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Multiple Imputation for Missing Data: Concepts and New ...

Multiple Imputation for Missing Data: Concepts and New ...

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nj−k−1 random variate and n j is the number of nonmissing observations for Y j. The regression coeffi-cients are drawn as β ∗ = βˆ+ σ ∗jV 0 hjZ where V0 hj is the upper triangular matrix in the Cholesky decomposition, V j = V0 hj V hj, and Z is a vector of k + 1 independent random normal variates. 2. The missing values are then ...

  Multiple, Imputation, Multiple imputation, Variate

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