Information Technology Reference
In-Depth Information
decide what you wish to observe and measure and how you will go about
observing it.
Good practice is to draft the analysis section of your final report
based on the conclusions you would like to make. What information do
you need to justify these conclusions? All such information must be
collected.
The next section is devoted to the choice of measuring devices, fol-
lowed by sections on determining sample size and preventive steps to
ensure your samples will be analyzable by statistical methods.
MEASURING DEVICES
Know what you want to measure. Collect exact values whenever possible.
Know what you want to measure. Will you measure an endpoint such as
death or measure a surrogate such as the presence of HIV antibodies? The
regression slope describing the change in systolic blood pressure (in mm
Hg) per 100 mg of calcium intake is strongly influenced by the approach
used for assessing the amount of calcium consumed (Cappuccio et al.,
1995). The association is small and only marginally significant with diet
histories (slope -0.01 (-0.003 to -0.016)) but large and highly significant
when food frequency questionnaires are used (-0.15 (-0.11 to -0.19)).
With studies using 24-hour recall, an intermediate result emerges (-0.06
(-0.09 to -0.03)). Diet histories assess patterns of usual intake over long
periods of time and require an extensive interview with a nutritionist,
whereas 24-hour recall, and food frequency questionnaires are simpler
methods that reflect current consumption (Block, 1982).
Before we initiate data collection, we must have a firm idea of what we
will measure.
A second fundamental principle is also applicable to both experiments
and surveys: Collect exact values whenever possible. Worry about group-
ing them in interval or discrete categories later.
A long-term study of buying patterns in New South Wales illustrates
some of the problems caused by grouping prematurely. At the beginning
of the study, the decision was made to group the incomes of survey sub-
jects into categories, under $20,000, $20,000 to $30,000, and so forth.
Six years of steady inflation later, the organizers of the study realized that
all the categories had to be adjusted. An income of $21,000 at the start of
the study would only purchase $18,000 worth of goods and housing at
the end. The problem was that those surveyed toward the end had filled
out forms with exactly the same income categories. Had income been
tabulated to the nearest dollar, it would have been easy to correct for
increases in the cost of living and convert all responses to the same scale.
