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Department of Statistics

2018 Conference on Applied Statistics in Agriculture

Group Photo Outside

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

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Workshop and Keynote Address

Guilherme RosaGuilherme 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

Walter StroupPseudo 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 
Elizabeth ClaassenPseudolikelihood or Quadrature? What We Advise (for now) and Why

Elizabeth Claassen - SAS
Walter Stroup - University of Nebraska - Lincoln
Colin Lewis-BeckA 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
Zhengyuan ZhuIntegration of Survey Data and Big Data to Improve Agricultural Statistics

Zhengyuan Zhu – Iowa State University
Tariku Jibat BeyeneUse 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
Linda YoungProducing County-Level Estimates Using All Available Data

Linda J. Young – USDA National Agricultural Statistics Service
Kessinee ChitakasempornkulHierarchical 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
Perla ReyesAspects of Linear Mixed Models for Multinomial Responses with Observed Low Frequencies

Perla E. Reyes – Kansas State University
Oscar Perez-Hernandez – Northwest Missouri State University
Philip DixonPooling of variances: the skeleton in the mixed model closet?

Philip M. Dixon – Iowa State University
William J PriceTeaching 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
Tariku Jibat BeyeneApplication 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
Dani Wilson-WellsUsing Quantile Regression to Improve Feed Intake Curve Estimates in Finisher Pigs

Caitlyn E. Bruns, Dani F. Wilson-Wells, and Tom A. Rathje – DNA Genetics
Nelson WalkerBias Correction of Bounded Location Errors in Binary Data

Nelson B. Walker and Trevor Hefley – Kansas State University
Trevor HefleyWhen and where: estimating the location and time of introduction for exotic pests and pathogens

Trevor Hefley – Kansas State University
Haoyu ZhangModeling abundance of multiple species using latent regression tree algorithms

Haoyu Zhang and Trevor Hefley – Kansas State University
Brian Gray and Kristen Bouska – USGS
Jixiang WuComparing 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
Jamal DaoudStatistical 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

Theophile MurayiTransformation 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
Trevor WittAerial Survey & Classification of Invasive Bush Honeysuckle

Trevor D. Witt, Andrea Meyer, Travis Balthazor and Kurt Carraway – Kansas State University
Ryan Armbrust – Kansas Forest Service
Jinguang LinFrom 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
Qianmei WuApplication of Generalized Additive Models on Extreme Time-series Sensor Data in Horticulture

Qianmei Wu, Walter Stroup and Ellen Paparozzi – University of Nebraska – Lincoln
Jung Ae LeeCox Regression for Modeling Seed Quality Decay Over Time

Jung Ae Lee and John C. Rupe – University of Arkansas, Fayetteville
Tingting HeDetermining climate factors associated with soybean production in South Dakota

Tingting He, Jianli Qi and Jixiang Wu – South Dakota State University
Kathleen ReyKatherine GoodeIntroducing ggResidpanel: An R Package for Easy Visualization of Residuals

Kathleen Rey and Katherine Goode – Iowa State University