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Software for non‐linear mixed effects modelling: a review of several packages
Author(s) -
Smith Michael K.
Publication year - 2003
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.38
Subject(s) - computer science , software , contrast (vision) , mixed model , generalized linear mixed model , linear model , r package , data mining , data science , software engineering , machine learning , artificial intelligence , programming language
This paper gives some background information on what non‐linear mixed effects models are, why they can be useful in analysing repeated measures and what makes analysing such data challenging. Various software packages and routines are available to perform this kind of analysis, and this paper will compare and contrast these. Copyright © 2003 John Wiley & Sons, Ltd.