Thursday, June 5, 2025
8:00 AM
Registration, check-in, coffee
8:50 AM
Welcome to NCCC170 2025
Julia Piaskowski, Director of Statistical Programs, College of Agricultural and Life Sciences, University of Idaho, Moscow, ID
9:00 AM
Introductions to University of Idaho Agricultural Experiment Station
Matt Powell, Interim Associate Dean of Research & Director of Idaho Agricultural Experiment Station, University of Idaho, Moscow, ID
9:10 AM
Improving interpretability in machine learning using confidence intervals in ALE plots
John Stevens, Department of Math and Statistics Utah State University, Logan, UT
Matthew Lister, Utah State University and Space Dynamics Laboratory, Logan, UT,
Machine learning models that predict a response based on a collection of predictor variables usually do not provide simple numeric summaries of predictor effects and so are often referred to as black box models.
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9:40 AM
Goodhardt’s law and plant breeding. Is cross-validation misleading about the success of genomic prediction?
Daniel E. Runcie, Department of Plant Sciences, University of California – Davis, Davis, CA
Goodhart’s law says that “when a measure becomes a target, it ceases to be a good measure.” Plant breeding aims to increase the genetic value of varieties, and the Breeder’s Equation states that the rate of gain is proportional to the accuracy of selection.
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10:10 AM
Using an extension of fragmentary data analysis methods to predict sex from fragments of bones
Philip Dixon, Department of Statistics, Iowa State University, Ames, IA
Mallory Levens, Department of World Languages and Cultures, Iowa State University, Ames, IA
Andrew Somerville. Department of World Languages and Cultures, Iowa State University, Ames, IA
This project started when an Anthropology student in my methods class asked me to be on her advisory committee. She had bone measurements from individuals recovered in an archeological dig and needed to predict each individual’s sex.
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10:40 AM
11:00 AM
Leveraging TAPS extension efforts for research purposes – opportunities, and challenges
Josefina Lacasa, Department of Statistics, Kansas State University, Manhattan, KS
Daran Rudnick, Department of Biological and Agricultural Engineering, Kansas State University, Manhattan, KS
The “Testing Ag Performance Solutions” (TAPS) program is an ongoing nationwide initiative aiming to connect producers, researchers, extensionists, faculty, and industry partners through a farm management competition for testing and demonstrating efficient input management practices.
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11:30 AM
Comparing the effects of sewage sludge ash and other recycled phosphorus fertilizers on soil quality; a two-way design plus control with several repeated measures
Aaron Rendahl, Department of Veterinary and Biomedical Sciences, University of Minnesota, Minneapolis, MN
In this study, I worked with researchers who were studying options for recycled phosphorus fertilizers, with particular interest in sewage sludge ash from the St. Paul Wastewater Treatment Plant. This ash contains significant amounts of phosphorus, which is essential to healthy plant development and is regularly applied in agronomic settings to ensure maximum crop yields.
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12:00 PM
1:30 PM
Mixed random forest-based GWAS and a forward-in-time simulation study
Alexander E. Lipka, Department of Crop Sciences, University of Illinois at Urbana-Champaign, Champaign, IL
I run a statistical genetics lab at UIUC. My lab seeks to explore how statistical genetics can be optimized to gain a better understanding on the genetic architecture of traits. This could lead to even more efficient applications of genomic prediction to crop breeding programs.
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2:00 PM
Best practices for GLMMs with zero-inflation – unique challenges for repeated-measures data and fitting covariates in binary process
Conor G. Fair, College of Agricultural and Environmental Sciences, University of Georgia, Griffin, GA
Julia Piaskowski, Director of Statistical Programs, College of Agricultural and Life Sciences University of Idaho, Moscow, ID
Raúl Macchiavelli, College of Agricultural Sciences, University of Puerto Rico, Mayagüez, PR
Josefina Lacasa, Department of Statistics, Kansas State University, Manhattan, KS
Bruce A. Craig, Department of Statistics, Purdue University, West Lafayette, IN
Walter W. Stroup, Department of Statistics, University of Nebraska-Lincoln, Lincoln, NE
The GLMM working group continues its efforts to compare the implementation of zero-inflation models across SAS and R software platforms with the analysis of this data set where the counts of beneficial insects were measured weekly from sugar beet plots exposed to different insecticidal treatments following a randomized complete block design.
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2:30 PM
GLMM working group updates and plans to move forward
Nora M. Bello, United States Department of Agriculture – Agricultural Research Service, Beltsville, MD
Walter W. Stroup, Department of Statistics, University of Nebraska-Lincoln, Lincoln, NE
Julia Piaskowski, Director of Statistical Programs, College of Agricultural and Life Sciences University of Idaho, Moscow, ID
Josefina Lacasa, Department of Statistics Kansas State University, Manhattan, KS
Reka Howard, Department of Statistics, University of Nebraska-Lincoln, Lincoln, NE
Daniel G. Palmer, StatsCraft, Spokane, WA
Quentin D. Read, United States Department of Agriculture – Agricultural Research Service, Beltsville, MD
Susan L. Durham, Department of Watershed Sciences and Ecology Center, Utah State University, Logan, UT
Conor G. Fair, College of Agricultural and Environmental Sciences, University of Georgia, Griffin, GA
Clark Kogan, Department of Pharmaceutical Sciences, Washington State University, Spokane, WA
Raúl E. Macchiavelli, College of Agricultural Sciences, University of Puerto Rico, Mayagüez, PR
Bruce A. Craig, Department of Statistics, Purdue University, West Lafayette, IN
Outline: Ongoing work on Best Practices for GLMM Implementation
Objectives of the Session I. Articulate any remaining technical aspects of examples presented at CASANR II. Discuss group’s approach to move advanced examples III.
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5:00 PM
Friday, June 6, 2025
9:00 AM
Residuals and diagnostics for multinomial regression models
Bruce A. Craig, Department of Statistics, Purdue University, West Lafayette, IN
Eric A.E. Gerber, Khoury College of Computer Science, Northeastern University, Evanston, IL
Multinomial logistic and other similar regression models have been used to describe multinomial data in applications ranging from modeling the human microbiome to modeling outcomes in sports. Though much work has been done on model diagnostics for discrete, binary, and ordinal outcomes, model diagnostics for multinomial regression models are limited.
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9:30 AM
9:50 AM
NCCC170 Business meeting
Announcements:
Thank you to our local host Julia Piaskowski and program chair Conor Fair Welcome to new NCCC170 members: Daniel Palmer (StatCraft), Heike Hofmann (UNL) NCCC170 website
https://nccc170.org has links including member profiles: check it out!
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12:00 PM
2:00 PM
Tour the Deep Soil Ecotron (the only one in the entire United States!)