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Full-Text Articles in Physical Sciences and Mathematics
Modeling And Design To Detect Interaction Of Insecticides, Herbicides And Other Similar Compounds, Timothy E. O'Brien
Modeling And Design To Detect Interaction Of Insecticides, Herbicides And Other Similar Compounds, Timothy E. O'Brien
Conference on Applied Statistics in Agriculture
This paper discusses model and experimental design aspects of agricultural studies aimed at discerning antagonism or synergy between two or more insecticides, herbicides, or other similar compounds. The developed methods involve a broad class of generalised nonlinear models, which are easily fitted to data using popular statistical packages such as the NLMIXED procedure in SAS® software. Sample computer code is given in the Appendix.
Determination Of The Inoculation Frequency, Timing Of Inoculation And Dose Of A Bacterial Ruminal Inoculant For Acidosis Prevention In Feedlot Cattle, J. F. Boucher, W. J. Smolenski, J. A. Robinson
Determination Of The Inoculation Frequency, Timing Of Inoculation And Dose Of A Bacterial Ruminal Inoculant For Acidosis Prevention In Feedlot Cattle, J. F. Boucher, W. J. Smolenski, J. A. Robinson
Conference on Applied Statistics in Agriculture
We are evaluating the efficacy of a ruminal bacterial inoculant (Megasphaera elsdenii 407 A) for prevention of acute acidosis in grain-fed cattle. As a part of this process, we examined the effects of inoculation frequency, timing of inoculation and dose of 407 A for prevention of acute acidosis in ruminally fistulated cattle. Three levels of frequency, two levels of timing and three doses were considered, however, a complete 3x2x3 factorial study was not run because of resource constraints. The study was conducted in two separate trials. The first was designed as a 3x2 factorial experiment with inoculation frequency and timing …
The Effect Of Design And Dose Level Choice On Estimatlng The Optimal Dose In A Quantitative Dose-Response Experiment, Henry R. Rolka, George A. Milliken, James R. Schwenke, Marta Remmenga
The Effect Of Design And Dose Level Choice On Estimatlng The Optimal Dose In A Quantitative Dose-Response Experiment, Henry R. Rolka, George A. Milliken, James R. Schwenke, Marta Remmenga
Conference on Applied Statistics in Agriculture
D-optimality is a commonly used criterion to evaluate a design with respect to parameter estimation. The variance of the optimal dose estimate is another criterion for evaluating a design. The quantitative dose-response experiment involves fitting a model to data and estimating an optimal dose. Two techniques for estimating an optimal dose and three models are used to compare the variances of optimal dose estimates over nine equally spaced balanced designs and five fixed unequally spaced six-point designs. The results show that a design which is more D-optimal than another design does not necessarily produce optimal dose estimates with less variance.