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Influence diagnostics in linear and nonlinear...
Journal article

Influence diagnostics in linear and nonlinear mixed-effects models with censored data

Abstract

HIV RNA viral load measures are often subjected to some upper and lower detection limits depending on the quantification assays, and consequently the responses are either left or right censored. Linear and nonlinear mixed-effects models, with modifications to accommodate censoring (LMEC and NLMEC), are routinely used to analyze this type of data. Recently, Vaida and Liu (2009) proposed an exact EM-type algorithm for LMEC/NLMEC, called the SAGE …

Authors

Matos LA; Lachos VH; Balakrishnan N; Labra FV

Journal

Computational Statistics & Data Analysis, Vol. 57, No. 1, pp. 450–464

Publisher

Elsevier

Publication Date

January 2013

DOI

10.1016/j.csda.2012.06.021

ISSN

0167-9473