Applications of scaled rank-sum statistics in herbicide QSAR

Quantitative structure/activity relationships (QSARs) can be delineated by multiple regression analysis based on substituent properties, or by comparative molecular field analysis (CoMFA). In either case, the negative logarithms of the doses required to achieve some particular effect (e.g., pED50) h...

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Bibliographic Details
Main Authors Clark, R.D. (Monsanto Company, St. Louis, MO.), Parlow, J.J, Brannigan, L.H, Schnur, D.M, Duewer, D.L
Format Book
LanguageEnglish
Published Washington, DC (USA) American Chemical Society 1995
Subjects
HERBICIDAS
HERBICIDE
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Summary:Quantitative structure/activity relationships (QSARs) can be delineated by multiple regression analysis based on substituent properties, or by comparative molecular field analysis (CoMFA). In either case, the negative logarithms of the doses required to achieve some particular effect (e.g., pED50) have generally been used as response variables. In pesticide development, these must ultimately be obtained from tests on intact organisms. Unfortunately, such parametric point-estimates derived from in vivo titration curves may unnecessarily limit the quality of the QSAR obtained. We show here that Scaled Rank Sums (SRS) represent an alternative, non-parametric approach which can provide robust quantitation of pesticidal efficacy suitable for either substituentwise regression analysis or CoMFA
Bibliography:H60
9719743
ISBN:9780841233218
0841233217