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**
Practicing with SPSS **

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**
Independent vs. Dependent Variables and
Categorical vs. Continuous Variables**

·
__
Independent Variable (IV)__
→ The variable that is controlled and manipulated by the experimenter; the
‘cause.’

·
__
Dependent Variable (DV)__
→ The variable that is the response measured by the experimenter; the ‘effect.’

Although there is overlap in meanings, the distinction between independent vs.
dependent variables and categorical vs. continuous/scaled variables is slightly
different.

For statistics such as the__ t__ test and ANOVA (__F__ test), Independent
Variables are Categorical and Dependent Variables are Continuous.

__
__

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Categorical Variables __
→ Just as the name implies, these variables can be thought of as categories, of
which there are usually 2 to 3 groups.

Examples within NHIS:

§
Sex – there are no range of sexes, you are either male or female

§
“…Ever been told …has ADHD?” – a ‘yes’ or ‘no’ question; you either have been
told your child has ADHD or he has not.

§
“..Has Senility/Dementia/Alzheimer’s…” - once again, you either fall into the
*category* of having one of these
issues, or you do not.

§
Family income (ab_bl20K)-this is a categorical measure of income since it places
family income within one of two categories (above vs. below 20 K)

§
ANXDEPYR “Frequently depressed, past 12 months.” This is a categorical measure
of depression. You were either depressed or not.

__
Continuous/Scaled Variables __
→ A continuous or scaled variable will have an ordered range of values to be
measured. Unlike categorical variables, these should have at least several
values that might vary from larger to smaller or vice versa.

Examples within NHIS (including created scales):

§
“How difficult is it for you to participate in social activities” – this
variable is measured on a scale from 1 to 5 (with 1 meaning unable to
participate and 5 meaning no difficulty at all).

§
“Is ---often unhappy, depressed, tearful, past 6 months.”
This is scale that has 3 points varying from 1. Not true 2. Somewhat true
3. Certainly true.

§
“Number of Persons in the Family” – Again, this is a continuous scale which
could range from a few to many family members.

§
A student-created Depression Scale – Many of you will create some form of
Depression Scale in your work. This could be based on several items (e.g., “Felt
Sad,” “Felt Hopeless”, “Felt Worthless”) each of which was a scale 1.-all the
time, 2. Most of the time….5. None of the time
Combining these 3 items together, you would have a new scale with scores
that could range from a minimum of 3 (severely depressed) to a maximum of 15
(not at all depressed) The new scale is a continuous variable.

§
“Rat_cat” Ratio of fam inc to poverty threshold.
This is a scaled measure of family income that has been recoded from
dollars to a scale ranging from 1 (very
low income) thru 14 (very high income).

Unlike the __t__ test and ANOVA, with statistics such as correlations, you
will have two continuous/scaled variables to determine if there is an
association between them.

**
Putting it all together:**

If you wanted to examine whether or not having ADHD was linked to feelings of
depression, your **Categorical IV**
would be **whether or not a child has ADHD**
and your **Scaled DV** would be some
sort of **Depression Scale**

o
Once again, **whether or not a child has
ADHD** is **categorical** (yes/no) and
the **Depression Scale** is, of course,
a **scale** or
**range** to measure the child’s level
of depression.

o If you want to determine if there is a relationship between social activities participation and income, you could calculate a correlation between the “Rat_cat” the continuous measure of family income, and the Social Activities item which was scored from 1 through 5