Outcome
variables may be of several types. The most important types
include continuous, dichotomous, categorical, and survival variables
(Altman,
1991).
Continuous
variables may be analyzed as interval data, i.e. that a difference
in one unit has the same meaning for all values of the variable.
An example is temperature, either in C or F, where a one-degree
difference has the same meaning at zero or 100 degrees. Measurements
of symptoms may sometimes be on a continuous scale. For
example, a visual analogue scale (VAS) may be used for the rating
of pain, but, whether such a scale truly represents an interval
scale is debatable. As long as the researcher is explicit about
the assumption made and thoughtful about whether it might be
misleading, scales for pain may often be treated as interval
scales.
Dichotomous
variables take one of two values. For example, a risk factor
may be present or not; complications after treatment occur or
do not occur; patients survive until 30 days after admission
or die before 30 days. The researcher must be thoughtful if
a dichotomy is constructed. Often, dichotomies are arbitrary
splits of physiologically continuous variables (e.g. age under
or over 50 years).
Categorical
variables
have more than 2 categories. These variables can be analyzed
as nominal data, when no ordering is present, or as ordinal
data, when an ordering is present. For example, disease category
at primary diagnosis might be a nominal variable, and patient
satisfaction measured on a 5-point Likert scale might be an
ordinal
variable.
Survival
variables may be used to analyze mortality over time, or the
occurrence of complications in time. Survival variables actually
consist of two components: a continuous time-to-event variable
which indicates a duration, and a dichotomous censoring
variable which indicates whether the event occurred, e.g. whether
the patient died or had a complication. When the event did not
occur, this is registered as "censoring", i.e. that the event
had not occurred by the end of follow-up. Censoring may be due
to the end of the study period, i.e. related to a certain calendar
time. In this case, it may safely be assumed to be unrelated
to the occurrence of the event. However, censoring is also coded
for patients who are lost to follow-up (e.g. refusal to participate
further, lost contact, etc.), which may have several underlying
reasons that may be related to the event (e.g. progression of
the disease).