an epidemiological study of listeriosis in dairy cattle

association (Kirkwood 1988, Thrusfield 1995). This problem is overcome by several
ways i.e. stratifying data to adjust for possible confounders or employing more complex
multivariate techniques. This is dealt with in the following chapter. However there also
are advantages of this technique. In univariate analysis it is possible to examine the
association between all predictor variables and an outcome. All observations obtained
can be used in the univariate analysis whereas in the multivariate analysis missing
values can result in a considerable reduction in the number of observations.
In the analysis of this data, possible confounders were not taken into account but
a number of predictor variables were found to be associated with the outcome variables.
However demonstration of a statistically significant association between a predictor
variable and an outcome variable does not necessarily mean that a relationship is causal.
In a biological sense for a predictor variable to be causal it must be experimentally
proved that it leads to the occurrence of disease. However in the absence of
experimental evidence epidemiological identification of an association is of
considerable value because it indicates a risk factor and removal of such a factor may
result in the reduction of disease (Thrusfield 1995).
In the following chapter the association between the predictor variables and the
different outcome variables is investigated using multivariate techniques.
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