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Full-Text Articles in Physical Sciences and Mathematics

The Row-Column Confounded 2MX4N Factorial Design And Its Different Fractions, Md Shamsuddin, Mian A S Adnan Apr 2005

The Row-Column Confounded 2MX4N Factorial Design And Its Different Fractions, Md Shamsuddin, Mian A S Adnan

Conference on Applied Statistics in Agriculture

The row-column confounded 2mX4n factorial designs and its different fractions can be constructed and analyzed using pseudo factors in the 4n portion. (Examples are shown)


The Use Of Pseudo Factors In 4N, 8N, 2MX4N, 2NX8N Factorial Designs, Md Shamsuddin, Mian A S Adnan Apr 2005

The Use Of Pseudo Factors In 4N, 8N, 2MX4N, 2NX8N Factorial Designs, Md Shamsuddin, Mian A S Adnan

Conference on Applied Statistics in Agriculture

The confounded factorial designs of the experiments 4n, 2mX4n, 8n, etc, and their different fractions can be constructed and analyzed using a suitable method of pseudo factors known as Rotation-Conversion Method. An example is shown.


The 3N Circular Factorial Designs: More Robust Estimate Of All Factorial Effects, Md Shamsuddin Apr 2005

The 3N Circular Factorial Designs: More Robust Estimate Of All Factorial Effects, Md Shamsuddin

Conference on Applied Statistics in Agriculture

A 3n circular factorial design which facilitates estimates of all factorial effects providing internal partial confounding with blocks within each of its diameters in different directions is constructed for use in analyzing the multi-directional data of different disciplines. The design possesses small error variance by eliminating the heterogeneity in different directions. An example is given.


Spatial Variability In Aggregation Based On Geostatistical Analysis, Shoufan Fang, George Z. Gertner, Guangxing Wang, Alan B. Anderson Apr 2005

Spatial Variability In Aggregation Based On Geostatistical Analysis, Shoufan Fang, George Z. Gertner, Guangxing Wang, Alan B. Anderson

Conference on Applied Statistics in Agriculture

This study derived the equations for computing the spatial variability in the aggregation of original maps of continuous attributes. The derivation of the equations is based on traditional statistical and geostatistical principles. The derived equations can be used to compute the variance, covariance, and spatial (auto-/cross-) covariance of the aggregated pixels and sub-areas in a given study area. Using the derived equations, the total uncertainty within a study area will not change after aggregation. For a case study, it has been shown that aggregation will reduce the values of variance/covariance and spatial covariance of the aggregated individual pixels. It was …


R2 Statistics For Mixed Models, Matthew Kramer Apr 2005

R2 Statistics For Mixed Models, Matthew Kramer

Conference on Applied Statistics in Agriculture

The R2 statistic, when used in a regression or ANOVA context, is appealing because it summarizes how well the model explains the data in an easy-to-understand way. R2 statistics are also useful to gauge the effect of changing a model. Generalizing R2 to mixed models is not obvious when there are correlated errors, as might occur if data are georeferenced or result from a designed experiment with blocking. Such an R2 statistic might refer only to the explanation associated with the independent variables, or might capture the explanatory power of the whole model. In the latter …


A Bayesian And Covariate Approach To Combine Results From Multiple Microarray Studies, John R. Stevens, R. W. Doerge Apr 2005

A Bayesian And Covariate Approach To Combine Results From Multiple Microarray Studies, John R. Stevens, R. W. Doerge

Conference on Applied Statistics in Agriculture

The growing popularity of microarray technology for testing changes in gene expression has resulted in multiple laboratories independently seeking to identify genes related to the same disease in the same organism. Despite the uniform nature of the technology, chance variation and fundamental differences between laboratories can result in considerable disagreement between the lists of significant candidate genes from each laboratory. By adjusting for known differences between laboratories through the use of covariates and employing a Bayesian framework to effectively account for between-laboratory variability, the results of multiple similar studies can be systematically combined via a meta-analysis. Meta-analyses yield additional information …


A Bayesian Random Coefficient Nonlinear Regression Model For A Split-Plot Experiment, Reid D. Landes, Trey Spencer, Ian A. Zelaya Apr 2005

A Bayesian Random Coefficient Nonlinear Regression Model For A Split-Plot Experiment, Reid D. Landes, Trey Spencer, Ian A. Zelaya

Conference on Applied Statistics in Agriculture

In random coefficients regression, we are often interested in the mean of a certain para-meter particular to the experimental unit (EU). When the mean depends on some treatment regimen, we are then interested in comparing the means among the different treatments. When the EUs are repeatedly measured on a variable containing information about the EU parameter, a standard procedure is to estimate each EU parameter and treat the estimates as the response variables. This is especially true when the regression model for an EU is non-linear. Often, for designed experiments with a factorial treatment structure, the estimated EU parameters are …


Evaluating The Effects Of Monensin Overdose In Dairy Cattle, Rebecca R. Hozak, James T. Symanowski, David G. Mcclary, Meliton N. Novilla, John C. Kube, R. Ken Mcguffey, John I. D. Wilkinson, Howard B. Green, Elvin E. Thomas Apr 2005

Evaluating The Effects Of Monensin Overdose In Dairy Cattle, Rebecca R. Hozak, James T. Symanowski, David G. Mcclary, Meliton N. Novilla, John C. Kube, R. Ken Mcguffey, John I. D. Wilkinson, Howard B. Green, Elvin E. Thomas

Conference on Applied Statistics in Agriculture

Monensin is approved as a feed additive by the FDA Center for Veterinary Medicine to increase milk production efficiency in lactating dairy cattle. To assess the effects of a gross error in mixing monensin into cattle feed, a 10-fold overdose was given for three consecutive days to naïve cows as well as cows previously dosed with monensin within the label range. Cows were evaluated during the overdose and for a subsequent 4 week observation period. Physiological variables were analyzed, including dry matter intake, body weight, body condition score, and serum chemistry profile. Production variables were analyzed, including milk yield and …


The Effect Of Monensin On Lactation Dairy Cows: A Dose Response Evaluation, Zhanglin Cui, Daniel Mowrey, Alan G. Zimmermann, James T. Symanowski, Howard B. Green, John I. D. Wilkinson Apr 2005

The Effect Of Monensin On Lactation Dairy Cows: A Dose Response Evaluation, Zhanglin Cui, Daniel Mowrey, Alan G. Zimmermann, James T. Symanowski, Howard B. Green, John I. D. Wilkinson

Conference on Applied Statistics in Agriculture

Monensin (Rumensin®) was fed at doses of 0, 8, 16, or 24 ppm to 966 dairy cows in nine different geographical locations in the USA and Canada. A dose response analysis was conducted on the primary variable, milk production efficiency, to determine the most appropriate dose response function, establish a minimum effective dose, and, when possible, determine a maximum effective dose. Linear mixed models (SAS® Proc Mixed v6.12) were fit to the data. Linear contrasts comparing the non-zero doses of monensin to the control were done to initially determine a minimum effective dose from the 3 non-zero design points. In …


Evaluating Clinical Mastitis In Dairy Cattle Fed Monensin, Meihua Qiao, Daniel Mowrey, Alan Zimmermann, James T. Symanowski, Howard B. Green, John I. D. Wilkinson Apr 2005

Evaluating Clinical Mastitis In Dairy Cattle Fed Monensin, Meihua Qiao, Daniel Mowrey, Alan Zimmermann, James T. Symanowski, Howard B. Green, John I. D. Wilkinson

Conference on Applied Statistics in Agriculture

The effect of Monensin on clinical mastitis in dairy cattle was evaluated from data collected at nine geographical clinical field trials using 966 Holstein cows and heifers in the United States and Canada. At each site, a randomized complete block design was conducted. Monensin (Rumensin®) was fed at concentrations of 0, 8, 16, or 24 ppm in a total mixed ration beginning 21 days before first calving for all nine sites, up to 7 days after second calving for six sites, and 203 days after second calving for three sites. Quarter milk samples were taken and cultured to determine the …


Modeling The Body Temperature Of Heat Stressed Holstein Lying Cows Under Two Different Cooling Processes, M. Zhou, A. M. Parkhurst, P. E. Hillman, C. N. Lee Apr 2005

Modeling The Body Temperature Of Heat Stressed Holstein Lying Cows Under Two Different Cooling Processes, M. Zhou, A. M. Parkhurst, P. E. Hillman, C. N. Lee

Conference on Applied Statistics in Agriculture

Heat stressed cows produce less milk. Thus, a major challenge during hot summer months is to keep the dairy barn at a comfortable temperature. Use of fans is an economical solution but the combination of both spray and fans appears to be an even more effective way to cool cows and improve the milk production than using fans alone. The goal of this study is to recommend an appropriate method for comparing the dynamics of the cooling processes. The first step is to develop a nonlinear model to characterize the thermoregulatory responses of heat stressed dairy cows when they are …


Bayesian Analysis Of Dose-Response Calibration Curves, William J. Price, Bahman Shafii Apr 2005

Bayesian Analysis Of Dose-Response Calibration Curves, William J. Price, Bahman Shafii

Conference on Applied Statistics in Agriculture

The statistical analysis of dose-response experiments typically models observed responses as a function of an applied dosage series. The estimated "dose-response curve" is used in predicting future responses, however, it is also commonly rewritten in an inverted form where dose is expressed as a function of the response. This modified "calibration curve" is useful in cases where observed responses are available, but their associated dosages are unknown. Traditional statistical techniques for the estimation of unknown doses from the dose-response curve are problematic, involving approximate solutions and methods. Alternatively, this type of inverse calibration problem naturally falls into the framework of …


Predicting Soil Temperatures In High Tunnels Using A Dynamic Model Based On Newtonian Law Of Cooling, Anil K. Jayaprakash, Kent M. Eskridge, Laurie Hodges, Daryl A. Travnicek Apr 2005

Predicting Soil Temperatures In High Tunnels Using A Dynamic Model Based On Newtonian Law Of Cooling, Anil K. Jayaprakash, Kent M. Eskridge, Laurie Hodges, Daryl A. Travnicek

Conference on Applied Statistics in Agriculture

High tunnels are low cost temporary greenhouses that are often used to extend the growing season for high value crops such as tulips, muscari, sweet pea cultivars, and hyacinth beans. Profitability depends on selection and timing of crops to optimize use of these structures. Predicting soil temperatures in high tunnels as a function of outside temperature is a critical factor in crop selection and timing. However, predicting soil temperatures is difficult because air temperatures constantly change from hour to hour and day to day. We develop a model to account for temperature dynamics in high tunnels by modifying the fundamental …


Design And Analysis Of Biological Assays Of Mixtures, Nancy Ferry, Bruce H. Stanley, Gregory Armel Apr 2005

Design And Analysis Of Biological Assays Of Mixtures, Nancy Ferry, Bruce H. Stanley, Gregory Armel

Conference on Applied Statistics in Agriculture

The simultaneous activity of multiple stimuli can be difficult to analyze, particularly on biological systems. However, these analyses are becoming increasingly important in drug or pesticide formulation for efficacy. This article will review techniques for the design and analysis of bioassays of mixtures. The two major techniques that will be reviewed are based upon the concepts of response and potency. Particular emphasis will be placed upon measuring levels of synergy, i.e., when the activity is greater than the sum of its parts, and antagonism, i.e., when the activity is less than would be expected. Theoretical examples will be given to …


Statistical Analysis Of Gene Expression Microarrays, Tanzy Love, Alicia Carriquiry Apr 2005

Statistical Analysis Of Gene Expression Microarrays, Tanzy Love, Alicia Carriquiry

Conference on Applied Statistics in Agriculture

This manuscript is composed of two major sections. In the first section of the manuscript we introduce some of the biological principles that form the bases of cDNA microarrays and explain how the different analytical steps introduce variability and potential biases in gene expression measurements that can sometimes be dificult to properly address. We address statistical issues associated to the measurement of gene expression (e.g., image segmentation, spot identification), to the correction for back-ground fluorescence and to the normalization and re-scaling of data to remove effects of dye, print-tip and others on expression. In this section of the manuscript we …


Editor's Preface And Table Of Contents, John E. Boyer Jr. Apr 2005

Editor's Preface And Table Of Contents, John E. Boyer Jr.

Conference on Applied Statistics in Agriculture

These proceedings contain papers presented in the seventeenth annual Kansas State University Conference on Applied Statistics in Agriculture, held in Manhattan, Kansas, April 24-26, 2005.