioral Research, 48, 340–369.
8. J.-P.Fox, (2010). Bayesian item response modeling:Theory and applications. New York, NY:Springer.
9. A.Gelman, J.B.Carlin, H.S.Stern, D.B.Dunson, A.Vehtari, & D.B.Rubin, (2013). Bayesian data analysis (3rd ed.). Boca Raton, FL:Chapman and Hall/CRC.
10. S.Goodman, (2008). A dirty dozen:Twelve p-value misconceptions. Seminars in Hematology, 45, 135–140. Retrieved from http://doi.org/10.1053/j.seminhematol.2008.04.003
11. R.Hoekstra, R.D.Morey, J.N.Rouder, & E.-J.Wagenmakers, (2014). Robust misinterpretation of confidence intervals. Psychonomic Bulletin & Review, 21, 1157–1164. http://doi.org/10.3758/s13423-013-0572-3
12. S.Jackman, (2009). Bayesian analysis for the social sciences. Chichester, England:Wiley.
13. D.Kaplan, & S.Depaoli, (2012). Bayesian structural equation modeling. In R.H.Hoyle (Ed.), Handbook of structural equation modeling (pp. 650–673). New York, NY:Guilford Press.
14. J.-S.Kim, & D.M.Bolt, (2007). Estimating item response theory models using Markov chain Monte Carlo methods. Educational Measurement:Issues and Practice, 26(4), 38–51.
15. S.-Y.Lee, (2007). Structural equation modeling:A Bayesian approach. Chichester, UK:Wiley.
16. R.Levy, (2011). Bayesian data-model fit assessment for structural equation modeling. Structural Equation Modeling:A Multidisciplinary Journal, 18, 663–685. http://doi.org/10.1080/10705511.2011.607723
17. R.Levy, (2014). Dynamic Bayesian network modeling of game based diagnostic assessments (CRESST Report No. 837). Los Angeles:University of California, National Center for Research on Evaluation, Standards, Student Testing. Retrieved from http://www.cse.ucla.edu/products/reports/R837.pdf
18. R.Levy, & J.Choi, (2013). Bayesian structural equation modeling. In G.R.Hancock & R.O.Mueller (Eds.), Structural equation modeling:A second course (2nd ed., pp. 563–623). Charlotte, NC:Information Age.
19. R.Levy, & A.V.Crawford, (2009). Incorporating substantive knowledge into regression via a Bayesian approach to modeling. Multiple Linear Regression Viewpoints, 35(2), 4–9.
20. R.Levy, & R.J.Mislevy, (2016). Bayesian psychometric modeling. Boca Raton, FL:Chapman and Hall/CRC.
21. R.Levy, R.J.Mislevy, & J.T.Behrens, (2011). MCMC in educational research. In S.Brooks, A.Gelman, G.L.Jones, & X.-L.Meng (Eds.), Handbook of Markov chain Monte Carlo:Methods and applications (pp. 531–545). London, UK:Chapman and Hall/CRC.
22. D.V.Lindley, & A.F.M.Smith, (1972). Bayes estimates for the linear model. Journal of the Royal Statistical Society. Series B, 34, 1–41.
23. Norsys Software Corporation. (1999–2012). Netica manual. Vancouver, British Columbia, Canada.
24. Reye, J. (2004). Student modelling based on belief networks. International Journal of Artificial Intelligence in Education, 14, 63–96.
25. D.B.Rubin, (1987). Multiple imputation for nonresponse in surveys. New York, NY:Wiley & Sons.
26. V.J.Shute, M.Ventura, M.Bauer, & D.Zapata-Rivera, (2009). Melding the power of serious games and embedded assessment to monitor and foster learning. In U.Ritterfeld, M.J.Cody, & P.Vorderer (Eds.), Serious games:Mechanisms and effects (Vol. 2, pp. 295–321). Philadelphia, PA:Routledge/LEA.
27. T.Snijders, & R.Bosker, (2012). Multilevel analysis:An introduction to basic and advanced multilevel modeling (2nd ed.). Los Angeles, CA:Sage.
28. X.-Y.Song, & S.-Y.Lee, (2012). Basic and advanced Bayesian structural equation modeling:With applications in the medical and behavioral sciences. Chichester, UK:Wiley.
29. E.-J.Wagenmakers, (2007). A practical solution to the pervasive problems of p values. Psychonomic Bulletin & Review, 14, 779–804. http://doi.org/10.3758/BF03194105
30. Y.Yuan, & D.P.MacKinnon, (2009). Bayesian mediation analysis. Psychological Methods, 14, 301–322. http://doi.org/10.1037/a0016972