GLOSSARY
OF TERMS
     
     
S
Sampling
error
See
random
error.
Selection
bias
- In
assessments of the validity of studies of healthcare interventions,
selection bias refers to systematic differences between
comparison groups in prognosis or responsiveness to treatment.
Random allocation with adequate concealment of allocation
protects against selection bias. Other means of selecting
who receives the intervention of interest, particularly leaving
it up to the providers and recipients of care, are more prone
to bias because decisions about care can be related
to prognosis and responsiveness to treatment.
- Selection
bias is sometimes used to describe a systematic error in reviews
due to how studies are selected for inclusion. Publication
bias is an example of this type of selection bias.
- Selection
bias, confusingly, is also sometimes used to describe a systematic
difference in characteristics between those who are selected
for study and those who are not. This affects the generalizability
(external
validity)
of a study but not its (internal) validity.
Sensitivity
analysis
An
analysis used to determine how sensitive the results of a study
or systematic review are to changes in how it was done.
Sensitivity analyses are used to assess how robust the results
are to uncertain decisions or assumptions about the data and
the methods that were used.
Sequential
trial
A
trial in which the data are analyzed after each patient's results
become available, and the trial continues until a clear
benefit is seen in one of the comparison groups, or it is unlikely
that any difference will emerge. The main advantage of sequential
trials is that they will be shorter than fixed length
trials when there is a large difference in the effectiveness
of the interventions being compared. Their use is restricted
to conditions where the outcome is known relatively quickly.
Single
blind
(synonym: single masked)
The investigator is aware of the treatment/intervention
the participant is getting, but the participant is unaware.
See also blinding,
double
blind,
triple
blind.
Specialized
register
See
Trials
Register.
Standardized mean difference
The
difference between two means divided by an estimate of the within-group
standard deviation. When an outcome (such as pain) is
measured in a variety of ways across studies (using different
scales) it may not be possible directly to compare or combine
study results in a systematic review. By expressing the
effects as a standardized value the results can be combined
since they have no units. Standardized mean differences are
sometimes referred to as a d index.
Statistical
power
The
probability that the null hypothesis will be rejected if it
is indeed false. In studies of the effectiveness of healthcare
interventions, power is a measure of the certainty of avoiding
a false negative conclusion that an intervention is not effective
when in truth it is effective. The power of a study is determined
by how large it is (the number of participants), the number
of events (e.g. strokes) or the degree of variation in a continuous
outcome (such as weight), how small an effect one believes is
important (i.e. the smallest difference in outcomes between
the intervention and the control groups that is considered to
be important), and how certain one wants to be of avoiding a
false positive conclusion (i.e. the cut-off that is used for
statistical
significance).
Statistical
significance
An
estimate of the probability of an association (effect) as large
or larger than what is observed in a study occurring by
chance, usually expressed as a P-value. For example, a P-value
of 0.049 for a risk difference of 10% means that there is less
than a one in 20 (0.05) chance of an association that
is as large or larger having occurred by chance and it could
be said that the results are "statistically significant"
at P = 0.05). The cut-off for statistical significance is usually
taken at 0.05, but sometimes at 0.01 or 0.10. These cut-offs
are arbitrary and have no specific importance. Although it is
often done, it is inappropriate to interpret the results of
a study differently according to whether the P-value is,
say, 0.055 or 0.045 (which are quite similar values, not
diametrically opposed ones).
Stratified
randomization
In
any randomized trial it is desirable that the comparison groups
should be as similar as possible as regards participant
characteristics that might influence the response to the intervention.
Stratified randomization is used to ensure that equal numbers
of participants with a characteristic thought to affect prognosis
or response to the intervention will be allocated to each
comparison group. For example, in a trial of women with
breast cancer, it may be important to have similar numbers of
pre-menopausal and post-menopausal women in each comparison
group. Stratified randomization could be used to allocate equal
numbers of pre- and post-menopausal women to each treatment
group. Stratified randomization is performed either by performing
separate randomization (often using random
permuted blocks)
for each strata, or by using minimization.
Systematic
error
See
bias.
Systematic
review (synonym:
systematic overview)
A review of a clearly formulated question that uses systematic
and explicit methods to identify, select and critically
appraise relevant research, and to collect and analyze data
from the studies that are included in the review. Statistical
methods (meta-analysis)
may or may not be used to analyze and summarize the results
of the included studies.
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