Analysis of aggregation, a worked example: numbers of ticks on red grouse chicks

Parasitology - Tập 122 Số 5 - Trang 563-569 - 2001
David A. Elston1, Robert L. Moss2, Thierry Boulinier3, Colin Arrowsmith4, Xavier Lambin4
1Biomathematics and Statistics Scotland, Environmental Modelling Unit, Macaulay Land Use Research Institute, Craigiebuckler, Aberdeen, UK.
2Centre for Ecology and Hydrology, Banchory, Aberdeenshire AB31 4BW, Scotland
3Laboratoire d'Ecologie, C.N.R.S#8211;U.M.R. 7625, Université Pierre et Marie Curie, 7 Quai St Bernard, 75252 Paris, France
4Department of Zoology, University of Aberdeen, Tillydrone Avenue, Aberdeen, AB24 2TZ, Scotland

Tóm tắt

The statistical aggregation of parasites among hosts is often described empirically by the negative binomial (Poisson-gamma) distribution. Alternatively, the Poisson-lognormal model can be used. This has the advantage that it can be fitted as a generalized linear mixed model, thereby quantifying the sources of aggregation in terms of both fixed and random effects. We give a worked example, assigning aggregation in the distribution of sheep ticksIxodes ricinuson red grouseLagopus lagopus scoticuschicks to temporal (year), spatial (altitude and location), brood and individual effects. Apparent aggregation among random individuals in random broods fell 8-fold when spatial and temporal effects had been accounted for.

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Tài liệu tham khảo

10.1073/pnas.95.7.3714

GENSTAT 5 COMMITTEE (1997). Genstat 5, Release 4.1 Reference Summary. Numerical Algorithms Group, Oxford.

LAWSON, A. , BIGGERI, A. , BÖHNING, D. , LESAFFRE, E. , VIEL, J.-F. & BERTOLLINI, R. (1999). Disease Mapping and Risk Assessment for Public Health. Wiley, New York.

10.1017/S0031182000066166

PAYNE, R. W. & ARNOLD, G. M. (eds) (1998). Genstat 5 Release 4.1 Procedure Library Manual PL11. Numerical Algorithms Group, Oxford.

10.1093/biomet/78.4.719

LEE, Y. & NELDER, J. A. (2000). Two ways of modelling overdispersion. Applied Statistics 49, 591–598.

MILNE, A. (1950b). The ecology of the sheep tick, Ixodes ricinus L. Spatial distribution. Parasitology 40, 35–45.

PIELOU, E. C. (1977). Mathematical Ecology . John Wiley & Sons, New York.

LITTELL, R. C. , MILLIKEN, G. A. , STROUP, W. W. & WOLFINGER, R. D. (1996). SAS System for Mixed Models . SAS Institute Inc., Cary, N.C.

LAWSON, A. , BIGGERI, A. , BÖHNING, D. , LESAFFRE, E. , VIEL, J.-F. & BERTOLLINI, R. (Eds) (1999). Disease Mapping and Risk Assessment for Public Health. Wiley, New York.

10.2307/4512143

10.2307/2532003

10.2307/3800810

10.1017/S0031182000075867

LEE, Y. & NELDER, J. A. (1996). Hierarchical generalised linear models (with discussion). Journal of the Royal Statistical Society, B 58, 619–678.

10.1034/j.1600-0706.2000.900206.x

MCCULLAGH, P. & NELDER, J. A. (1989). Generalized Linear Models, 2nd Edn. Chapman and Hall, London.

MILNE, A. (1950a). The ecology of the sheep tick, Ixodes ricinus L. Microhabitat economy of the adult tick. Parasitology 40, 14–34.

10.2307/3800485

10.1017/S0031182000075855

10.2307/2334448