[en] The goal of this study is to assess the effect of follicle stimulating hormone (FSH)
on the growth of follicles in prepubertal heifers. Adams and co-workers have shown that follicles
develop in waves as in post-pubertal heifers: after a few days, a dominant follicle arises on one
of the two ovaries whereas the other subordinate follicles regress.The dominant follicle remains
detectable when the next wave occurs. The number and the diameters of these follicles have
been measured for 14 days.The same experiment was repeated after a 3-day FSH stimulation.
Several large follicles now arise simultaneously on both ovaries together with small follicles
which cannot be detected any more when the next wave occurs. Unfortunately, follicles were
not individually tracked. Therefore a three-component mixture model was used to describe the
potential simultaneous observation of dominant, decaying dominant and subordinate follicles
before the FSH stimulation; the same type of model was considered for large, decaying large
and small follicles after the hormonal stimulation. Moreover, for technical reasons, only follicles
larger than 2 mm are observable. Measurements were thus left truncated.The models fitted are
used to quantify the effects of the stimulation and to determine the ideal time point at which
follicles should be punctured under ultrasonography to harvest ovocytes that will be fertilized
and cultured in vitro.
Disciplines :
Mathematics
Author, co-author :
Lambert, Philippe ; Université de Liège - ULiège > Institut des sciences humaines et sociales > Méthodes quantitatives en sciences sociales
Language :
English
Title :
A mixture model to assess the effect of a hormonal stimulation on the development of follicles in prepubertal heifers
Publication date :
2002
Journal title :
Journal of the Royal Statistical Society. Series C, Applied Statistics
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Bibliography
Adams, G., Evans, A. and Rawlings, N. (1994) Follicular waves and circulating gonadotrophins in 8-month-old prepubertal heifers. J. Reprodn Fertil., 100, 27-33.
Akaike, H. (1973) Information theory and an extension of the maximum likelihood principle. In Proc. 2nd Int. Symp. Inference Theory (eds B.N. Petrov and F. Csáki), pp. 267-281. Budapest: Akadémiai Kiadó.
Hinde, J. (1982) Compound poisson regression models. In GLIM82 (ed. R. Gilchrist), pp. 109-121. New York: Springer.
Ihaka, R. and Gentleman, R. (1996) R: a language for data analysis and graphics. J. Comput. Graph. Statist., 5, 299-314.
McCullagh, P. and Nelder, J.A. (1989) Generalized Linear Models, 2nd edn. London: Chapman and Hall.
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