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Multivariate iteratively re-weighted least squares, with applications to dose-response data

✍ Scribed by M. S. Wilhelm; E. M. Carter; J. J. Hubert


Publisher
John Wiley and Sons
Year
1998
Tongue
English
Weight
159 KB
Volume
9
Category
Article
ISSN
1180-4009

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✦ Synopsis


This paper develops a general multivariate iteratively re-weighted least squares (MIRLS) algorithm to ®t multinomial data for a large class of link functions. The algorithm is shown to be very useful for the generalized linear model when applied to ordered data using either the logit or the normit link. Since binomial dose-response experiments are often monitored over time, then these dependent binomial responses can be modelled by using either link function. Examples from acute toxicity and teratology illustrate the algorithm.