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• W2783243577 abstract "An efficient and accurate numerical approximation methodology useful for obtaining the observed information matrix and subsequent asymptotic covariance matrix when fitting models with the EM algorithm is presented. The numerical approximation approach is compared to existing algorithms intended for the same purpose, and the computational benefits and accuracy of this new approach are highlighted. Instructive and real-world examples are included to demonstrate the methodology concretely, properties of the estimator are discussed in detail, and a Monte Carlo simulation study is included to investigate the behaviour of a multi-parameter item response theory model using three competing finite-difference algorithms." @default.
• W2783243577 created "2018-01-26" @default.
• W2783243577 creator A5028731830 @default.
• W2783243577 date "2018-01-09" @default.
• W2783243577 modified "2023-10-18" @default.
• W2783243577 title "Numerical approximation of the observed information matrix with Oakes' identity" @default.
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• W2783243577 doi "https://doi.org/10.1111/bmsp.12127" @default.
• W2783243577 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29315543" @default.
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