User menu

On the Bayesian nonparametric generalization of IRT-type models

Bibliographic reference San Martin, Ernesto ; Jara, Alejandro ; Rolin, Jean-Marie ; Mouchart, Michel. On the Bayesian nonparametric generalization of IRT-type models. In: Psychometrika, (2011)
Permanent URL
  1. Agresti Alan, Caffo Brian, Ohman-Strickland Pamela, Examples in which misspecification of a random effects distribution reduces efficiency, and possible remedies, 10.1016/j.csda.2003.12.009
  2. Antoniak Charles E., Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems, 10.1214/aos/1176342871
  3. Bechger Timo M., Verhelst Norman D., Verstralen Huub H. F. M., Identifiability of nonlinear logistic test models, 10.1007/bf02294439
  4. Borsboom Denny, Mellenbergh Gideon J., van Heerden Jaap, The theoretical status of latent variables., 10.1037/0033-295x.110.2.203
  5. Burr Deborah, Doss Hani, A Bayesian Semiparametric Model for Random-Effects Meta-Analysis, 10.1198/016214504000001024
  6. Bush C., A semiparametric Bayesian model for randomised block designs, 10.1093/biomet/83.2.275
  7. Chandra, S. (1977). On the mixture of probability distributions. Scandinavian Journal of Statistics, 4, 105–112.
  8. Conway, J.B. (1985). A course in functional analysis. New York: Springer.
  9. Explanatory Item Response Models, ISBN:9781441923233, 10.1007/978-1-4757-3990-9
  10. de Leeuw Jan, Verhelst Norman, Maximum Likelihood Estimation in Generalized Rasch Models, 10.2307/1165071
  11. Doob, J.L. (1949). Applications of the theory of martingales. Colloques Internationaux du Centre National de le Recherche Scientifique, 13, 23–27.
  12. Duncan Kristin A, MacEachern Steven N, Nonparametric Bayesian modelling for item response, 10.1177/1471082x0700800104
  13. Escobar Michael D., West Mike, Bayesian Density Estimation and Inference Using Mixtures, 10.2307/2291069
  14. Ferguson Thomas S., A Bayesian Analysis of Some Nonparametric Problems, 10.1214/aos/1176342360
  15. Ferguson Thomas S., Prior Distributions on Spaces of Probability Measures, 10.1214/aos/1176342752
  16. Florens, J.-P., Mouchart, M., & Rolin, J.-M. (1990). Elements of Bayesian statistics. New York: Dekker.
  17. Florens, J.-P., & Rolin, J.-M. (1984). Asymptotic sufficiency and exact estimability. In Florens, J.-P., Mouchart, M., Raoult, J.-P., & Simar, L. (Eds.), Alternative approaches to time series analysis (pp. 121–142). Bruxelles: Publications des Facultés Universitaires Saint-Louis.
  18. Geisser Seymour, Eddy William F., A Predictive Approach to Model Selection, 10.2307/2286745
  19. Ghosh Malay, Inconsistent maximum likelihood estimators for the Rasch model, 10.1016/0167-7152(94)00109-l
  20. Hanson Timothy E, Inference for Mixtures of Finite Polya Tree Models, 10.1198/016214506000000384
  21. Hanson Timothy, Johnson Wesley O, Modeling Regression Error With a Mixture of Polya Trees, 10.1198/016214502388618843
  22. Ishwaran Hemant, Discussion, 10.2307/3315668
  23. Jansen Margo G. H., van Duijn Marijtje A. J., Extensions of Rasch's multiplicative poisson model, 10.1007/bf02295428
  24. Jara, A. (2007). Applied Bayesian non- and semi-parametric inference using DPpackage. Rnews, 7(3), 17–26.
  25. Jara Alejandro, Hanson Timothy E., Lesaffre Emmanuel, Robustifying Generalized Linear Mixed Models Using a New Class of Mixtures of Multivariate Polya Trees, 10.1198/jcgs.2009.07062
  26. Kadane, J. (1975). The role of identification in Bayesian theory. In Fienberg, S., & Zellner, A. (Eds.), Studies in Bayesian econometrics and statistics (pp. 175–191). Amsterdam: North-Holland.
  27. Karabatsos George, Walker Stephen G., Coherent psychometric modelling with Bayesian nonparametrics, 10.1348/000711007x246237
  28. Kiefer J., Wolfowitz J., Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters, 10.1214/aoms/1177728066
  29. Kleinman Ken P., Ibrahim Joseph G., A semi-parametric Bayesian approach to generalized linear mixed models, 10.1002/(sici)1097-0258(19981130)17:22<2579::aid-sim948>;2-p
  30. Kleinman Ken P., Ibrahim Joseph G., A Semiparametric Bayesian Approach to the Random Effects Model, 10.2307/2533846
  31. Lavine Michael, Some Aspects of Polya Tree Distributions for Statistical Modelling, 10.1214/aos/1176348767
  32. Lavine Michael, More Aspects of Polya Tree Distributions for Statistical Modelling, 10.1214/aos/1176325623
  33. Li Yisheng, Lin Xihong, Müller Peter, Bayesian Inference in Semiparametric Mixed Models for Longitudinal Data, 10.1111/j.1541-0420.2009.01227.x
  34. Lindley, D.V. (1971). Bayesian statistics: a review. Montpelier: Society for Industrial and Applied Mathematics.
  35. Lindsay Bruce, Clogg Clifford C., Grego John, Semiparametric Estimation in the Rasch Model and Related Exponential Response Models, Including a Simple Latent Class Model for Item Analysis, 10.2307/2289719
  36. Maris Gunter, Bechger Timo M., Equivalent MIRID models, 10.1007/bf02289859
  37. Miyazaki Kei, Hoshino Takahiro, A Bayesian Semiparametric Item Response Model with Dirichlet Process Priors, 10.1007/s11336-008-9108-6
  38. Mouchart, M., & Rolin, J.M. (1984). A note on conditional independence with statistical applications. Statistica, 44, 557–584.
  39. Mouchart M., San Martı́n E., Specification and identification issues in models involving a latent hierarchical structure, 10.1016/s0378-3758(02)00295-1
  40. Mukhopadhyay Saurabh, Gelfand Alan E., Dirichlet Process Mixed Generalized Linear Models, 10.2307/2965710
  41. Muller Peter, Rosner Gary L., A Bayesian Population Model With Hierarchical Mixture Priors Applied to Blood Count Data, 10.2307/2965398
  42. Neyman J., Scott Elizabeth L., Consistent Estimates Based on Partially Consistent Observations, 10.2307/1914288
  43. Pfanzagl J., Incidental Versus Random Nuisance Parameters, 10.1214/aos/1176349392
  44. Picci Giorgio, Some Connections Between the Theory of Sufficient Statistics and the Identifiability Problem, 10.1137/0133025
  45. Rao, M.M. (1984). Probability theory with applications. New York: Academic Press.
  46. Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests. Copenhagen: The Danish Institute for Educational Research.
  47. Revuelta Javier, Identifiability and Equivalence of GLLIRM Models, 10.1007/s11336-008-9084-x
  48. Revuelta Javier, Estimating Difficulty from Polytomous Categorical Data, 10.1007/s11336-009-9145-9
  49. Roberts Gareth O., Rosenthal Jeffrey S., Markov-chain monte carlo: Some practical implications of theoretical results, 10.2307/3315667
  50. San Martín, E. (2000). Latent structural models: specification and identification problems. Belgium: Ph.D. Dissertation, Institute of Statistics, Université Catholique de Louvain.
  51. Martín Ernesto San, del Pino Guido, De Boeck Paul, IRT Models for Ability-Based Guessing, 10.1177/0146621605282773
  52. San Martín, E., & Mouchart, M. (2007). On joint completeness: sampling and Bayesian versions, and their connections. Sankhyā, 69, 780–807.
  53. Teicher Henry, Identifiability of Mixtures, 10.1214/aoms/1177705155
  54. Walker Stephen G., Mallick Bani K., Hierarchical Generalized Linear Models and Frailty Models with Bayesian Nonparametric Mixing, 10.1111/1467-9868.00101
  55. Wasserman, L. (1998). Asymptotic properties of nonparametric Bayesian procedures. In Dey, D., Müller, P., & Sinha, D. (Eds.), Developments in statistical inference and data analysis (pp. 293–304). New York: Springer.
  56. Woods Carol M., Ramsay-curve item response theory (RC-IRT) to detect and correct for nonnormal latent variables., 10.1037/1082-989x.11.3.253
  57. Woods Carol M., Ramsay-Curve Item Response Theory for the Three-Parameter Logistic Item Response Model, 10.1177/0146621607308014
  58. Woods Carol M., Thissen David, Item Response Theory with Estimation of the Latent Population Distribution Using Spline-Based Densities, 10.1007/s11336-004-1175-8
  59. Yang Mingan, Dunson David B., Bayesian Semiparametric Structural Equation Models with Latent Variables, 10.1007/s11336-010-9174-4
  60. Yang Mingan, Dunson David B., Baird Donna, Semiparametric Bayes hierarchical models with mean and variance constraints, 10.1016/j.csda.2010.03.025