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On model expansion, model contraction, identifiability and prior Information: Two illustrative scenarios involving mismeasured variables

Publication ,  Journal Article
Gustafson, P; Gelfand, AE; Sahu, SK; Johnson, WO; Hanson, TE; Joseph, L; Lee, J
Published in: Statistical Science
May 1, 2005

When a candidate model for data is nonidentifiable, conventional wisdom dictates that the model must be simplified somehow so as to gain identifiability. We explore two scenarios involving mismeasured variables where, in fact, model expansion, as opposed to model contraction, might be used to obtain identifiability. We compare the merits of model contraction and model expansion. We also investigate whether it is necessarily a good idea to alter the model for the sake of identifiability. In particular, estimators obtained from identifiable models are compared to those obtained from nonidentifiable models in tandem with crude prior distributions. Both asymptotic theory and simulations with Markov chain Monte Carlo-based estimators are used to draw comparisons. A technical point which arises is that the asymptotic behavior of a posterior mean from a nonidentifiable model can be investigated using standard asymptotic theory, once the posterior mean is described in terms of the identifiable part of the model only. © Institute of Mathematical Statistics, 2005.

Duke Scholars

Published In

Statistical Science

DOI

ISSN

0883-4237

Publication Date

May 1, 2005

Volume

20

Issue

2

Start / End Page

111 / 140

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 0104 Statistics
 

Citation

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ICMJE
MLA
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Gustafson, P., Gelfand, A. E., Sahu, S. K., Johnson, W. O., Hanson, T. E., Joseph, L., & Lee, J. (2005). On model expansion, model contraction, identifiability and prior Information: Two illustrative scenarios involving mismeasured variables. Statistical Science, 20(2), 111–140. https://doi.org/10.1214/088342305000000098
Gustafson, P., A. E. Gelfand, S. K. Sahu, W. O. Johnson, T. E. Hanson, L. Joseph, and J. Lee. “On model expansion, model contraction, identifiability and prior Information: Two illustrative scenarios involving mismeasured variables.” Statistical Science 20, no. 2 (May 1, 2005): 111–40. https://doi.org/10.1214/088342305000000098.
Gustafson P, Gelfand AE, Sahu SK, Johnson WO, Hanson TE, Joseph L, et al. On model expansion, model contraction, identifiability and prior Information: Two illustrative scenarios involving mismeasured variables. Statistical Science. 2005 May 1;20(2):111–40.
Gustafson, P., et al. “On model expansion, model contraction, identifiability and prior Information: Two illustrative scenarios involving mismeasured variables.” Statistical Science, vol. 20, no. 2, May 2005, pp. 111–40. Scopus, doi:10.1214/088342305000000098.
Gustafson P, Gelfand AE, Sahu SK, Johnson WO, Hanson TE, Joseph L, Lee J. On model expansion, model contraction, identifiability and prior Information: Two illustrative scenarios involving mismeasured variables. Statistical Science. 2005 May 1;20(2):111–140.

Published In

Statistical Science

DOI

ISSN

0883-4237

Publication Date

May 1, 2005

Volume

20

Issue

2

Start / End Page

111 / 140

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 0104 Statistics