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Convenience Sample of On-Farm Research Cooperators Representative of Wisconsin Farmers

Published online by Cambridge University Press:  20 January 2017

Edward C. Luschei*
Affiliation:
Department of Agronomy, University of Wisconsin, Madison WI 53706
Clarissa M. Hammond
Affiliation:
Department of Agronomy, University of Wisconsin, Madison WI 53706
Chris M. Boerboom
Affiliation:
Department of Agronomy, University of Wisconsin, Madison WI 53706
Pete J. Nowak
Affiliation:
Department of Rural Sociology, University of Wisconsin, Madison WI 53706
*
Corresponding author's E-mail: [email protected].

Abstract

Researchers interested in describing or understanding agroecological systems have many reasons to consider on-farm research. Yet, despite the inherent realism and pedagogical value of on-farm studies, recruiting cooperators can be difficult and this difficulty can result in so-called “convenience samples” containing a potentially large and unknown bias. There is often no formal justification for claiming that on-farm research results can be extrapolated to farms beyond those participating in the study. In some sufficiently well-understood research areas, models may be able to correct for potential bias; however, no theoretical argument is as persuasive as a direct comparison between a randomized and a convenience sample. In a 30-cooperator on-farm study investigating weed community dynamics across the state of Wisconsin, we distributed a written survey probing farmer weed management behaviors and attitudes. The survey contained 59 questions that overlapped a large, randomized survey of farmer corn pest management behavior. We compared 187 respondents from the larger survey with the 18 respondents from our on-farm study. For dichotomous response questions, we found no difference in response rate for 80% of the questions (α = 0.2, β > 0.5). Differences between the two groups were logically connected to the selection criteria used to recruit cooperators in the on-farm study. Similarly, comparisons of nondichotomous response questions did not differ for 80% of the questions (α = 0.05, β > 0.9). Exploratory multivariate analyses failed to reveal differences that might have been hidden from the marginal analyses. We argue that our findings support the notion that the convenience samples often associated with on-farm research may be representative of the more general class of farms, despite lack of bias protection provided by truly randomized designs.

Type
Education/Extension
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Arnett, B. and Rikli, R. 1981. Effect of method of subject selection (volunteer vs. random) and treatment variable on motor performance. Res. Q. Exerc. Sport 52:433440.CrossRefGoogle ScholarPubMed
Beck, M. W. 1997. Inference and generality in ecology: current problems and experimental solution. Oikos 78:265273.CrossRefGoogle Scholar
Drinkwater, L. E. 2002. Cropping systems research: reconsidering agricultural experimental approaches. HortTechnology 12:355361.CrossRefGoogle Scholar
Eberhardt, L. L. and Thomas, J. M. 1991. Designing environmental field studies. Ecol. Monogr 61:5373.CrossRefGoogle Scholar
Ghersa, C. M., Roush, M. L., Radosevich, S. R., and Cordray, S. M. 1994. Coevolution of agroecosystems and weed management. Bioscience 44:8594.CrossRefGoogle Scholar
Goodwin, B. K., Schurle, B. W., Norman, D. W., Freyenberger, S. G., Bloomquist, L. E., and Regher, D. L. 1997. Determinants of Kansas farmers' participation in on-farm research. J. Agric. Appl. Econ 29:385396.CrossRefGoogle Scholar
Hammond, C. M. 2005. Farmer Management Practices and Large Scale Weed Community Dynamics Across the Landscape of Wisconsin. . Madison, WI: University of Wisconsin. 143.Google Scholar
Hammond, C. M., Luschei, E. C., Boerboom, C. M., and Nowak, P. J. 2006. Adoption of integrated pest management tactics by Wisconsin farmers. Weed Technol 20:756767.CrossRefGoogle Scholar
Hultsch, D. F., MacDonald, S. W., Hunter, M. A., Maitland, S. B., and Dixon, R. A. 2002. Sampling and generalisability in developmental research: comparison of random and convenience samples of older adults. Int. J. Behav. Dev 26:345359.CrossRefGoogle Scholar
Hurlbert, S. H. 1984. Pseudoreplication and the design of ecological field experiments. Ecol. Monogr 54:187211.CrossRefGoogle Scholar
Jordan, N., Gunsolus, J., Becker, R., and White, S. 2002. Public scholarship—linking weed science with public work. Weed Sci 50:547554.CrossRefGoogle Scholar
Kolasa, J. and Rollo, C. D. 1991. Introduction: the heterogeneity of heterogeneity: a glossary. Pages 123. In Kolasa, J. and Pickett, S. T. A. Ecological Heterogeneity. New York: Springer-Verlag.CrossRefGoogle Scholar
Lynne, G. D., Shonkwiler, J. S., and Rola, L. R. 1988. Attitudes and farmer conservation behavior. Am. J. Agric. Econ 70:1219.CrossRefGoogle Scholar
Maxwell, B. D. and Luschei, E. C. 2004. Justification for site-specific weed management based on ecology and economics. Weed Sci 52:6975.Google Scholar
Nesselroade, J. R. 1986. Selection and generalization in investigations of interrelationships among variables. Some commentary on aging research. Educ. Gerontol 12:395402.CrossRefGoogle Scholar
Norman, D., Freyenberger, S., and Schurle, B. 1997. County extension agents and on-farm research work: results of a Kansas survey. J. Extension 35:18.Google Scholar
Norman, D. W., Bloomquist, L. E., Freyenberger, S. G., Regehr, D. L., Schurle, B. W., and Janke, R. R. 1998. Farmers attitudes concerning on-farm research: Kansas survey results. J. Nat. Resour. Life Sci. Educ 27:3541.CrossRefGoogle Scholar
Nowak, P. and Cabot, P. 2004. The human dimension of natural resource management programs. J. Soil Water Conserv 59:128135.Google Scholar
Pannell, D. J. and Zilberman, D. 2001. Economic and sociological factors affecting growers' decision making on herbicide resistance. Pages 251278. In Powles, S. B. and Shaner, D. L. Herbicide Resistance and World Grains. Boca Raton, FL: CRC.CrossRefGoogle Scholar
Peters, R. H. 1991. A Critique for Ecology. Cambridge, UK: Cambridge University Press. 366.Google Scholar
Python 2006. Python software. http://www.python.org/download/windows/. Accessed: October 18, 2006.Google Scholar
Riley, J. and Alexander, C. J. 1997. Statistical literature for participatory on-farm research. Exp. Agric 33:7382.CrossRefGoogle Scholar
Rzewnicki, P. E., Thompson, R., Lesoing, G. W., Elmore, R. W., Francis, C. A., Parkhurst, A. M., and Moomaw, R. S. 1988. On-farm experiment designs and implications for locating research sites. Am. J. Altern. Agric 3:168173.CrossRefGoogle Scholar
SAS. Statistical Analysis Systems 2003. SAS Procedures Guide. Version 9.1. Cary, NC: SAS Institute.Google Scholar
Sassenrath, G. F., Heilman, , Luschei, E., Bennett, G. L., Fitzgerald, G., Klesius, P., Tracy, W., Williford, J. R., and Zimba, P. 2008. Technology, complexity and change in agricultural production systems. Renewable Agric. Food Syst 23:111.CrossRefGoogle Scholar
Two-by-Two 2006. Two-by-Two software. http://www.med.uio.no/imb/stat/two-by-two/installation.html. Accessed: October 18, 2006.Google Scholar
Warner, K. D. 2006. Extending agroecology: grower participation in partnerships is key to social learning. Renewable Agric. Food Syst 21:8494.CrossRefGoogle Scholar
Wiens, J. A. 2000. Ecological heterogeneity: an ontogeny of concepts and approaches. Pages 932. In Hutchings, M. J., John, E. A., and Stewart, A. J. A. The Ecological Consequences of Environmental Heterogeneity. Oxford, UK: Blackwell Science.Google Scholar
Wilson, D. R. and Martinez, T. R. 1997. Improved heterogeneous distance functions. J. Artif. Intell. Res 6:134.CrossRefGoogle Scholar
Wolfram Research 2005. Mathematica. Version 5.2. Champaign, IL: Wolfram Research.Google Scholar
Wuest, S. B., McCool, D. K., Miller, B. C., and Veseth, R. J. 1999. Development of more effective conservation farming systems through participatory on-farm research. Am. J. Altern. Agr 14:98102.CrossRefGoogle Scholar