department of cognitive science michael j. kalsher adv. experimental methods & statistics psyc...

Department of Cognitive Science

Michael J. Kalsher

Adv. Experimental Methods & Statistics

PSYC 4310 / COGS 6310

Dummy Coding

1PSYC 4310/6310 Advanced Experimental Methods and Statistics © 2011, Michael Kalsher

PSYC 4310/6310 Advanced Experimental Methods and Statistics © 2011, Michael Kalsher

Dummy Coding: What is it?

• Linear regression works over score level variables (e.g. age; income level; weight, etc.)

• But … not all data are score level:– Sex (male vs. female)– Location (RPI vs. Sage vs. HVCC)– Political affiliation (Democrat, Independent, Republican)

• Dummy coding is a way of representing groups of people using only zeros and ones.


Nominal values as binary numbers

• Binary: 0 = off/absent, 1 = on/present

• Can treat nominal variables as presence (or absence) of features Example:

Presence of maleness /presence of femaleness


Creating Dummy Variables• Dummy coding produces “dummy

variables” equal to N-1 (where N = the original number of categories).

• Consider Political Affiliation: Democrat, Independent, Republican– Here there are three categories that will be recoded into

two dummy coded variables

• Steps:– 1. Assign one category as the “Baseline” group– 2. Create two variables representing the other groups: X

and Y– 3. X=1 if in group X; Y=1 if in group Y; both are 0 if in

baseline group


Example: Presidential RatingsDuring class in the Fall 2010 semester, students in PSYC 4310 were asked to indicate:– Rating of President Obama’s performance (1=Strongly

Disapprove; 5=Strongly Approval)

– Party affiliation (1=Democrat; 2=Independent; 3=Republican)

– One approach is to analyze the data using an “experimental technique” such as ANOVA.

– But suppose you wanted to analyze in the context of regression with several other “predictor” variables?

– Another approach is to recode Party Affiliation into Dummy Coded Variables so that we can use this variable in a regression analysis.

5

PSYC 4310/6310 Advanced Experimental Methods and Statistics © 2011, Michael Kalsher 6

President’s performance ratings as a function of

party affiliation.

KeyAffiliation:1 = Democrat2= Independent3= Republican

Rating:1= Poor Performance5 = Great Performance


#1: Select the Variable

#2: Name the 1st Dummy Code, then click on “Change”


Next, Click on “Old and New Values”


In this step, we want all “Democrats” to get a code of “1” and everyone else to get a code of “0”. To do this, we type in “1” for the “Old Value” and “1” for the “New Value”, then click on “Add”.

Add “1” hereAdd “1” here


#2

#3

#1

Next, we need to change the remaining groups to have a value of “0” for the first dummy variable. 1. Select “All other values”, 2. type in “0” adjacent to “Value” in the section labeled “New Value”. 3. Click on “Add”. 4. Click on “Continue”

#4


You should now be back at the main “Recode into Different Variables” dialogue box, then click “Ok”. Check the Data View and you will see the “Democrat Dummy Code”


1. Click “Reset” 2. Name the 2nd

Dummy Code (Republican).

3. Click on “Change”.

4. Click on “Old and New Values”


After changing the “Old Value” of Republicans (3) to the “New Value” (1) and “All other values” to “0”, click on “Continue”, which takes you back to the main dialogue box, then click “Ok”. Check the Data View and you will see the “Republican Dummy Code”


The Data View now shows the two columns of the recoded “Democrat” and “Republican” Dummy Codes.


Now we can run the regression analysis using the Dummy Coded variables as predictors and Rating as the DV

department of cognitive science michael j. kalsher adv. experimental methods & statistics psyc...

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