SEARCH

SEARCH BY CITATION

References

  • Bates, D.M., Maechler, M. & Dai, B. (2008) lme4: linear mixed-effects models using S4 classes. URL http://lme4.r-forge.r-project.org/ [version 0.999375-40]
  • Brommer, J.E., Merilä, J., Sheldon, B.C. & Gustafsson, L. (2005) Natural selection and genetic variation for reproductive reaction norms in a wild bird population. Evolution, 59, 13621371.
  • Charmantier, A., McCleery, R.H., Cole, L.R., Perrins, C.M., Kruuk, L.E.B. & Sheldon, B.C. (2008) Adaptive phenotypic plasticity in response to climate change in a wild bird population. Science, 320, 800803.
  • Chevin, L.-M., Lande, R. & Mace, G.M. (2010) Adaptation, plasticity, and extinction in a changing environment: towards a predictive theory. PLoS Biology, 8, e1000357.
  • Dingemanse, N.J., Kazem, A.J.N., Réale, D. & Wright, J. (2010) Behavioural reaction norms: animal personality meets individual plasticity. Trends in Ecology & Evolution, 25, 8189.
  • Dingemanse, N.J., Bouwman, K.M., van de Pol, M., van Overveld, T., Patrick, S., Matthysen, E. & Quinn, J.S. (2011) Variation in personality and behavioural plasticity across four populations of the great tit Parus major. Journal of Animal Ecology, doi: 10.1111/j.1365-2656.2011.01877.x
  • Hadfield, J.D. (2008) Estimating evolutionary parameters when viability selection is operating. Proceedings of the Royal Society B: Biological Sciences, 275, 723734.
  • Henderson, C.R. (1982) Analysis of covariance in the mixed model: higher-level, nonhomogeneous, and random regressions. Biometrics, 38, 623640.
  • Hox, J.J. (2010) Multilevel Analysis. Techniques and Applications. Routledge, New York.
  • de Jong, G. (1990) Quantitative genetics of reaction norms. Journal of Evolutionary Biology, 3, 447468.
  • Kreft, I.G.G. (1996) Are Multilevel Techniques Necessary? An Overview Including Simulation Studies. California State University, Los Angeles.
  • Maas, C.J.M. & Hox, J.J. (2004a) Robustness issues in multilevel regression analysis. Statistica Neerlandica, 58, 127137.
  • Maas, C.J.M. & Hox, J.J. (2004b) The influence of violations of assumptions on multilevel parameter estimates and their standard errors. Computational Statistics & Data Analysis, 46, 427440.
  • Martin, J.G.A., Nussey, D.H., Wilson, A.J. & Réale, D. (2011) Measuring individual differences in reaction norms in field and experimental studies: a power analysis of random regression models. Methods in Ecology and Evolution, 2, 362374.
  • Moineddin, R., Matheson, F.I. & Glazier, R.H. (2007) A simulation study of sample size for multilevel logistic regression models. BMC Medical Research Methodology, 7, 34.
  • Nussey, D.H., Wilson, A.J. & Brommer, J.E. (2007) The evolutionary ecology of individual phenotypic plasticity in wild populations. Journal of Evolutionary Biology, 20, 831844.
  • Nussey, D.E., Postma, E., Gienapp, P. & Visser, M.E. (2005) Selection on heritable phenotypic plasticity in a wild bird population. Science, 310, 304306.
  • Pigliucci, M. (2001) Phenotypic Plasticity: Beyond Nature and Nurture. Johns Hopkins University Press, Baltimore.
  • Pinheiro, J.C. & Bates, D.M. (2000) Mixed-Effects Models in S and S-plus. Springer Verlag, New York.
  • van de Pol, M. (2011) R-package odprism: Optimal Design and Performance of Random Intercept and Slope Models. URL http://cran.r-project.org/web/packages/odprism/ [version 1.0]
  • van de Pol, M. & Verhulst, S. (2006) Age-dependent traits: a new statistical model to separate within- and between-individual effects. American Naturalist, 167, 766773.
  • van de Pol, M. & Wright, J. (2009) A simple method for distinguishing within- versus between-subject effects using mixed models. Animal Behaviour, 77, 753758.
  • van de Pol, M., Osmond, H. & Cockburn, A. (In press) Fluctuations in population composition dampen the impact of phenotypic plasticity on trait dynamics in superb fairy-wrens. Journal of Animal Ecology. doi: 10.1111/j.1365-2656.2011.01919.x.
  • R Development Core Team (2010) R: a language and environment for statistical computing. R foundation for statistical computing, Vienna. http://www.r-project.org [version 2.11.0].
  • Raudenbush, S.W., Spybrook, J., Congdon, R., Liu, X. & Martinez, A. (2011) Optimal Design software for multi-level and longitudinal research. URL http://www.wtgrantfoundation.org or from sitemaker.umich.edu/group-based.
  • Reed, T.E., Wanless, S., Harris, M.P., Frederiksen, M., Kruuk, L.E.B. & Cunningham, E.J.A. (2006) Responding to environmental change: plastic responses vary little in a synchronous breeder. Proceedings of the Royal Society B: Biological Sciences, 273, 27132719.
  • Reed, T.E., Waples, R.S., Schindler, D.E., Hard, J.J. & Kinnison, M.T. (2010) Phenotypic plasticity and population viability: the importance of environmental predictability. Proceedings of the Royal Society B: Biological Sciences, 277, 33913400.
  • Scheipl, F., Greven, S. & Kuchenhoff, H. (2008) Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models. Computational Statistics & Data Analysis, 52, 32833299.
  • Scherbaum, C.A. & Ferreter, J.M. (2009) Estimating statistical power and required sample sizes for organizational research using multilevel modeling. Organizational Research Methods, 12, 347367.
  • Schielzeth, H. & Forstmeier, W. (2009) Conclusions beyond support: overconfident estimates in mixed models. Behavioral Ecology, 20, 416420.
  • Sih, A., Bell, A.M., Johnson, J.C. & Ziemba, R.E. (2004) Behavioral syndromes: an integrative overview. The Quarterly Review of Biology, 79, 241277.
  • Snijders, T.A.B. (2005) Power and sample size in multilevel linear models. Encyclopedia of Statistics in Behavioral Science, volume 3 (eds B.S. Everitt & D.C. Howell), pp. 15701573. Wiley, Chicester.
  • Snijders, T.A.B. & Bosker, R.J. (1993) Standard errors and sample sizes for two-level research. Journal of Educational Statistics, 18, 237259.
  • Snijders, T.A.B. & Bosker, R.J. (1999) Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling. SAGE Publications, London.
  • Vaupel, J.W., Manton, K.G. & Stallard, E. (1979) The impact of heterogeneity in individual frailty on the dynamics of mortality. Demography, 16, 439454.
  • Verbeek, M. (2000) A Guide to Modern Econometrics. Wiley, New York.
  • Vindenes, Y., Engen, S. & Saether, B.-E. (2008) Individual heterogeneity in vital parameters and demographic stochasticity. The American Naturalist, 171, 455467.
  • Visscher, P.M. (2006) A note on the asymptotic distribution of likelihood ratio tests to test variance components. Twin Research and Human Genetics, 9, 490495.
  • Visser, M.E. (2008) Keeping up with a warming world; assessing the rate of adaptation to climate change. Proceedings of the Royal Society B: Biological Sciences, 275, 649659.