Internal and external views of Testing
Inferences are said to possess
internal validity if a causal relation between two variables is properly
demonstrated. A causal inference may be based on a relation when three criteria
are satisfied:
1.
the "cause" precedes the "effect" in time
(temporal precedence),
2.
the "cause" and the "effect" are related
(covariation), and
3.
there are no plausible alternative explanations for the observed
covariation (nonspuriousness)
In scientific experimental
settings, researchers often manipulate a variable (the independent variable)
to see what effect it has on a second variable (the dependent variable)] For example, a researcher
might, for different experimental groups, manipulate the dosage of a particular
drug between groups to see what effect it has on health. In this example, the
researcher wants to make a causal inference, namely, that different doses of
the drug may be held responsible for
observed changes or differences. When the researcher may confidently attribute
the observed changes or differences in the dependent variable to the independent
variable, and when he can rule out other explanations (or rival hypotheses), then his causal inference is said to be
internally valid
In many cases, however, the magnitude
of effects found in the dependent variable may not just depend on
·
variations in the independent variable,
·
the power of the instruments and statistical procedures used
to measure and detect the effects, and
·
the choice of statistical methods (see: Statistical conclusion
validity).
Rather, a number of variables
or circumstances uncontrolled for (or uncontrollable) may lead to additional or
alternative explanations (a) for the effects found and/or (b) for the magnitude
of the effects found. Internal validity, therefore, is more a matter of degree
than of either-or, and that is exactly why research designs other than true
experiments may also yield results with a high degree of internal validity.
In order to allow for
inferences with a high degree of internal validity, precautions may be taken
during the design of the scientific study. As a rule of thumb, conclusions
based on correlations or associations may only allow for lesser degrees of
internal validity than conclusions drawn on the basis of direct manipulation of
the independent variable. And, when viewed only from the perspective of
Internal Validity, highly controlled true experimental designs (i.e. with
random selection, random assignment to either the control or experimental
groups, reliable instruments, reliable manipulation processes, and safeguards
against confounding factors) may be the "gold standard" of scientific
research. By contrast, however, the very strategies employed to control these
factors may also limit the generalizability or External Validity of the
findings.
External validity is the validity of generalized (causal)
inferences in scientific research, usually based on experiments as experimental validity. In other words, it is
the extent to which the results of a study can be generalized to other
situations and to other people For example, inferences based on comparative
psychotherapy studies often employ specific samples (e.g. volunteers, highly
depressed, no comorbidity).
If psychotherapy is found
effective for these sample patients, will it also be effective for
non-volunteers or the mildly depressed or patients with concurrent other
disorders?
·
Situation: All situational specifics (e.g. treatment conditions,
time, location, lighting, noise, treatment administration, investigator,
timing, scope and extent of measurement, etc. etc.) of a study potentially limit
generalizability.
·
Pre-test effects: If cause-effect relationships can only be found
when pre-tests are carried out, then this also limits the generality of the
findings.
·
Post-test effects: If cause-effect relationships can only be found
when post-tests are carried out, then this also limits the generality of the
findings.
·
Reactivity (placebo, novelty, and Hawthorne effects): If
cause-effect relationships are found they might not be generalizable to other
settings or situations if the effects found only occurred as an effect of
studying the situation.
·
Rosenthal effects: Inferences about cause-consequence
relationships may not be generalizable to other investigators or researchers.
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