Environmental Health Criteria 214

HUMAN EXPOSURE ASSESSMENT
one is a type II error. The probability of a type I error is denoted
by alpha and the probability of a type II error by ß. Only alpha is
considered in the construction of the hypothesis test. However, as
described later, both type I and type II errors are considered in
sample size determinations.
The general procedure for common tests that try to determine if
some factor has an effect on the exposure outcome is as follows: a
test statistic is constructed whose value is known if the null
hypothesis is true. For example, if the null hypothesis is that the
population mean is 1 (H 0 : µ=1), then under the null hypothesis, × =
0, where × is the sample mean. Next, adjustments are made so that
the distribution of this test statistic is known. For example, with
s denoting the sample standard deviation and n the sample size,
the test statistic T defined by Eq. 4.12 in Table 13, where T has
a distribution which follows a t-distribution with n-1 degrees of
freedom. Now, using the known distribution of the test statistic, we
construct ranges of values for which we reject (rejection region) and
fail to reject (acceptance region) the null hypothesis. The rejection
region is any area which has probability alpha, usually chosen to
correspond to likelihoods between 0.025 and 0.05.
A large number of problems in exposure assessment involve the
comparison of two groups, for example, control and treatment; old
method and new method; or normal and abnormal. If we focus on the
location problem, where the means or the medians are compared, then
depending on the assumptions we make with regard to the data,
different tests can be performed. Assumptions typically made include:
* The data consist of a random sample from population 1 ( X 1,i ,
i = 1, ..., n), and a random sample from population 2 ( X 2,i =
1, ..., n 2 )
* The two samples are independent of each other.
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