Abstract
Traps baited with semiochemicals are often used to investigate the chemical ecology of scolytids and associated insects. One statistical problem frequently encountered in these studies are treatments that catch no insects and, thus, have zero mean and variance, such as blank or control traps. A second problem is the use of multiple comparison procedures that do not control the experimentwise error rate. We conducted a literature survey to determine the frequency of these two statistical problems in Journal of Chemical Ecology for 1990–2002. Simulations were then used to examine the effects of these problems on the validity of multiple comparison procedures. Our results indicate that both statistical problems are common in the literature, and when combined can significantly inflate both the experimentwise and per comparison error rate for multiple comparison procedures. A possible solution to this problem is presented that involves confidence intervals for the treatment means. Options to increase the statistical power of trapping studies are also discussed.
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REFERENCES
Borden, J. H. 1982. Aggregation pheromones, pp. 74-139, in J. B. Mitton and K. B. Sturgeon (eds.). Bark Beetles in North American Conifers: A System for the Study of Evolutionary Biology. University of Texas Press, Austin, TX.
Borden, J. H. 1997. Disruption of semiochemical-mediated aggregation in bark beetles, pp. 421-438, in R. T. Carde and A. K. Minks (eds.). Insect Pheromone Research, New Directions. Kluwer Academic, Boston, MA.
Carmer, S.G. and Swanson, M. R. 1973. An evaluation of ten pairwise multiple comparison procedures by Monte Carlo methods. J. Am. Stat. Assoc. 68:66-74.
Carmer, S.G. and Walker, W. M. 1982. Baby bear's dilemma: A statistical tale. Agron. J. 74:122-124.
Cohen, J. 1988. Statistical Power Analysis for the Behavioral Sciences. Erlbaum, Mahwah, NJ.
Day, R.W. and Quinn, G. P. 1989. Comparisons of treatments after an analysis of variance in ecology. Ecol. Monogr. 59:433-463.
Hayter, A. J. 1986. The maximum familywise error rate of Fisher's least significant difference test. J. Am. Stat. Assoc. 81:1000-1004.
Herms, D.A., Haack, R. A., and Ayres, B. D. 1991. Variation in semiochemical-mediated prey-predator interaction: Ips pini (Scolytidae) and Thanasimus dubius (Cleridae). J. Chem. Ecol. 17:1705-1714.
Hsu, J. C. 1996. Multiple Comparisons: Theory and Methods. Chapman & Hall/CRC, Boca Raton, Florida.
Littell, R.C., Milliken, G. A., Stroup, W.W., and Wolfinger, R. D. 1996. SAS System for Mixed Models. SAS Institute, Cary, NC.
McCulloch, C.E. and Searle, S. R. 2001. Generalized, Linear, and Mixed Models. Wiley, New York, NY.
Miller, D.R., Gibson, K.E., Raffa, K.F., Seybold, S.J., Teale, S. A., and Wood, D. L. 1997. Geographic variation in response of pine engraver, Ips pini, and associated species to pheromone, lanierone. J. Chem. Ecol. 23:2013-2031.
Raffa, K. F. 2001. Mixed messages across multiple trophic levels: The ecology of bark beetle chemical communication systems. Chemoecology 11:49-65.
Rothman, K. J. 1990. No adjustments are needed for multiple comparisons. Epidemiology 1:43-46.
SAS Institute INC. 2001. The SAS System for Windows, Version 8. SAS Institute, Cary, NC.
Saville, D. J. 1990. Multiple comparison procedures: The practical solution. Am. Stat. 44:174-180.
Smith, M.T., Salom, S.M., and Payne, T. L. 1993. The Southern Pine Bark Beetle Guild: An Historical Review of the Research on the Semiochemical-Based Communication System of the Five Principle Species. Virginia Polytechnic Institute and State University, Blacksburg, VA.
Sokal, R.R. and Rohlf, F. J. 1995. Biometry: The Principles and Practices of Statistics in Biological Research. W. H. Freeman, New York, NY.
Stewart-Oaten, A. 1995. Rules and judgements in statistics: Three examples. Ecology 76:2001-2009.
The R Core Development Team. 2003. R 1.7.0—A Language and Environment. http://www.r-project.org/
Toothaker, L. E. 1993. Multiple comparison procedures. Sage, Newbury Park, CA.
Westfall, P. H., Tobias, R.D., Rom, D., Wolfinger, R. D., and Hochberg, Y. 1999. Multiple Comparisons and Multiple Tests Using the SAS System. SAS Institute, Cary, NC.
Wood, D. L. 1982. The role of pheromones, kairomones, and allomones in the host selection and colonization behavior of bark beetles. Ann. Rev. Entomol. 27:411-446.
Zhou, J., Ross, D.W.,and Niwa, C. G. 2001. Kairomonal response of Thanasimus undatulus, Enoclerus sphegeus (Coleoptera: Cleridae), and Temnochila chlorodia (Coleoptera: Trogositidae) to bark beetle semiochemicals in Eastern Oregon. Environ. Entomol. 30:993-998.
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Reeve, J.D., Strom, B.L. Statistical Problems Encountered in Trapping Studies of Scolytids and Associated Insects. J Chem Ecol 30, 1575–1590 (2004). https://doi.org/10.1023/B:JOEC.0000042069.17533.3c
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DOI: https://doi.org/10.1023/B:JOEC.0000042069.17533.3c