leave open the possibility that there are other causes and factors affecting the
result seen in the DV.Control, Manipulation, and Bias
Control refers to the ability to manipulate, regulate, or statistically adjust for
the multitude of factors that can influence the DV. Control is necessary to
make assertions about cause and effect. Manipulation is an important aspect
of control in experimental designs and refers to the ability of researchers to
control the IV. The IV is considered to be the intervention, or treatment, that is
being tested in an experimental study. The intervention may be physiological,
psychological, behavioral, educational, or a combination of these.
For example, a researcher hypothesizes that educational interventions will
result in increased condom use among sexually active teens and wants to test a
newly developed computer-based intervention. The researcher manipulates the
IV, the educational intervention, by determining what content will be included,
how it will be delivered, in what environment it will be delivered, and who will
receive it. The researcher in this example would then compare preintervention
condom usage with postintervention usage. The researcher also could compare
the difference in condom usage between the intervention group and a control
group. In health-related experimental designs, the control group of subjects
usually receives the standard of care but does not get the intervention. The
control group of teens, in this example, would participate in the traditional sex
education classes offered in their school but would not be able to access the
computer-based program. However, because factors other than education can
affect condom use, the researcher also needs to control for these extraneous
or confounding factors.
Extraneous variables are those that confound, or confuse, the effect of the
IV on the DV. Researchers can control for extraneous variables through careful
selection of participants, use of consistent data collection procedures, randomiza-
tion, or use of certain statistical tests. Examples of confounding variables in the
example might be the age of the teen, religious beliefs, self-efficacy for resisting
peer pressure, cost of condoms, ease of purchasing them, and whether or not
the teen has a current sexual partner. Without careful control of extraneous
variables, bias can be introduced into the study.
Bias results when extraneous variables influence and distort the relationship
between the IV and the DV so that the findings are not really reflecting the
true relationship. For example, if the study included students without a current
sexual partner, it would be highly likely that the intervention would result in
no significant difference in condom use. This lack of difference might be attrib-
uted to the intervention being ineffective when it is actually caused by the factKEY TERMS
control: Ability
to manipulate,
regulate, or
statistically adjust
for factors that
can affect the
dependent variable
manipulation:
The ability of
researchers
to control the
independent
variable
extraneous
variables: Factors
that interfere with
the relationship
between the
independent
and dependent
variables;
confounding
variable; Z variable
bias: When
extraneous
variables influence
the relationship
between the
independent
and dependent
variables152 CHAPTER 6 Key Principles of Quantitative Designs