2018 Conference on Applied Statistics in Agriculture

The 30th annual conference on Applied Statistics in Agriculture was held May 6-8, 2018, in Manhattan Kansas.

Workshop and Keynote Address

Guilherme J. M. Rosa

Department of Animal Science
Department of Biostatistics & Medical Informatics
University of Wisconsin – Madison

Workshop: Introduction to Graphical Modeling for Agricultural Data

Keynote Address: Harnessing Operational Farm Data to Enhance Advancement of Agricultural Sciences

Session Presentations

	Pseudo likelihood or Quadrature? What We Thought We Knew, What We Think We Know, and What We Are Still Trying to Figure Out Walter Stroup - University of Nebraska-Lincoln Elizabeth A. Claassen - JMP
	Pseudolikelihood or Quadrature? What We Advise (for now) and Why Elizabeth Claassen - SAS Walter Stroup - University of Nebraska - Lincoln
	A Nonlinear Hierarchical Model for Forecasting Crop Growth in the US Corn Belt Colin Lewis-Beck, Petruta Caragea, Jarad Niemi, Brian Hornbuckle and Victoria Walker – Iowa State University
	Integration of Survey Data and Big Data to Improve Agricultural Statistics Zhengyuan Zhu – Iowa State University
	Use of classification and regression tree (CART) to predict motivators influencing dog owners’ intention to vaccinate against rabies in Ethiopia Tariku Jibat Beyene and Natalia Cernicchiaro – Kansas State University Crawford Revie – University of Prince Edward Island, Canada Samson Leta and Beakal Mindaye – Addis Ababa University, Ethiopia
	Producing County-Level Estimates Using All Available Data Linda J. Young – USDA National Agricultural Statistics Service
	Hierarchical Bayesian Structural Equation Modeling of Heterogeneous Relationships between Performance Outcomes in Animal Production Systems Kessinee Chitakasempornkul, Abigail Jager and Nora M. Bello – Kansas State University
	Aspects of Linear Mixed Models for Multinomial Responses with Observed Low Frequencies Perla E. Reyes – Kansas State University Oscar Perez-Hernandez – Northwest Missouri State University
	Pooling of variances: the skeleton in the mixed model closet? Philip M. Dixon – Iowa State University
	Teaching a New Dog an Old Trick: AMMI Analysis in Microbiome Data William J. Price, Janet E. Williams and Mark A. McGuire – University of Idaho Kimberly A. Lackey, Courtney L. Meehan and Michelle K. McGuire – Washington State University
	Application of mixed models to estimate the risk of emergence of antimicrobial resistance in gut bacteria in beef cattle administered with therapeutic antimicrobials Tariku Jibat Beyene, Leigh Ann Feuerbacher, T.G. Nagaraja and Natalia Cernicchiaro – Kansas State University
	Using Quantile Regression to Improve Feed Intake Curve Estimates in Finisher Pigs Caitlyn E. Bruns, Dani F. Wilson-Wells, and Tom A. Rathje – DNA Genetics
	Bias Correction of Bounded Location Errors in Binary Data Nelson B. Walker and Trevor Hefley – Kansas State University
	When and where: estimating the location and time of introduction for exotic pests and pathogens Trevor Hefley – Kansas State University
	Modeling abundance of multiple species using latent regression tree algorithms Haoyu Zhang and Trevor Hefley – Kansas State University Brian Gray and Kristen Bouska – USGS
	Comparing the growth patterns of monoculture and mixture of three plant species Jixiang Wu and Arvid Boe – South Dakota State University Kenneth Albrecht – University of Wisconsin-Madison
	Statistical Analysis Investigation on Vegetable Oils Stability during Deep Frying using Selected Quality Parameters Jamal I. Daoud, Mohamed E. S. Mirghani, Irwandi Jaswir – International Islamic University Malaysia A. A. Yasin – Algezura University Sudan

Poster Sessions

	Transformation of skewed flavonoid dietary intake data to a near-normal sample distribution: a comparison of Box-Cox transformation to Markov chain Monte Carlo predictive modeling: 2007-2010 NHANES data Theophile Murayi, Joseph D. Goldman, Rhonda S. Sebastian and Alanna J. Moshfegh – United States Department of Agriculture
	Aerial Survey & Classification of Invasive Bush Honeysuckle Trevor D. Witt, Andrea Meyer, Travis Balthazor and Kurt Carraway – Kansas State University Ryan Armbrust – Kansas Forest Service
	From One Environment to Many: The Problem of Reproducibility of Results in Agricultural Research Jinguang Lin, James J. Higgins and Michael J. Higgins – Kansas State University
	Application of Generalized Additive Models on Extreme Time-series Sensor Data in Horticulture Qianmei Wu, Walter Stroup and Ellen Paparozzi – University of Nebraska – Lincoln
	Cox Regression for Modeling Seed Quality Decay Over Time Jung Ae Lee and John C. Rupe – University of Arkansas, Fayetteville
	Determining climate factors associated with soybean production in South Dakota Tingting He, Jianli Qi and Jixiang Wu – South Dakota State University
	Introducing ggResidpanel: An R Package for Easy Visualization of Residuals Kathleen Rey and Katherine Goode – Iowa State University