Date: Mon, 21 Jan 2008 15:29:44 -0800
Reply-To: Abdus Salam <email@example.com>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Abdus Salam <firstname.lastname@example.org>
Subject: Which method would be more robust.
Content-Type: text/plain; charset=us-ascii
Dear expert listers,
I have a dataset where the variables are overall satisfaction(7 point scale),Value for money comparison(7 Point Scale) and also a variable with 13 attributes which contains Description ratings(7 point scale),One variable called attribute(7 point scale),Rating performance(7 Point Scale),Rating quality of Communication (7 point scale).
Now client needs a robust Driver analysis based on these variable. What I think first
1) I have to make all the variables as Binary variable as I need to know only Top 2 Box performance.
2) To check the strength of relationship - I want to do correlation with overall satisfaction to all other variables.
To check which factor drives the overall satisfaction very well:
1) I have to make all the variables as Binary variable.
2) Then for removing the multicolinearity I have to do factor analysis on the base of 13 attributes.
3) After getting a good factor solution -taking those factor solution and other 4 variables as an independent variable; overall satisfaction as a dependent variable.
4) Finally wants to run a linear regression analysis with enter method.
Can anyone suggest me which one would be more robust method?
Be a better friend, newshound, and
know-it-all with Yahoo! Mobile. Try it now. http://mobile.yahoo.com/;_ylt=Ahu06i62sR8HDtDypao8Wcj9tAcJ
To manage your subscription to SPSSX-L, send a message to
LISTSERV@LISTSERV.UGA.EDU (not to SPSSX-L), with no body text except the
command. To leave the list, send the command
For a list of commands to manage subscriptions, send the command