Independent and dependent variables

PRS530D

1. Independent
and
Dependent

Variables
Variables
–
things
that
we

measure,
control,
or
manipulate

in
research.

2. Independent
Variables

Differing
conditions
or
characteristics
that
are
manipulated
or

under
control
in
the
analysis

(also
referred
to
as
predictor
or

causal
variables).


Graphed
on
the
X-axis
















































Should
be
put
in
the
rows
of
tables


They
are
the

X
variables
in
equations.

Y=1.8
*
X+32
F=1.8
*
C+32
F
=
dependent
or
outcome
variable
C
=
independent
or
predictor
variable
Changes
in
F
depend
on
changes
in
C

3. Dependent
Variables

Affected
factors,
attributes,
or
characteristics
not
under

control
in
the
analysis

(also
referred
to
as
response
or

outcome
variables).


Variables
depend
on
what
the
subject
will
do
in
response

Dependent
variables
are
graphed
on
the
Y-axis

Should
be
put

in
the
columns
of
tables


They
are
the
Y
variables
in
equations.
Y=(X-32)/1.8
C=(F-32)/1.8
C=dependent
or
outcome
variable
F
=
independent
or
predictor
variable

4. Independent and dependent variables are defined within the
research context, a dependent variable in one research
setting may be an independent variable within another.
Example using Social cognitive Theory as our theoretical orientation and variables from the
BRFSS dataset.
Study question # 1 - Does ‘access to health care’ and feelings about ‘having
children’ predict ‘intake of folic acid’?

BEHAVIOR
(# 1 [OM] folic acid - DV)
ENVIRONMENT INDIVIDUAL
(# 3.1 health care coverage - IV) (#18.4 having children- IV)

5. Study question # 2 - Does ‘access to health care’ and ‘intake
of folic acid’ predict ‘tobacco use’?
BEHAVIOR
(# 7.2 tobacco use - DV)

ENVIRONMENT INDIVIDUAL
(# 3.1 health care coverage - IV) (# 1 [OM] folic acid - IV)
In study question # 1 ‘intake of folic acid’ was our dependent variable
(DV) while in study question # 2 we used ‘intake of folic acid’ as one
of our independent variables (IVs).

6. Levels of Measurement
Variables differ in “how well” they
can be measured, in how much
measurable information their
measurement scale can provide.

7. Nominal

Allow
for
only
qualitative
classification

Can
be
measured
only
in
terms
of
whether
the

individual
items
belong
to
some
distinctively

different
categories.



For
example…all
we
can
say
is
that
2

individuals
are
different
in
terms
of
Variable
A

(one
is
female
and
one
is
male)
but
we
cannot

say
which
one
“has
more”
of
the
quality

represented
by
the
variable.



Common
variables:
Gender,
Race,
Color,

City,
etc.

8. Ordinal

Ordinal
variables
allow
us
to
rank
order
the
items
we

measure
in
terms
of
which
has
less
and
which
has

more
of
the
quality
represented
by
the
variable,
but

still
they
do
not
allow
us
to
say
“how
much
more”.



Example…we
know
that
upper-middle
class
is
higher

than
middle
but
we
cannot
say
how
much
higher.



Which
gives
you
less
information?
Nominal
or
ordinal

variables?



Nominal

Can
we
say
how
much
less
information
it
gives?



No…so
this
is
an
example
of
what
type
of
variable?



Ordinal

9. Interval

Allow
us
not
only
to
rank
order
the
items
that

are
measured,
but
also
to
quantify
and

compare
the
sizes
of
differences
between

them.



Example…temperature
is
measured
on
an

interval
scale.

We
can
say
that
50
degrees
is

10
degrees
higher
than
40
degrees
and
that

an
increase
from
50-70
is
twice
as
much
as

an
increase
from
40-50.

10. Ratio

Ratio variables are similar to interval variables;
in addition to all the properties of interval
variables, they feature an identifiable absolute
zero point.

Now I can say on a Kelvin temperature scale that
200 degrees is higher than 100 degrees and that it
is twice as high.
*A lot of analysis procedures do no distinguish
between ratio and interval properties of a
measurement scale.

11. Categorical
vs.
Continuous

Data
Data can be continuous or categorical (discrete)

12. Continuous Data

A set of data is said to be continuous if the
values / observations belonging to it may take
on any value within a finite or infinite interval.

You can count, order and measure continuous
data.

For example, height; weight; temperature; the
time required to run a mile.

13. •Continuous variables are measured on an:
–ordinal scale/rank-level – example - on a five-point rating scale measuring
attitudes toward abortion, the difference between a rating of 2 and a rating
of 3 may not represent the same difference as the difference between a
rating of 4 and a rating of 5
–Interval – example - if depression were measured on an interval scale, then
a difference between a score of 10 and a score of 11 would represent the
same difference in anxiety as would a difference between a score of 50 and
a score of 51
–ratio scale – example- Kelvin scale of temperature. This scale has an
absolute zero. Thus, a temperature of 300 Kelvin is twice as high as a
temperature of 150 Kelvin.
Continuous dependent variables are described with measures of central
tendency (means, medians, modes), and dispersion (variance,
standard deviation, range).

14. Categorical Data

Represents a set of discrete events, such as
groups, decisions, or anything else that can be
classified into categories;

A categorical variable may also consist of more than
two categories. For example, a person's major at
RSPH can be categorized as BSHE, EPI, IH, etc.

A categorical variable can be ordered or unordered.
For instance, a person's level of schooling is an
ordered variable; a person's sex is an unordered
variable.

15. Qualitative Data
•Categorical Data are measured on a:
–Nominal Scale - (i.e. gender, race, religion, state of
residence, make of car)
•Dichotomous - dichotomous (i.e. on/off, alive/dead, yes/no,
male/female)
–Ordinal/rank-order – (i.e. order of participation, arrival
for 4 people, class standing)
Categorical and dichotomous dependent variables are
described with frequencies and percentages.

16. Continuous or Categorical
•1)
The
number
of
people
infected
with
HIV.
Categorical
-
The
number
of
people
infected
must
be
a
whole
number.

•2)
The
temperature
at
which
Salmonella
is
killed.
Continuous
-
The
temperature
can
take
on
infinitely
many
values
(any

decimal
is
possible).
•3)
The
number
of
suicides
committed
by
teenagers.
Categorical
-
The
number
of
suicides
must
be
a
whole
number.

•4)
The
number
of
teenage
pregnancies.
Categorical
-
The
number
of
suicides
must
be
a
whole
number.
•5)
The
time
it
takes
for
a
smoker
to
develop
emphysema
Continuous.
The
amount
of
time
can
take
on
infinitely
many
values
(any

decimal
is
possible).




6)
The
production
of
fruits
and
vegetables
by
weight.

Continuous.
The
weight
of
the
fruits
and
vegetables
can
take
on
infinitely

many
values
(any
decimal
is
possible).


17. Categorize the following variables as being qualitative
or quantitative, categorical or continuous, and specify
the level of measurement:

Response time:
Quantitative
Continuous
Interval

Rating of job
satisfaction:
Quantitative
Continuous
Ordinal

Favorite color:
Qualitative
Discrete
Nominal

Occupation
aspired
to:

(Qualitative
as
it
stands

but

could
be
considered


quantitative
if
rated
in

terms

of
expected

income,
prestige

etc.)








Discrete








Nominal

Number
of
words

remembered:
Quantitative
Continuous




Interval