Mixed models: Getting the best use of parasitological data

Trends in Parasitology

Volumn 19, Issue 8, 2003, Pages 370-375

  Paterson, Steve ^a   Lello, Joanne ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER PROGRAM; DISEASE CONTROL; DISEASE PREDISPOSITION; EPIDEMIOLOGICAL DATA; HOST PARASITE INTERACTION; HUMAN; NONHUMAN; PARASITE PREVALENCE; PARASITOSIS; REVIEW; STATISTICAL ANALYSIS; STATISTICAL MODEL;

PROTOZOA;

EID: 0041704534     PISSN: 14714922     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1471-4922(03)00149-1     Document Type: Review

References (36)

1. Wilson K., Grenfell B.T. Generalized linear modelling for parasitologists. Parasitol. Today. 13:1997;33-38.
2. Pacala S.W., Dobson A.P. The relation between the number of parasites and host age: population causes and maximum likelihood estimation. Parasitology. 96:1988;197-210.
3. Paterson S. The use of repeated measure linear modelling to analyze longitudinal data from experimental parasite infections. J. Parasitol. 87:2001;969-971.
4. Wilson K., et al. Analysis of aggregated parasite distributions: a comparison of methods. Funct. Ecol. 10:1996;592-601.
5. Zinsstag J., et al. Effect of strategic gastrointestinal nematode control on faecal egg count in traditional West African cattle. Vet. Res. 31:2000;259-266.
6. Crawley M.J. GLIM for Ecologists. 1993;Blackwell Scientific Publications.
7. Lindsey J.K. Models for Repeated Measures. 1999;Oxford University Press.
8. Crowder M.J., Hand D.J. Analysis of Repeated Measures. 1990;Chapman & Hall.
9. Grafen A., Hails R.S. Modern Statistics for the Life Sciences. 2002;Oxford University Press.
10. Smith J.A., et al. Heritable variation in resistance to gastro-intestinal nematodes in an unmanaged mammal population. Proc. R. Soc. Lond. B Biol. Sci. 266:1999;1283-1290.
11. Sokal R.R., Rohlf F.J. Biometry. 1995;Freeman.
12. Diggle P., et al. Childhood malaria in the Gambia: a case-study in model-based geostatistics. J. R. Stat. Soc. 51:2002;493-506.
13. Shaw D.J., Dobson A.P. Patterns of macroparasitic abundance and aggregation in wildlife populations: a quantitative review. Parasitology. 111:1996;S111-S133.
14. Hudson, P.J. and Dobson, A.P. (1995) Macroparasites: observed patterns. In Ecology of Infectious Diseases in Natural Populations (Grenfell, B.T. and Dobson, A.P., eds), pp. 144-176, Cambridge University Press.
15. McCulloch C.E., Searle S.R. Generalized, Linear and Mixed Models. 2001;Wiley.
16. Breslow N.E., Clayton D.G. Approximate inference in generalised linear mixed models. J. Am. Stat. Assoc. 88:1993;9-25.
17. Crompton D.W.T., et al. Investigating over-dispersion; Moniformis (Acanthocephala) and rats. Parasitology. 88:1984;317-331.
18. Anderson, R.M. and May, R.M. (1992) Infectious Diseases of Humans: Dynamics and Control, Oxford University Press.
19. Bliss C.I., Fisher R.A. Fitting the negative binomial distribution to biological data. Biometrics. 9:1953;176-200.
20. Wilson, K. et al. (2002) Heterogeneities in macroparasite infections: patterns and processes. In The Ecology of Wildlife Diseases (Hudson, P.J. et al., eds), pp. 6-44, Oxford University Press.
21. Anderson R.M., May R.M. Regulation and stability of host-parasite population interactions; regulatory processes. J. Anim. Ecol. 47:1978;219-247.
22. May R.M., Anderson R.M. Regulation and stability of host-parasite population interactions; destabilising processes. J. Anim. Ecol. 47:1978;249-267.
23. Grenfell B.T., et al. Modelling patterns of parasite aggregation in natural populations: trichostrongylid nematode-ruminant interactions as a case study. Parasitology. 111:1995;S135-S151.
24. Smith, G. et al. (1995) Macroparasite group report. In Ecology of Infectious Diseases in Natural Populations (Grenfell, B.T. and Dobson, A.P., eds), pp. 209-229, Cambridge University Press.
25. Elston D.A., et al. Analysis of aggregation, a worked example: numbers of ticks on red grouse chicks. Parasitology. 122:2001;563-569.
26. Falconer, D.S. (1989) Introduction to Quantitative Genetics, Longman Scientific and Technical.
27. Tempelman R.J. Generalized linear mixed models in dairy cattle breeding. J. Dairy Sci. 81:1998;1428-1444.
28. Stear M.J., et al. The genetic basis of resistance to Ostertagia circumcincta in lambs. Vet. J. 154:1997;111-119.
29. Stear M.J., et al. Regulation of egg-production, worm burden, worm length and worm fecundity by host responses in sheep infected with Ostertagia circumcincta. Parasite Immunol. 17:1995;643-652.
30. Stear M.J., et al. The processes influencing the distribution of parasitic nematodes among naturally infected lambs. Parasitology. 117:1998;165-171.
31. Strain S.A.J., et al. The genetic control of IgA activity against Teladorsagia circumcincta and its association with parasite resistance in naturally infected sheep. Parasitology. 124:2002;545-552.
32. Stear M.J., et al. Eosinophilia as a marker of resistance to Teladorsagia circumcincta in Scottish Blackface lambs. Parasitology. 124:2002;553-560.
33. Morrison D.A. How to improve statistical analysis in parasitology research publications. Int. J. Parasitol. 32:2002;1065-1070.
34. Gamerman D. Markov Chain Monte Carlo. 1997;Chapman & Hall.
35. Lagarias J.C., et al. Convergence properties of the nelder-mead simplex algorithm in low dimensions. SIAM J. Optimization. 9:1998;112-147.
36. McCullagh P., Nelder J.A. Generalised Linear Models. 1989;Chapman & Hall.