Multinomial logistic regression I would like to get help from an expert or anyone who knows about this.  As a beginner in SPSS, I've googled the steps to do multinomial regression.  I've decide to use multinomial because from what I googled and understood, binomial is for situations that only have 2 categories like yes or no, which you could code 0 for yes and 1 for no.  This is what I understand if you choose to use binomial. 
My situation is I have a set of questionnaires that use more than 2 answers.  For example, level of income: 1. $2000, 2. $3000, 3. $4000, 4. $5000.  That is the kind of question I have.  So, obviously I choose to use multinomial regression.
My IV's are 1) social capital, 2) training, 3) credit/loan; and my DV is effectiveness which can be measured by 1) income, 2) saving, 3) repayment rate.  
In my questionnaire, I only have two kind of question which "yes or no" and choose answer like above mention "1 or 2 or 3 or 4."  So my questions are:


*

*Did I choose the right regression to use, that is multinomial, or do I have to use binomial?  

*If it's multinomial, I need help with the steps like do I have to calculate all my DV questions and transform them into one, which will make new "item" in SPSS columns, then put it in the dependent column of multinomial regression?  Because I have approximately 15 questions to measure my DV.  Then in the factors columns what did I put?  Every question of my IV's (like 30 questions separately) or just the total of the 30 questions?  And what should I put on covariates?  


http://sdrv.ms/JtOHu3
above is my questionaire sample link.
income level, savings and repayment is to measure my dv ~ effectiveness of microfinance.
other is my iv, that is credit/capital , training and social capital.
feel free to improve my questionaire if you like.
 A: I recommend you delay the question of which sort of model to use in relating your DV to your IVs.  First, you need to tackle scale development and see what sort of DV you arrive at.  Maybe it'll end up something measured on an interval scale that is suitable for a linear regression. 
As Peter has said, combining variables that could be components of your ultimate DV could be challenging since they're measured on different scales, but it can be done.  You'll need to put in careful thought  about how to combine them in a way that preserves the weights you believe each one deserves.  I don't have an answer about that to offer you, but I can suggest a few authors you might read:  Robert Devellis, Paul Spector, and Lewis Aiken.  Or there are probably lots of websites that deal with scale development and with the reliability and validity of scales one forms based on several "ingredients."  If you search for terms like these and add the qualifier "different scales" you'll probably find good sources.
