NCCC_old170: Research Advances in Agricultural Statistics
(Multistate Research Coordinating Committee and Information Exchange Group)
Status: Inactive/Terminating
NCCC_old170: Research Advances in Agricultural Statistics
Duration: 10/01/2011 to 09/30/2016
Administrative Advisor(s):
NIFA Reps:
Non-Technical Summary
Statement of Issues and Justification
Statisticians who consult and do research in an Agricultural Experiment Station environment have a unique relationship with the University. Their multi-disciplinary, collaborative role is generally more extensive than that of other faculty within the University and often cuts across several departments or units. Collaboration of statisticians and scientists allows land grant institutions to perform their agricultural research missions more effectively and efficiently than would otherwise be possible. Statisticians at each station tend to specialize in specific areas. This multi-state committee provides a mechanism that brings together statisticians from many stations working in related areas. The resulting exchange of ideas and the sharing of knowledge is of benefit to all project members and to the institutions they represent.
As State and Federal appropriations continue to fall short of levels needed for research and grants become more competitive, it becomes even more imperative that research dollars go as far as possible. This requires Experiment Station statisticians to keep abreast of the latest statistical research as well as to work to develop methodology appropriate to their consulting roles. Advances in the complexity of designed experiments and observational studies along with a broader range of qualitative and quantitative types of data being collected in increasingly larger quantities require new methodologies for proper design and analysis to insure the quality of the data and the inferences drawn from them.
Never has the charge to remain current in the statistical profession been more challenging. Assessing the utility of the new statistical methods, many of which are computationally intensive, and the associated software is increasingly important. Further, dissemination of the information to agricultural researchers must be made in a timely manner. Thus, it is critical that Station statisticians work cooperatively to determine the best current approaches to common statistical problems and to help guide future directions of statistical research and software development.
In this respect, Experiment Station statisticians and their counterparts in government and industry can work together to provide more effective assistance to the agricultural researchers of their respective states. This NCCC committee can play an extremely important role by serving as a focal point for the development and implementation of sound statistical practice, thereby improving the quality of research in the agricultural sciences. Thus this committee is a support project that ultimately assists agricultural researchers in other disciplines in their efforts to accomplish national research priorities. The members of this NCCC are committed to this goal.
Objectives
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To identify, foster and coordinate cooperative research efforts in statistics among statisticians serving food and agriculture research programs
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To address the statistical design and analysis issues associated with studies involving technologies that typically produce a large number of spatially and/or temporally correlated observations per sample but few samples (e.g., gene and protein arrays, metabolomics, mass spectroscopy, chromatography and precision agriculture)
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To address concerns associated with the development and implementation of generalized linear mixed model techniques and software used by statisticians and researchers
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To address meta-analysis issues associated with multi-location, multi-investigator projects including those in which study treatments and/or designs may differ by location
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To facilitate the rapid transfer of new statistical methodologies and developments to statisticians and researchers in Experiment Stations, USDA, and industry, with emphasis on outreach and collaboration
Procedures and Activities
Since its inception, NCCC-170 has addressed a series of statistical topics using the following general procedure. At each annual meeting, the members discuss current research projects at their university or research station and the statistical issues associated with them. These topics are compiled and when appropriate, the members use this information to decide on a statistical topic to be addressed by the group in the next project cycle. Once that decision has been made, a three or four year cycle begins.
The first and, if necessary, second year of the cycle are devoted to educating the project membership on the chosen topic. This is accomplished primarily through the annual meeting technical programs presented by knowledgeable project members and, on occasion, non-members (usually located at that year's meeting site). Once this phase has been completed, materials are developed for members to use in their research, education and outreach activities. These may include workshop materials for subject matter audiences, software and usage instructions for data analysis, and statistical material for members own continuing education. Material development is carried out by a subcommittee of volunteers from the project membership. A draft of their work (e.g., a dry-run of a workshop) is presented at the next annual meeting to obtain feedback from the entire group. During this meeting, a decision is made regarding whether or not a final version needs to be presented the following year.
Over the past nineteen years, project members have dealt with statistical aspects of on-farm trials, mixed models, spatial statistics, and generalized linear mixed models. They have developed mixed model workshops for both statistical and subject matter audiences and a spatial workshop for subject matter audiences. These workshops have been successful and continue to be updated and offered even after the project focus has moved to a new topic. A generalized linear mixed model workshop was offered for the first time at the American Society of Agronomy annual meeting in 2010.
In addition to these group outputs, these discussions have also impacted project members' collaborations at their own institutions and have led to numerous refereed and non-refereed publications, participation in competitive grants and presentations at professional meetings. The Literature section lists publications from the project's 2010 Annual Report as examples of these individual outputs.
The initial years of this project renewal will focus on the continuation of generalized linear mixed model problems with an emphasis on computing issues and the analysis of data sets with high dimensional observations coupled with both small and large sample sizes. Meta-analysis issues for multi-location, multi-investigator studies will be a new focus.
Expected Outcomes and Impacts
- Education of members leading to cooperative research efforts and improved consulting and teaching by individual members.
- Cooperative research efforts among some members and information exchange on new developments among all members in the areas of spatial statistics, generalized linear mixed models, and the analysis of high dimensional, large volume data.
- Continued offering of workshops to educate subject matter scientists on valid design and statistical analysis of studies involving spatial statistics, linear mixed models, and generalized linear mixed models.
Projected Participation
View Appendix E: ParticipationEducational Plan
Members will educate their individual clientele of subject matter scientists and students in one-on-one and group settings as they deem appropriate. Workshops will continue to be offered to regional and national subject matter groups.
Organization/Governance
The Chair and Secretary are elected by the members present at the annual meeting. The meeting Local Arrangement Chair for the next year is the member from the state in which the meeting will be held. The meeting Program Chair for the next year is a volunteer from among the members present at the annual meeting.
Literature Cited
Aston K.I., Li G.P., Hicks B.A., Sessions B.R., Davis A.P., Rickords L.F., Stevens J.R.,and White K.L. (2010). Abnormal levels of transcript abundance of developmentally important genes in various stages of preimplantation bovine somatic cell nuclear transfer embryos. Cellular Reprogramming 2(1):23-32.
Bathke, A. C., O. Schabenberger, R.D. Tobias and L.V. Madden (2009). Greenhouse-Geisser adjustment and the ANOVA-type statistic: Cousins or twins? The American Statistician 63: 239-246.
Bello, N.M., J.P. Steibel and R.J. Tempelman (2010). A hierarchical Bayesian approach to mixed effects modeling of random and residual variance-covariance matrices in bivariate mixed effects models. Biometrical Journal 52: 297-313.
Burris, E., D. Burns, K.S. McCarter, C. Overstreet and M. Wolcott (2010). Evaluation of the effects of Telone II (fumigation) on nitrogen management and yield in Louisiana delta cotton. Precision Agriculture 11: 239-257.
Caesar, TC, S.E. Wright, U.M. Sainju, R.L. Kolberg and M.S. West (2010). Impacts of long-term no-tillage and conventional tillage management of spring wheat-lentil cropping systems in dryland Eastern Montana, USA, on fungi associated to soil aggregation. World Congress of Soil Science.
Dominigue MJ, Kramer M, Feldlaufer MF (2010). Sexual dimorphism of arrestment and gregariousness in the bed bug (Cimex lectularius) in response to cuticular extracts from nymphal exuviae. Physiological Entomology. DOI: 10.1111/j.1365-3032.2010.00738.x
Ehlenfeldt MK, Polashock JJ, Stretch AW, Kramer M (2010). Mummy berry fruit rot and shoot blight incidence in blueberry: prediction, ranking, and stability in a long-term study. HortScience 45(1): 9297.
Fleming-Waddell JN, Olbricht GR, Taxis TM, White JD, Vuocolo T, Craig BA, Tellam RL, Neary MK, Cockett NE, and Bidwell CA (2009). Effect of DLK1 and RTL1 but not MEG3 or MEG8 on muscle gene expression in callipyge lambs. Plos ONE 4(10), e7399.
Gilbert-Norton L., Wilson R., Stevens J.R. and Beard K.H. (2010). A meta-analytic review of corridor effectiveness. Conservation Biology 24(3):660-668.
Kramer M, Weldon PJ and Carroll JF (2009). Canonical discriminant analysis for constructing composite scores for concurrently measured behaviours. Animal Behaviour 77: 763-768.
Kramer M, Feldlaufer MF and Chauhan KR (2010). Mosquito biting behavior: Statistical power and sources of variation in toxicity and repellent bioassays. Journal of Medical Entomology 47: 199-204.
Madden, L.V. and P.A. Paul (2009). Assessing heterogeneity in the relationship between wheat yield and Fusarium head blight intensity using random-coefficient mixed models. Phytopathology 99: 850-860.
McDonald, M., K.R. Brye, D.M. Miller and E.E. Gbur (2009). Broiler litter application history and soil depth effects on arsenic adsorption in soil. Soil Science 174: 661-675.
Milliken, G., J. Willers, K. McCarter and J. Jenkins (2009). Designing experiments to evaluate the effectiveness of precision agricultural practices on research fields: Part 1 Concepts for their formulation. Operational Research, Business and Economics, 1109-2858 (Print) 1866-1505 (Online).
Singer, J., K. Kohler, K, Moore and D. Meek (2009). Living mulch forage yield and botanical composition in a corn-soybean-forage rotation. Agronomy Journal 101:1249-1257.
Young, L.J., C.A. Gotway and K.K. Lopiano (2010). Challenges associated with integrating data from multiple scales to assess relationships. Proceedings of the 9th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Leicester, UK.