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Practicing with SPSS

 

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.

 

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

 

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