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Information Journal Paper

Title

PARAMETER IDENTIFIABILITY ISSUES IN A LATENT MARKOV MODEL FOR MISCLASSIFIED BINARY RESPONSES

Pages

  39-57

Abstract

 Medical researchers may be interested in disease processes that are not directly observable. Imperfect diagnostic tests may be used repeatedly to monitor the condition of a patient in the absence of a gold standard. We consider parameter IDENTIFIABILITY and ESTIMABILITY in a Markov model for alternating binary longitudinal responses that may be misclassified. Exactly two distinct sets of parameter values are shown to generate the distribution for the data in a common situation and we propose a restriction to distinguish the two. Even with the restriction, parameters may not be estimable. Issues of sampling and correct model specification are discussed.

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    APA: Copy

    ROSYCHUK, R.J., & THOMPSON, M.E.. (2004). PARAMETER IDENTIFIABILITY ISSUES IN A LATENT MARKOV MODEL FOR MISCLASSIFIED BINARY RESPONSES. JOURNAL OF THE IRANIAN STATISTICAL SOCIETY (JIRSS), 3(1), 39-57. SID. https://sid.ir/paper/117835/en

    Vancouver: Copy

    ROSYCHUK R.J., THOMPSON M.E.. PARAMETER IDENTIFIABILITY ISSUES IN A LATENT MARKOV MODEL FOR MISCLASSIFIED BINARY RESPONSES. JOURNAL OF THE IRANIAN STATISTICAL SOCIETY (JIRSS)[Internet]. 2004;3(1):39-57. Available from: https://sid.ir/paper/117835/en

    IEEE: Copy

    R.J. ROSYCHUK, and M.E. THOMPSON, “PARAMETER IDENTIFIABILITY ISSUES IN A LATENT MARKOV MODEL FOR MISCLASSIFIED BINARY RESPONSES,” JOURNAL OF THE IRANIAN STATISTICAL SOCIETY (JIRSS), vol. 3, no. 1, pp. 39–57, 2004, [Online]. Available: https://sid.ir/paper/117835/en

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