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Articles 1 - 14 of 14
Full-Text Articles in Physical Sciences and Mathematics
Evaluating Linear And Nonlinear Models For The Respiration Rate Of Four Breeds Of Heat Stressed Feedlot Heifers, Q. Huang, A. M. Parkhurst, T. M. Brown-Brandl, R. A. Eigenberg, J. A. Nienaber
Evaluating Linear And Nonlinear Models For The Respiration Rate Of Four Breeds Of Heat Stressed Feedlot Heifers, Q. Huang, A. M. Parkhurst, T. M. Brown-Brandl, R. A. Eigenberg, J. A. Nienaber
Conference on Applied Statistics in Agriculture
Heat stress is a factor that causes loss of production and even death in cattle. Animals differ in vulnerability to heat stress. One reason for the difference may be the coat color associated with different breeds or genotypes. A good measure of the heat stress is respiration rate which increases in response to increasing ambient temperature. The objective of this study is to characterize the respiration rates of four genotypes of heat stressed feedlot heifers. Linear and nonlinear models will be compared to find an appropriate method of detecting differences among genotypes.
A Comparison Of Models And Designs For Experiments With Nonlinear Dose-Response Relationships, Shengjie Guo, W. W. Stroup, E. T. Paparozzi, M. E. Conley
A Comparison Of Models And Designs For Experiments With Nonlinear Dose-Response Relationships, Shengjie Guo, W. W. Stroup, E. T. Paparozzi, M. E. Conley
Conference on Applied Statistics in Agriculture
Research investigating dose-response relationship is common in agricultural science. Animal response to drug dose and plant response to amount of irrigation, pesticide, or fertilizer are familiar examples. This paper is motivated by plant nutrition research in horticulture. Plant response to level of nutrient applied is typically sigmoidal, i.e. no response at very low levels, observable response at mid-levels, point-of-diminishing returns and plateau at high levels. Plant scientists need accurate estimates of these response relationships 1) to determine lower threshold below which plants show deficiency symptoms and 2) to determine upper point-of-diminishing returns, above which excessive doses are economically and environmentally …
Decision Quality Metrics – A Tool For Managing Quality Of Repeated Bioassays, Nancy Ferry, William Letsinger
Decision Quality Metrics – A Tool For Managing Quality Of Repeated Bioassays, Nancy Ferry, William Letsinger
Conference on Applied Statistics in Agriculture
Bioassays are often used in tiered screening systems to detect potential products, such as crop protection products. Often these assays are not replicated. The ultimate products of these bioassays are decisions, with biologically “active” compounds advanced to the next level of screening. Activity is determined by the response of the test organisms (e.g., weeds, insects or fungi) to each compound. The reproducibility of the bioassay is crucial. There are two types of possible errors in screening, false positives and false negatives. The quality of the decisions based upon these bioassays can be monitored through time using controls. This paper will …
Evaluating Nonlinear Crossed Random Effects Models For Comparing Temperature Of Feeding Pigs Under Different Thermal Environments, M. Zhou, A. M. Parkhurst, R. A. Eigenberg, J. A. Nienaber, G. L. Hahn
Evaluating Nonlinear Crossed Random Effects Models For Comparing Temperature Of Feeding Pigs Under Different Thermal Environments, M. Zhou, A. M. Parkhurst, R. A. Eigenberg, J. A. Nienaber, G. L. Hahn
Conference on Applied Statistics in Agriculture
The thermal environment plays a large role in an animal’s ability to convert feed into weight gain. A better understanding of a pig’s metabolism will help swine producers select environmental specifications for optimizing feed conversion. The objectives of this study are to 1) characterize the thermoregulatory responses of pigs during a feeding event 2) compare those responses for three thermal environmental treatments applied in a Latin Square design 3) investigate different procedures for fitting nonlinear mixed-effect models with crossed random effects (NLME function in R, %NLINMIX macro in SAS, random effects modeling in AD Model Builder: ADMB-RE). We found that …
Modeling Dispersal Of Yellow Starthistle In The Canyon Grasslands Of North Central Idaho, Bahman Shafii, William J. Price, Timothy S. Prather, Lawrence W. Lass, Derek Howard
Modeling Dispersal Of Yellow Starthistle In The Canyon Grasslands Of North Central Idaho, Bahman Shafii, William J. Price, Timothy S. Prather, Lawrence W. Lass, Derek Howard
Conference on Applied Statistics in Agriculture
Yellow starthistle is an invasive plant species that reduces productivity and plant diversity within the canyon grasslands of Idaho. Early detection of yellow starthistle and predicting its spread have important managerial implications that could greatly reduce the economic/environmental losses due to this weed. The spread of an invasive plant species depends on its ability to reproduce and disperse seed into new areas. Typically, information on the factors that directly affect a plant’s ability to reproduce and subsequently disperse seed is not available or difficult to obtain. Alternatively, topographic factors, such as slope and aspect as well as competitive correlates such …
All Possible Model Selection In Proc Mixed – A Sas Macro Application, George C J Fernandez
All Possible Model Selection In Proc Mixed – A Sas Macro Application, George C J Fernandez
Conference on Applied Statistics in Agriculture
A user-friendly SAS macro application to perform all possible model selection of fixed effects including quadratic and cross products in the presence of random and repeated measures effects using SAS PROC MIXED is available. This macro application will complement the model selection option currently available in the SAS PROC REG for multiple linear regressions and the experimental SAS procedure GLMSELECT that focuses on the standard independently and identically distributed general linear model for univariate responses. Options are also included in this macro to select the best covariance structure associated with the user-specified fully saturated repeated measures model; to graphically explore …
Using Random Sampling To Estimate Insect Counts As Response Surfaces Involving Space And Time, Benjamin G. Mullinix, Glynn Tillman
Using Random Sampling To Estimate Insect Counts As Response Surfaces Involving Space And Time, Benjamin G. Mullinix, Glynn Tillman
Conference on Applied Statistics in Agriculture
In fall 2000, an on-farm sustainable agricultural research project was established for cotton (Gossypium hirstum L.) in Tift County, Georgia. Twenty fields that were to be planted to cotton in 2001 were identified which were approximately 5 to 10 acres in size. Four randomly selected fields were assigned to each of five cover crops: 1) cereal rye (Secale cereale L.); 2) crimson clover (Trifolium incarnatum L.); 3) legume mixture of balansa clover (T. michelianum Savi), crimson clover, and hairy vetch (Vicia villosa Roth); 4) previous legume mixture plus cereal rye; and 5) no cover crop (fallow) in conventionally tilled fields. …
An Estimator Of Treatment Effects Under Combined Sampling And Experimental Designs, Christina D. Smith
An Estimator Of Treatment Effects Under Combined Sampling And Experimental Designs, Christina D. Smith
Conference on Applied Statistics in Agriculture
Sampling design and experimental design have developed relatively independently in recent statistical history. However, many studies do involve both a sampling design and an ex-perimental design. For example, a polluted site may be exhaustively partitioned into area plots, a random sample of plots selected, and the selected plots randomly assigned to three clean-up regimens. To date there is no commonly used procedure for incorporating both the sampling design and the experimental design into the estimation of treatment effects. For this reason we will consider an estimator of treatment effect that does incorporate both sampling and experimental designs and discuss some …
Appropriate Statistical Methods For Comparing Sources Of Nutritional Methionine, D. D. Kratzer, R. C. Littell
Appropriate Statistical Methods For Comparing Sources Of Nutritional Methionine, D. D. Kratzer, R. C. Littell
Conference on Applied Statistics in Agriculture
Kratzer and Ash(1996) presented Experimentation Science as a process to accomplish the Scientific Method with a complete protocol including relevant statistical design and analyses The first principal to sound Experimentation Science is the principle of Relevance. This is a case study primarily of Relevance in Experimentation Science. In our consulting work we found a so called “performance” design as not relevant because of the use of null hypothesis testing to promote a concept of equivalence. The best alternative involves equivalence testing, more replication and representative-ness. Secondly we found a dose response design for two products where non-linear asymptotic regression is …
Clustering A Series Of Replicated Polyploid Gene Expression Experiments In Maize, Lingling An, Nicole C. Riddle, James A. Birchler, R. W. Doerge
Clustering A Series Of Replicated Polyploid Gene Expression Experiments In Maize, Lingling An, Nicole C. Riddle, James A. Birchler, R. W. Doerge
Conference on Applied Statistics in Agriculture
Ploidy level is defined as the number of individual sets of chromosomes contained in a single cell. Many important crop plants, such as potato, soybean and wheat are polyploid. Although it is widely known that polyploidy is a frequent evolutionary event, it is not fully understand why polyploids have been so successful. In this work cluster analysis is employed to study gene expression changes in a maize inbred line (B73) across a range of polyploidy levels. The B73 ploidy series includes monoploid, diploid, triploid and tetraploid plants and consists of biological and technical replicates as measured by microarray technology. An …
A Visual Aid For Statisticians And Molecular Biologists Working With Microarray Experiments, Deborah L. Boykin, Earl W. Taliercio, Rowena Y. Kelley, W. Paul Williams
A Visual Aid For Statisticians And Molecular Biologists Working With Microarray Experiments, Deborah L. Boykin, Earl W. Taliercio, Rowena Y. Kelley, W. Paul Williams
Conference on Applied Statistics in Agriculture
The use of microarrays to measure the expression of large numbers of genes simultaneously is increasing in agriculture research. Statisticians are expected to help biologists analyze these large data sets to identify biologically important genes that are differentially regulated in the samples under investigation. However, molecular biologists are often unfamiliar with the statistical methods used to analyze microarrays. Presented here are methods developed to graphically represent microarray data and various types of errors commonly associated with microarrays to help visualize sources of error. Two case studies were used. In case study one, genes differentially regulated when two corn lines, one …
Dose-Response Modeling With Marginal Information On A Missing Categorical Covariate, John R. Stevens, David I. Schlipalius
Dose-Response Modeling With Marginal Information On A Missing Categorical Covariate, John R. Stevens, David I. Schlipalius
Conference on Applied Statistics in Agriculture
When the relationship between a dosage-type variable and a binary outcome depends on a categorical variable, a common analysis would employ a dose-response model with the categorical variable as a covariate. When the level of the categorical variable is not known for all subjects, however, the standard dose-response model alone cannot provide useful inference. We present an EM-based approach to account for the missing covariate in a dose-response model setting when additional knowledge about the marginal distribution of the covariate is available. This approach is motivated by a study of the beetle Rhyzopertha dominica, a pest of stored grain in …
A Comparison Of Multiple Testing Methods: Spinosad As A Treatment For Lice On Cattle, Zhanglin Cui, Daniel H. Mowrey, Alan G. Zimmermann, Douglas E. Hutchens
A Comparison Of Multiple Testing Methods: Spinosad As A Treatment For Lice On Cattle, Zhanglin Cui, Daniel H. Mowrey, Alan G. Zimmermann, Douglas E. Hutchens
Conference on Applied Statistics in Agriculture
A common problem in statistics is making multiple tests of hypotheses without controlling for the type I error rate. SAS has identified several different methods to adjust p-values for multiple testing. To compare the effect of these methods, an animal health dataset that deals with the treatment of cattle lice was examined. Clinical trials were conducted in Illinois and Wisconsin to evaluate the efficacy of two formulations of a new product Spinosad, two commercially available positive controls, and an untreated negative control. A baseline lice count was recorded prior to the treatment. After treatment, weekly measurements of lice counts were …
Editor's Preface And Table Of Contents, John E. Boyer Jr.
Editor's Preface And Table Of Contents, John E. Boyer Jr.
Conference on Applied Statistics in Agriculture
These proceedings contain papers presented in the eighteenth annual Kansas State University Conference on Applied Statistics in Agriculture, held in Manhattan, Kansas, April 30-May 2, 2006.