Transcript VARIABLES
VARIABLES
Concepts that are operationalized
(things that vary)
Because things vary, research is
conducted
How or why things vary
How differences in one variable are related
to another
Types of Variables
INDEPENDENT/DEPENDENT
CRITERION/OUTCOME
DICHOTOMOUS
ATTRIBUTE/ACTIVE
EXTRANEOUS
INTERVENING
CONFOUNDING
UNCONTROLLED
Independent Variable
The presumed cause
The manipulated variable in an experiment
The treatment
The “active” variable
The Dependent Variable
The variable that the researcher is
interested in understanding, explaining or
predicting
The outcome variable
The “critereon variable”
Independent /Dependent
Variables
Variables are not inherently one kind or the
other, you must look at them in the context
of the study.
Causality is not necessarily implied, rather
the directionality of the influence
independent variable changes in the
dependent variable
Criterion variable
The dependent variable--the outcome
Dichotomous variable
A variable having two (and only two) values
e.g., male, female
smoker, nonsmoker
alive, dead
Attribute and Active variables
Attribute variable--preexisting
characteristic which researcher simply
observes and measures, e.g. bloodtype,
medical diagnosis, etc.
Active Variable--researcher creates or
manipulates this, e.g. metrology class,
experimental drug, etc.
Variables to be controlled for:
Extraneous Variables which have an
unwanted or irrelevant effect on
Intervening
the
dependent
variable
under
Confounding
investigation. The kind of
Uncontrolled
independent variable which may
unexpectedly alter the results of
the study
CONTROLLING
EXTRANEOUS VARIABLES
1.
HOMOGENEITY/ELIMINATION OF
VARIABLE
2. INCLUDE IN DESIGN
3. MATCHING
4. STATISTICAL CONTROL
5. REPEATED MEASURES
6. RANDOMIZATION
Homogenity, Elimination of Var.
Use subjects who are homogeneous for the
variable which is suspected may have a
confounding effect on the results of the
study.
eg. If gender or age is thought to be a
confounding factor use all one gender or
all one age cohort as subjects, thus
eliminating this as a factor
Include in the design
Include the presumed intervening variable
in the design of the study.
For example: If age is a factor include
several age groups in the design and
analyze the results separately for each
group.
Matching
Match subject in two groups on relevant
characteristics such as age, gender,
diagnosis.
Statistical Control
After study is completed perform an
analysis of covariance to determine if the
presumed extraneous variable had an
effecrt.
Repeated Measures
If the variable is subject to fluxuation,
measure several times under several
different circumstances.
Randomization
Overall, the best way to control extraneous
variables.
Random assignment to groups means that
all possible extraneous variables should
be spread evenly between groups.