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References

Published online by Cambridge University Press:  13 November 2009

C. Patrick Doncaster  and
Andrew J. H. Davey
C. Patrick Doncaster
Affiliation:
University of Southampton
Andrew J. H. Davey
Affiliation:
UK Water Research Centre (WRc)
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Type
Chapter
Information
Analysis of Variance and Covariance
How to Choose and Construct Models for the Life Sciences
 , pp. 281 - 283
Publisher: Cambridge University Press
Print publication year: 2007

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References

Allison, D. B., Allison, R. L., Faith, M. S., Paultre, F. and Pi-Sunyer, F. X. (1997) Power and money: designing statistically powerful studies while minimizing financial costs. Psychological Methods, 2, 20–33.CrossRefGoogle Scholar
Beck, M. W. (1997) Inference and generality in ecology: Current problems and an experimental solution. Oikos, 78, 265–73.CrossRefGoogle Scholar
Carey, J. M. and Keough, M. J. (2002) The variability of estimates of variance, and its effect on power analysis in monitoring design. Environmental Monitoring and Assessment, 74, 225–41.CrossRefGoogle ScholarPubMed
Cohen, J. (1988) Statistical Power Analysis for the Behavioral Sciences, Second Edition. New Jersey: Lawrence Erlbaum.Google Scholar
Cohen, J. (1992) Quantitative methods in psychology: a power primer. Psychological Bulletin, 112, 155–9.CrossRefGoogle Scholar
Colegrave, N. and Ruxton, G. D. (2003) Confidence intervals are a more useful complement to nonsignificant tests than are power calculations. Behavioral Ecology, 14, 446–450.CrossRefGoogle Scholar
Crawley, M. J. (2002) Statistical Computing. An Introduction to Data Analysis using S-Plus. Chichester: Wiley.Google Scholar
Darlington, R. B. and Smulders, T. V. (2001) Problems with residual analysis. Animal Behaviour, 62, 599–602.CrossRefGoogle Scholar
Davey, A. J. H. (2003) Competitive interactions in stream fish communities. Ph.D. thesis, University of Southampton, Southampton.Google Scholar
Day, R. W. and Quinn, G. P. (1989) Comparisons of treatments after an analysis of variance in ecology. Ecological Monographs, 59, 433–63.CrossRefGoogle Scholar
Dayton, P. K. (1998) Reversal of the burden of proof in fisheries management. Science, 279, 821–2.CrossRefGoogle Scholar
Di Stefano, J. (2003) How much power is enough? Against the development of an arbitrary convention for statistical power calculations. Functional Ecology, 17, 707–9.CrossRefGoogle Scholar
Dytham, C. (1999, 2003) Choosing and Using Statistics: A Biologist's Guide. Oxford: Blackwell.Google Scholar
Field, S. A., Tyre, A. J., Jonzén, N., Rhodes, J. R. and Possingham, H. P. (2004) Minimizing the cost of environmental management decisions by optimizing statistical thresholds. Ecology Letters, 7, 669–75.CrossRefGoogle Scholar
Freckleton, R. P. (2002) On the misuse of residuals in ecology: regression of residuals vs. multiple regression. Journal of Animal Ecology, 71, 542–5.CrossRefGoogle Scholar
García-Berthou, E. (2001) On the misuse of residuals in ecology: testing regression residuals vs. the analysis of covariance. Journal of Animal Ecology, 70, 708–11.CrossRefGoogle Scholar
Grafen, A. and Hails, R. (2002) Modern Statistics for the Life Sciences. Oxford: Oxford University Press.Google Scholar
Graham, M. H. and Edwards, M. S. (2001) Statistical significance versus fit: estimating the importance of individual factors in ecological analysis of variance. Oikos, 93, 505–13.CrossRefGoogle Scholar
Greenwood, J. J. D. (1993) Statistical power. Animal Behaviour, 46, 1011.CrossRefGoogle Scholar
Hines, W. G. S. (1996) Pragmatics of pooling in ANOVA tables. The American Statistician, 50, 127–39.Google Scholar
Hoenig, J. M. and Heisey, D. M. (2001) The abuse of power: the pervasive fallacy of power calculations for data analysis. American Statistician, 55, 19–24.CrossRefGoogle Scholar
Hurlbert, S. H. (1984) Pseudoreplication and the design of ecological field experiments. Ecological Monographs, 54, 187–211.CrossRefGoogle Scholar
Ioannidis, J. P. A. (2005) Why most published research findings are false. Public Library of Science Medicine, 2, 696–701.Google ScholarPubMed
Janky, D. G. (2000) Sometimes pooling for analysis of variance hypothesis tests: a review and study of a split-plot model. The American Statistician, 54, 269–79.Google Scholar
Jennions, M. D. and Møller, A. P. (2003) A survey of the statistical power of research in behavioral ecology and animal behavior. Behavioral Ecology, 14, 438–45.CrossRefGoogle Scholar
Kent, A., Hawkins, S. J. and Doncaster, C. P. (2003) Population consequences of mutual attraction between settling and adult barnacles. Journal of Animal Ecology, 72, 941–52.CrossRefGoogle Scholar
Keough, M. J. and Mapstone, B. D. (1997) Designing environmental monitoring for pulp mills in Australia. Water Science and Technology, 35, 397–404.CrossRefGoogle Scholar
Keppel, G. and Wickens, T. D. (1973, 1982, 1991, 2004) Design and Analysis: A Researcher's Handbook. New Jersey: Prentice-Hall.Google Scholar
Kirk, R. E. (1968, 1982, 1994) Experimental Design: Procedures for the Behavioural Sciences. Belmont CA: Wadsworth.Google Scholar
Lenth, R. V. (2001) Some practical guidelines for effective sample size determination. American Statistician, 55, 187–93.CrossRefGoogle Scholar
Mapstone, B. D. (1995) Scalable decision rules for environmental impact studies: effect size, Type I and Type II errors. Ecological Applications, 5, 401–10.CrossRefGoogle Scholar
McClelland, G. H. (1997) Optimal design in psychological research. Psychological Methods, 2, 3–19.CrossRefGoogle Scholar
McKillup, S. 2006. Statistics Explained. An Introductory Guide for Life Scientists. Cambridge: Cambridge University Press.Google Scholar
Moran, M. D. (2003) Arguments for rejecting the sequential Bonferroni in ecological studiesOikos, 100, 403–5.CrossRefGoogle Scholar
Motulsky, H. and Christopoulos, A. (2004) Fitting Models to Biological Data Using Linear and Nonlinear Regression. Oxford: Oxford University Press.Google Scholar
Newman, J. A., Bergelson, J. and Grafen, A. (1997) Blocking factors and hypothesis tests in ecology: is your statistics text wrong?Ecology, 78, 1312–20.CrossRefGoogle Scholar
Peterman, R. M. (1990) Statistical power analysis can improve fisheries research and management. Canadian Journal of Fisheries and Aquatic Sciences, 47, 2–15.CrossRefGoogle Scholar
Quinn, G. P. and Keough, M. J. (2002) Experimental Design and Data Analysis for Biologists. Cambridge: Cambridge University Press, UK.CrossRefGoogle Scholar
Ratkowski, D. A., Evans, M. A. and Alldredge, J. R. (1993) Cross-over Experiments. Design, Analysis and Application. Statistics Textbooks and Monographs. New York: Marcel Dekker.Google Scholar
Resetarits, W. J. Jr. and Bernardo, J. (eds.) (1998) Experimental Ecology: Issues and Perspectives. Oxford: Oxford University Press.Google Scholar
Ruxton, G. D. and Colegrave, N. (2003) Experimental Design for the Life Sciences. Oxford: Oxford University Press.Google Scholar
Schultz, E. F. (1955) Rules of thumb for determining expectations of mean squares in analysis of variance. Biometrics, 11, 123–35.CrossRefGoogle Scholar
Searle, S. R. (1971, 1997) Linear Models. New York: John Wiley.Google Scholar
Searle, S. R., Casella, G. and McCulloch, C. E. (1992) Variance Components. New York: John Wiley & Sons.CrossRefGoogle Scholar
Shaw, R. G. and Mitchell-Olds, T. (1993) ANOVA for unbalanced data: an overview. Ecology, 74, 1638–45.CrossRefGoogle Scholar
Sokal, R. R. and Rohlf, F. J. (1969, 1981, 1995) Biometry. New York: Freeman and Co.Google Scholar
Tagg, N., Innes, D. J. and Doncaster, C. P (2005). Outcomes of reciprocal invasions between genetically diverse and genetically uniform populations of Daphnia obtusa (Kurz). Oecologia, 143, 527–36.CrossRefGoogle Scholar
Thomas, L. and Juanes, F. (1996) The importance of statistical power analysis: an example from animal behaviour. Animal Behaviour, 52, 856–9.CrossRefGoogle Scholar
Underwood, A. J. (1994) On beyond BACI: sampling designs that might reliably detect environmental disturbance. Ecological Applications, 4, 3–15.CrossRefGoogle Scholar
Underwood, A. J. (1997) Experiments in Ecology: Their Logical Design and Interpretation Using Analysis of Variance. Cambridge: Cambridge University Press.Google Scholar
Winer, B. J., Brown, D. R. and Michels, K. M. (1962, 1971, 1991) Statistical Principles in Experimental Design. New York: McGraw-Hill.CrossRefGoogle Scholar
Zar, J. H. (1974, 1984, 1996, 1998) Biostatistical Analysis. New Jersey: Prentice Hall.Google Scholar
Allison, D. B., Allison, R. L., Faith, M. S., Paultre, F. and Pi-Sunyer, F. X. (1997) Power and money: designing statistically powerful studies while minimizing financial costs. Psychological Methods, 2, 20–33.CrossRefGoogle Scholar
Beck, M. W. (1997) Inference and generality in ecology: Current problems and an experimental solution. Oikos, 78, 265–73.CrossRefGoogle Scholar
Carey, J. M. and Keough, M. J. (2002) The variability of estimates of variance, and its effect on power analysis in monitoring design. Environmental Monitoring and Assessment, 74, 225–41.CrossRefGoogle ScholarPubMed
Cohen, J. (1988) Statistical Power Analysis for the Behavioral Sciences, Second Edition. New Jersey: Lawrence Erlbaum.Google Scholar
Cohen, J. (1992) Quantitative methods in psychology: a power primer. Psychological Bulletin, 112, 155–9.CrossRefGoogle Scholar
Colegrave, N. and Ruxton, G. D. (2003) Confidence intervals are a more useful complement to nonsignificant tests than are power calculations. Behavioral Ecology, 14, 446–450.CrossRefGoogle Scholar
Crawley, M. J. (2002) Statistical Computing. An Introduction to Data Analysis using S-Plus. Chichester: Wiley.Google Scholar
Darlington, R. B. and Smulders, T. V. (2001) Problems with residual analysis. Animal Behaviour, 62, 599–602.CrossRefGoogle Scholar
Davey, A. J. H. (2003) Competitive interactions in stream fish communities. Ph.D. thesis, University of Southampton, Southampton.Google Scholar
Day, R. W. and Quinn, G. P. (1989) Comparisons of treatments after an analysis of variance in ecology. Ecological Monographs, 59, 433–63.CrossRefGoogle Scholar
Dayton, P. K. (1998) Reversal of the burden of proof in fisheries management. Science, 279, 821–2.CrossRefGoogle Scholar
Di Stefano, J. (2003) How much power is enough? Against the development of an arbitrary convention for statistical power calculations. Functional Ecology, 17, 707–9.CrossRefGoogle Scholar
Dytham, C. (1999, 2003) Choosing and Using Statistics: A Biologist's Guide. Oxford: Blackwell.Google Scholar
Field, S. A., Tyre, A. J., Jonzén, N., Rhodes, J. R. and Possingham, H. P. (2004) Minimizing the cost of environmental management decisions by optimizing statistical thresholds. Ecology Letters, 7, 669–75.CrossRefGoogle Scholar
Freckleton, R. P. (2002) On the misuse of residuals in ecology: regression of residuals vs. multiple regression. Journal of Animal Ecology, 71, 542–5.CrossRefGoogle Scholar
García-Berthou, E. (2001) On the misuse of residuals in ecology: testing regression residuals vs. the analysis of covariance. Journal of Animal Ecology, 70, 708–11.CrossRefGoogle Scholar
Grafen, A. and Hails, R. (2002) Modern Statistics for the Life Sciences. Oxford: Oxford University Press.Google Scholar
Graham, M. H. and Edwards, M. S. (2001) Statistical significance versus fit: estimating the importance of individual factors in ecological analysis of variance. Oikos, 93, 505–13.CrossRefGoogle Scholar
Greenwood, J. J. D. (1993) Statistical power. Animal Behaviour, 46, 1011.CrossRefGoogle Scholar
Hines, W. G. S. (1996) Pragmatics of pooling in ANOVA tables. The American Statistician, 50, 127–39.Google Scholar
Hoenig, J. M. and Heisey, D. M. (2001) The abuse of power: the pervasive fallacy of power calculations for data analysis. American Statistician, 55, 19–24.CrossRefGoogle Scholar
Hurlbert, S. H. (1984) Pseudoreplication and the design of ecological field experiments. Ecological Monographs, 54, 187–211.CrossRefGoogle Scholar
Ioannidis, J. P. A. (2005) Why most published research findings are false. Public Library of Science Medicine, 2, 696–701.Google ScholarPubMed
Janky, D. G. (2000) Sometimes pooling for analysis of variance hypothesis tests: a review and study of a split-plot model. The American Statistician, 54, 269–79.Google Scholar
Jennions, M. D. and Møller, A. P. (2003) A survey of the statistical power of research in behavioral ecology and animal behavior. Behavioral Ecology, 14, 438–45.CrossRefGoogle Scholar
Kent, A., Hawkins, S. J. and Doncaster, C. P. (2003) Population consequences of mutual attraction between settling and adult barnacles. Journal of Animal Ecology, 72, 941–52.CrossRefGoogle Scholar
Keough, M. J. and Mapstone, B. D. (1997) Designing environmental monitoring for pulp mills in Australia. Water Science and Technology, 35, 397–404.CrossRefGoogle Scholar
Keppel, G. and Wickens, T. D. (1973, 1982, 1991, 2004) Design and Analysis: A Researcher's Handbook. New Jersey: Prentice-Hall.Google Scholar
Kirk, R. E. (1968, 1982, 1994) Experimental Design: Procedures for the Behavioural Sciences. Belmont CA: Wadsworth.Google Scholar
Lenth, R. V. (2001) Some practical guidelines for effective sample size determination. American Statistician, 55, 187–93.CrossRefGoogle Scholar
Mapstone, B. D. (1995) Scalable decision rules for environmental impact studies: effect size, Type I and Type II errors. Ecological Applications, 5, 401–10.CrossRefGoogle Scholar
McClelland, G. H. (1997) Optimal design in psychological research. Psychological Methods, 2, 3–19.CrossRefGoogle Scholar
McKillup, S. 2006. Statistics Explained. An Introductory Guide for Life Scientists. Cambridge: Cambridge University Press.Google Scholar
Moran, M. D. (2003) Arguments for rejecting the sequential Bonferroni in ecological studiesOikos, 100, 403–5.CrossRefGoogle Scholar
Motulsky, H. and Christopoulos, A. (2004) Fitting Models to Biological Data Using Linear and Nonlinear Regression. Oxford: Oxford University Press.Google Scholar
Newman, J. A., Bergelson, J. and Grafen, A. (1997) Blocking factors and hypothesis tests in ecology: is your statistics text wrong?Ecology, 78, 1312–20.CrossRefGoogle Scholar
Peterman, R. M. (1990) Statistical power analysis can improve fisheries research and management. Canadian Journal of Fisheries and Aquatic Sciences, 47, 2–15.CrossRefGoogle Scholar
Quinn, G. P. and Keough, M. J. (2002) Experimental Design and Data Analysis for Biologists. Cambridge: Cambridge University Press, UK.CrossRefGoogle Scholar
Ratkowski, D. A., Evans, M. A. and Alldredge, J. R. (1993) Cross-over Experiments. Design, Analysis and Application. Statistics Textbooks and Monographs. New York: Marcel Dekker.Google Scholar
Resetarits, W. J. Jr. and Bernardo, J. (eds.) (1998) Experimental Ecology: Issues and Perspectives. Oxford: Oxford University Press.Google Scholar
Ruxton, G. D. and Colegrave, N. (2003) Experimental Design for the Life Sciences. Oxford: Oxford University Press.Google Scholar
Schultz, E. F. (1955) Rules of thumb for determining expectations of mean squares in analysis of variance. Biometrics, 11, 123–35.CrossRefGoogle Scholar
Searle, S. R. (1971, 1997) Linear Models. New York: John Wiley.Google Scholar
Searle, S. R., Casella, G. and McCulloch, C. E. (1992) Variance Components. New York: John Wiley & Sons.CrossRefGoogle Scholar
Shaw, R. G. and Mitchell-Olds, T. (1993) ANOVA for unbalanced data: an overview. Ecology, 74, 1638–45.CrossRefGoogle Scholar
Sokal, R. R. and Rohlf, F. J. (1969, 1981, 1995) Biometry. New York: Freeman and Co.Google Scholar
Tagg, N., Innes, D. J. and Doncaster, C. P (2005). Outcomes of reciprocal invasions between genetically diverse and genetically uniform populations of Daphnia obtusa (Kurz). Oecologia, 143, 527–36.CrossRefGoogle Scholar
Thomas, L. and Juanes, F. (1996) The importance of statistical power analysis: an example from animal behaviour. Animal Behaviour, 52, 856–9.CrossRefGoogle Scholar
Underwood, A. J. (1994) On beyond BACI: sampling designs that might reliably detect environmental disturbance. Ecological Applications, 4, 3–15.CrossRefGoogle Scholar
Underwood, A. J. (1997) Experiments in Ecology: Their Logical Design and Interpretation Using Analysis of Variance. Cambridge: Cambridge University Press.Google Scholar
Winer, B. J., Brown, D. R. and Michels, K. M. (1962, 1971, 1991) Statistical Principles in Experimental Design. New York: McGraw-Hill.CrossRefGoogle Scholar
Zar, J. H. (1974, 1984, 1996, 1998) Biostatistical Analysis. New Jersey: Prentice Hall.Google Scholar

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