Abstract We propose a double-robust procedure for modeling the correlation matrix of a longitudinal dataset. It is based on an alternative Cholesky ...
Sep 23, 2011 · We propose a double-robust procedure for modeling the correlation matrix of a longitudinal dataset. It is based on an alternative Cholesky ...
PDF | We propose a double-robust procedure for modeling the correlation matrix of a longitudinal dataset. It is based on an alternative Cholesky.
Abstract. Modelling the covariance structure of multivariate longitudinal data is more challenging than its univariate counterpart, owing to the complex ...
We propose a double-robust procedure for modeling the correlation matrix of a longitudinal dataset. It is based on an alternative Cholesky decomposition of ...
A Fisher scoring algorithm for computing the maximum likelihood estimator of the parameters when the nonredundant and unconstrained entries of (L,D) are ...
We propose a double-robust procedure for modeling the correlation matrix of a longitudinal dataset. It is based on an alternative Cholesky decomposition of ...
Aug 17, 2017 · Estimating correlation coefficients among outcomes is one of the most important analytical tasks in epidemiological and clinical research.
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Reference: Robust estimation of the correlation matrix of longitudinal data (Mehdi Maadooliat, Mohsen Pourahmadi and Jianhua Z. Huang), In Statistics and ...
In this article, we develop a new robust estimating equation method for estimation of longitudinal models when there are outliers. Specifically, to achieve ...