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References

  • Abadi, F., Gimenez, O., Arlettaz, R. & Schaub, M. (2010). An assessment of integrated population models: bias, accuracy, and violation of the assumption of independence. Ecology 91, 714.
  • Besbeas, P., Freeman, S.N., Morgan, B.J.T. & Catchpole, E.A. (2002). Integrating mark-recapture-recovery and census data to estimate animal abundance and demographic parameters. Biometrics 58, 540547.
  • Gelman, A. (2005). Analysis of variance: why is it more important than ever (with discussion). Ann. Stat. 33, 153.
  • Gelman, A. & Hill, J. (2007). Data analysis using regression and multilevel/hierarchical models. Cambridge: Cambridge University Press.
  • Gurevitch, J., Curtis, P.S. & Jones, M.H. (2001). Meta-analysis in ecology. Adv. Ecol. Res. 32, 199247.
  • Halstead, B.J., Wylie, G.D., Coates, P.S., Valcarcel, P. & Casazza, M.L. (2012). Bayesian shared frailty models for regional inference about wildlife survival. Anim. Conserv. 15, 117124.
  • Kéry, M. (2010). Introduction to winbugs for Ecologists. – A Bayesian approach to regression, ANOVA, mixed models and related analyses. Burlington: Academic Press.
  • Kéry, M. & Schaub, M. (2012). Bayesian population analysis using WinBUGS. A hierarchical perspective. Waltham: Academic Press.
  • Lunn, D.J., Thomas, A., Best, N. & Spiegelhalter, D. (2000). WinBUGS – A Bayesian modelling framework: concepts, structure, and extensibility. Stat. Comput. 10, 325337.
  • Papadatou, E., Pradel, R., Schaub, M., Dolch, D., Geiger, H., Ibanez, C., Kerth, G., Popa-Lisseanu, A., Schorcht, W., Teubner, J. & Gimenez, O. (2012). Comparing survival among species with imperfect detection using multilevel analysis of mark-recapture data: a case study on bats. Ecography 35, 153161.
  • Plummer, M. (2003). JAGS: a program for analysis of bayesian graphical models using Gibbs sampling. Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003). pp. 1-10. Vienna, Austria.
  • Royle, J.A. & Dorazio, R.M. (2008). Hierarchical modeling and inference in ecology. The analysis of data from populations, metapopulations and communities. New York: Academic Press.