With multiple regression, is it necessary to recode independent variables that are measured using Likert Scale responses into dummy variables (with values of 1 or 0)?
Background: I am testing hypotheses concerning consumer purchasing patterns. A survey was used to collect the necessary data for the various independent variables. The questions and subsequently the data collected is structured according to five point Likert Scale responses (eg. (1) no importance to (5) utmost importance; e.g. (1) strongly agree to (5) strongly disagree).
Dependent Variable: Have you purchased products from ACME retailer?
Possible responses: (1) yes, (0) no
There are several independent variables, this is a sample of just one: PRICE.
Survey question: How important was price in your purchase consideration? Possible responses:
(1) no importance
(2) little importance
(3) moderate importance
(4) great importance
(5) utmost importance
If it is necessary to recode using dummy variables, it is my understanding that 4 dummy variables are needed, with one reference category.
Dummy 1: no importance=1, otherwise=0
Dummy 2: little importance=1, otherwise=0
Dummy 3: moderate importance=1, otherwise=0
Dummy 4: great importance=1, otherwise=0
With SPSS (version 16), can this be done by clicking “transform”, “recode into new variable” and then creating the above dummy variables?
I am pretty confident in running the regression and then interpreting the results, but I am having difficulty in actually coding the data for multiple regression. Any assistance would be greatly appreciated.