joint strategic needs assessment foundation profile - JSNA

Interative Hull Atlas: www.hullpublichealth.org/Pages/hull_atlas.htm More information: www.jsnaonline.org and www.hullpublichealth.org
important and the fact that both areas report high levels of poor health may be more
important. One such test is the 2 test which compares the percentages between different
groups (with the original assumption that the percentages are the same for all groups).
The
2 test for trend compares the percentages across different groups with ordered
categories, such as deprivation, and assesses whether there is an increasing or
decreasing trend in the percentages across the ordered categories. McNemar‟s test can
be used to compare paired percentages. Paired data occurs when responses from the
same individual are compared, paired analyses generally occur when the aim is
compare changes over time (see evaluation of Community Physical Activity Survey in
section 8.6.9 on page 319).
Another test is the t-test which compares the mean or average of a parameter between two
groups. A paired test is used
12.5 Confidence Intervals
A confidence interval (CI), calculated using statistical methods, gives a range of likely
values for the parameter of interest. Since one cannot generally survey all people for all
years within all geographical areas of interest, it is common practice to obtain necessary
data from a sample of the population. However, different samples will result in different
estimates for the measure of interest due to natural variation of measurement data
(assuming all other influences remain constant). Therefore, it is useful to have a range
of values for the measure of interest (e.g. percentage or mean, difference between two
means or measure of risk, etc) rather than a single value to get an idea of the range of
likely values. The usual CI calculated is the 95% CI, in which we are 95% confident that
the interval obtained (from the sample) will contain the true underlying measure of
interest. Having a range of values for which the population statistic/measure lies is
much more useful than having a single value. The interval also takes into consideration
the number of people on which the estimate is based, so that if there are many people
surveyed the interval tends to be narrower (and therefore more useful). The 95% CI for
a difference in a percentage or mean between two groups that does not include the
value zero (i.e. the percentage or mean is not the same for both groups) will have a pvalue
less than 0.05 72 (see section 12.4 on page 774). If the CI is wide then this
suggests uncertainty regarding the underlying statistic.
For example, if the standardised mortality ratio is 140 then it implies there is an increase
of 40% in the mortality rate locally compared to that in the standard population (which
may be national population). This raises immediate concern. However, if the 95% CI
ranges from 50 to 230 then it implies that the true underlying ratio lies between 50 and
230, i.e. half the mortality locally compared to nationally through to more than twice the
mortality rate locally compared to that observed nationally. Since this is a wide range,
we are less confident in saying that there is an increased mortality rate locally as it could
very easily have occurred by natural variation of measurements rather than representing
72 In rare cases this is not the case depending on the way in which the statistical test is undertaken and
the assumptions made, however, if it is not true then the p-value will be close to 0.05.
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