The data for this cross-sectional retrospective study are from surveys
of 65 dairy-cattle herds in central New York, USA sampled between Feb
ruary, 1993 and March, 1995. The objective was to identify probability
distributions of logarithmically transformed somatic-cell counts (lin
ear score) for use in a simulation model of mastitis and milk quality.
Probability density functions were estimated using maximum-likelihood
estimators for the linear score of individual-cow composite-milk samp
les culture negative and culture positive for the pathogens Streptococ
cus agalactiae, Streptococcus non-agalactiae, Staphylococcus aureus, a
nd coagulase-negative staphylococci for the complete dataset and by bu
lk-tank somatic-cell count group (<500 000, greater than or equal to 5
00 000 SCC/ml). Based on the rankings of three goodness-of-fit tests (
Anderson-Darling, Kolmogorov-Smirnov and chi(2)), the Weibull distribu
tion (among the three top-ranking distributions for 14 out of 15 cases
) may be used to model the individual-cow linear-score response by cul
ture-result-specific bulk-tank somatic-cell count group. A beta distri
bution was among the three top-ranking distributions for nine out of 1
5 culture-result-specific bulk-tank somatic-cell count groups and has
a logical relationship to linear score because it is defined on a fixe
d interval. On the other hand, the normal distribution had a poorer fi
t than the Weibull and at least two other distributions far all cultur
e negative and coagulase-negative staphylococci samples. We do not ass
ume that the underlying biological processes are fully explained by ei
ther Weibull or beta distribution-but modelling the Linear score for t
he above culture results with these distributions provided an adequate
fit to the survey data, reduced the need for two-sided truncation tha
t open intervals needed, and had errors that did not appear to be syst
ematically positive or negative. (C) 1998 Elsevier Science B.V.