SPSS Project

#1
Hi there,

I was hoping someone could help me. I'm doing a project on promotions at work.

I have three variables, scores on a job performance test (continuos variable) , promotion decision (yes or no) and experience of job performance tester (more than five years or less than five years).

In SPSS, I have coded the promotion decision variable as 1 for yes and 2 for no and used a similar coding for the tester experience variable.

My research question is are job performance and promotion decisions related and if they are, is this relationship affected the experience of the job performance tester?

To test the first part of my reaserch question, I'm just going to do a simple bivariate correlation using SPSS. The problem I'm facing is that I dont know how to test the second part of my research question i.e. does tester experience have an effect on the relationship.

Does anybody have any ideas ? I've been told I need to do a regression, but not too familiar with these.

Any help would be greatly appreciated.
 

JohnM

TS Contributor
#2
The variables should be all analyzed together in a logistic regression model (to see if the independent variables are correlated with a dichotomous (yes/no) dependent variable, and if they interact with one another).

In your study, the independent variables are:
(a) job performance test
(b) experience of job performance tester

The dependent variable is:
(1) promotion decision

Basically, the logistic regression method will tell you if changing one or both of the independent variables has a significant effect on the dependent variable, i.e.,

Do certain scores on the job performance test change the probability of a "yes" on the promotion decision? Does the experience of the tester affect this "relationship" or correlation (i.e., does the probability of a "yes" decision, dependent on a test score, also change, based on the tester's experience?).

The following links are good sources of information on logistic regression:

http://personal.ecu.edu/whiteheadj/data/logit/

http://www2.chass.ncsu.edu/garson/pa765/logistic.htm

http://luna.cas.usf.edu/~mbrannic/files/regression/Logistic.html

Good luck,
John