Hello Rich,
Thank you for you response. It gave me many good points to think about…it is been seven years since I completed a MS Thesis whereby I was using logistic and
linear regressions without a second thought. The regional aspect of the formula for example doesn’t apply to all regions (i.e., branches are basically located in 4 separate counties in
Let me declare I’m not a statistician although my boss is and has 40 years of Direct Marketing experience. He was tasked with developing a Mortgage Model, so
we can determine what variables best predict what type of members may apply for a mortgage. He told me to use the stepwise method. But I’ll have to investigate this method as you recommended.
To highlight the nature of the IV regressed on the dichotomously coded Mortgage variable; I used a binary (0, 1) or (0=No, 1=Yes) to represent if a customer
had a current mortgage instead of the mortgage balance range of (0 to 1,536,757) on 3.3% of the cases or 12,307. The independent variables used consisted of ordinal and interval/ratio data. Basic demographic variables were dummy coded; for example male
and female were separated out into there own variables (0 = no, 1 = yes). Some of the continuous variables were fico score, age (continuous) and other products. The products were dummy coded as well (0 = no participation, 1 = participation).
I first used the entire sample or universe of cases. Then I used a 27% random sample (using SPSS’s probability algorithm in V. 19) and applied it to the full
sample and scored the data set using the regression equation to create the gain chart.
What would you recommend in terms what “Method of regression (Enter, Stepwise, Remove Forward, Backwards) to use? Or if Mortgage Bal should be used instead
of binary variables due to the fact I’m using linear regression models.
Thank you in advance for any further comments,
Quentin Zavala, MS
Quentin Zavala
SchoolsFirst Federal Credit Union
Business Analyst, Research and Analytics
714-258-4000 ext 8601
qzavala[hidden email]
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