Issue |
Genet. Sel. Evol.
Volume 35, Number 5, September-October 2003
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Page(s) | 457 - 468 | |
DOI | https://doi.org/10.1051/gse:2003034 |
DOI: 10.1051/gse:2003034
Longitudinal random effects models for genetic analysis of binary data with application to mastitis in dairy cattle
Romdhane Rekayaa, Daniel Gianolab, b and George Shookba Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA
b Department of Dairy Science, University of Wisconsin, Madison, WI 53706, USA
(Received 13 June 2002; accepted 13 March 2003)
Abstract
A Bayesian analysis of longitudinal mastitis records obtained in the
course of lactation was undertaken. Data were 3341 test-day binary
records from 329 first lactation Holstein cows scored for mastitis at
14 and 30 days of lactation and every 30 days thereafter. First, the
conditional probability of a sequence for a given cow was the product
of the probabilities at each test-day. The probability of infection at
time
t for a cow was a normal integral, with its argument being a
function of "fixed" and "random" effects and of time. Models for
the latent normal variable included effects of: (1) year-month of test
+ a five-parameter linear regression function ("fixed", within
age-season of calving) + genetic value of the cow + environmental
effect peculiar to all records of the same cow + residual. (2) As in
(1), but with five parameter random genetic regressions for each
cow. (3) A hierarchical structure, where each of three parameters of
the regression function for each cow followed a mixed effects linear
model. Model 1 posterior mean of heritability was 0.05. Model 2
heritabilities were: 0.27, 0.05, 0.03 and 0.07 at days 14, 60, 120 and
305, respectively. Model 3 heritabilities were 0.57, 0.16, 0.06 and
0.18 at days 14, 60, 120 and 305, respectively. Bayes factors were:
0.011 (Model 1/Model 2), 0.017 (Model 1/Model 3) and 1.535
(Model 2/Model 3). The probability of mastitis for an "average" cow,
using Model 2, was: 0.06, 0.05, 0.06 and 0.07 at days 14, 60, 120 and
305, respectively. Relaxing the conditional independence assumption
via an autoregressive process (Model 2) improved the results
slightly.
Key words: mastitis / longitudinal / threshold model
Correspondence and reprints: Romdhane Rekaya
e-mail: rrekaya@arches.uga.edu
© INRA, EDP Sciences 2003