1984
DOI: 10.2307/2530913
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A Growth-Curve Model Approach to Multivariate Quantal Bioassay

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Cited by 25 publications
(7 citation statements)
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“…This is also the case for the models of Mayer et al [4] (two-step linear regression approach for very small effects) or Van Wijk and Kraaij [5] (extended log-logistic model). Carter and Hubert [6] used a multivariate regression and have shown that, in practice, an inverse time model is appropriate.…”
Section: Expressing Lc50 As a Function Of Timementioning
confidence: 99%
“…This is also the case for the models of Mayer et al [4] (two-step linear regression approach for very small effects) or Van Wijk and Kraaij [5] (extended log-logistic model). Carter and Hubert [6] used a multivariate regression and have shown that, in practice, an inverse time model is appropriate.…”
Section: Expressing Lc50 As a Function Of Timementioning
confidence: 99%
“…Reinsel (1982) extended the univariate growth curve model to the multivariate case, where several response variables are measured over multiple time points. The multivariate growth curve model enables us to examine relationships between different response variables (also see Carter & Hubert, 1984;Lundbye-Christensen, 1996;Nummi & MOtt6nen, 2000). Another recent extension is to impose reduced-rank restrictions on the univariate growth curve model, motivated by the fact that the mathematical structure of the growth curve model is akin to that of the reduced-rank regression model (Albert & Kshirsagar, 11993;Reinsel & Velu, 1998, pp.…”
Section: Introductionmentioning
confidence: 99%
“…This is also the case for the models of Mayer et al [4] (two‐step linear regression approach for very small effects) or Van Wijk and Kraaij [5] (extended log‐logistic model). Carter and Hubert [6] used a multivariate regression and have shown that, in practice, an inverse time model is appropriate.…”
Section: Methods and Derivation Of An Alternative Approachmentioning
confidence: 99%