95-3 Statistical Perspectives On a Large On-Farm Weed Management Study.



Monday, October 17, 2011: 2:00 PM
Henry Gonzalez Convention Center, Room 006B, River Level

Philip Dixon, Department of Statistics, Iowa State University, Ames, IA, Richard Cole, Monsanto, St Louis, IL, David Jordan, North Carolina State University-Crop Science Dept., Raleigh, NC, Micheal Owen, Department of Agronomy, Iowa State University, Ames, IA, David Shaw, Mississippi State University, Starkville, MS, Stephen Weller, Purdue University, West Lafeyette, IN, Robert Wilson, Panhandle Research & Extension Center, UNL, Scottsbluff, NE and Bryan Young, Plant Soil & General Agr, Southern Illinois University, Carbondale, IL
Complex experiments can be analyzed in many different ways. Some choices are important; others are less so.  The Benchmark study is a large (6 state, 150 farm, 5 year) on-farm comparison of two weed management strategies.  Farms are grouped into 7 combinations of crop (corn, soybean, or cotton) and rotation scheme (continuous, rotation with glyphosate resistant crops in both phases, rotation with alternating glyphosate resistant and non-resistant crops).  On each farm, a field is divided in half.  Weed management follows University recommended best management practices on one half and grower’s choice on the other. I will use this study to illustrate four options for data analysis and evaluate the sensitivity of the results to the choice.  I will discuss choosing a modeling framework for weed count data (linear mixed model or a generalized linear mixed model), choosing how to handle overdispersion, choosing a model to assess sustainability, and choosing a correlation models for temporal and spatial data.
See more from this Division: C03 Crop Ecology, Management & Quality
See more from this Session: Symposium--Moving Beyond the RCBD: Funding, Management, and Analysis of Nontraditional Research Designs