GLOSSARY
OF TERMS
     
     
F
Factorial
design
Most
trials only consider a single factor, where an intervention
is compared with one or more alternatives, or a placebo. In
a trial using a 2x2 factorial design, participants are allocated
to one of four possible combinations. For example in a 2x2 factorial,
RCT of nicotine replacement and counseling, participants
would be allocated to (a) nicotine replacement alone,
(b) counseling alone, (c) both, or (d) neither. In this way
it is possible to test the independent effect of each intervention
on smoking cessation and the combined effect of (interaction
between) the two interventions.
Fixed
effect model
A
statistical model that stipulates that the units under analysis
(e.g. people in a trial or study in a meta-analysis) are
the ones of interest, and thus constitute the entire population
of units. Only within-study variation is taken to influence
the uncertainty of results (as reflected in the confidence interval)
of a meta-analysis using a fixed effect model. Variation
between the estimates of effect from each study (heterogeneity)
does not effect the confidence interval in a fixed effect model.
See random
effects model.
FTP
(File Transfer Protocol) Server
Enables users to open a connection to a host computer and
log in (often anonymously, by using 'anonymous' as the user's
name). Once logged in, files can be transferred between the
host computer and the remote computer (the computer to which
the host has been connected).
G
Generalizability
(synonyms: applicability,
external validity,
relevance, and transferability)
Generalizability is the degree to which the results of a
study or systematic review can be extrapolated to other circumstances,
in particular to routine health care situations.
Gold
standard
The
method, procedure or measurement that is widely accepted as
being the best available against which new interventions should
be compared. It is particularly important in studies of
the accuracy of diagnostic tests. For example, handsearching
is sometimes used as the gold standard for identifying trials
against which electronic searches of databases, such as
MEDLINE are compared.
H
Heterogeneity
In
systematic reviews heterogeneity refers to variability or differences
between studies in the estimates of effects. A distinction
is sometimes made between "statistical heterogeneity"
(differences in the reported effects), "methodological
heterogeneity" (differences in study design) and "clinical
heterogeneity" (differences between studies in key characteristics
of the participants, interventions or outcome measures). Statistical
tests of heterogeneity are used to assess whether the observed
variability in study results (effect
sizes)
is greater than that expected to occur by chance. However, these
tests have low statistical power. See also homogeneity.
Historical
control
A
person, or group of persons, for whom data were collected earlier
than for the group being studied. Because of changes over time
in risks, prognosis, healthcare, etc. there is a large risk
of bias (in studies that use historical controls) due to systematic
differences between the comparison groups.
Homogeneity
In
systematic reviews homogeneity refers to the degree to which
the results of studies included in a review are similar. "Clinical
homogeneity" means that, in trials included in a review,
the participants, interventions and outcome measures are similar
or comparable. Studies are considered "statistically homogeneous"
if their results vary no more than might be expected by the
play of chance. See heterogeneity.
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