logarithmic regression excel data analysis

#Logarithmic regression excel data analysis how to

Other than that, it pretty much seems the same as my situation, with the exeption that I have 3 binary class predictors, and 3 numeric predictors. I started by altering the data a bit to match my scenario by changing 'M' and 'F' to 0 and 1, and also to change 'No' and 'Yes' to 0 and 1. I looked at the Neuralgia example 51.2 avalailable at. Reeza, I took your advice, and started over with a documented example I understood.

#Logarithmic regression excel data analysis how to

So, while it helps me to see the predicted probability of each observation in my dataset, I am needing to be able to figure out how to calculate that probability by hand, so I can give the mainframers a formula. They have, in a DB2 table, all of the variables in my SAS model, but they need a formula to calculate the probability any account will end up in collections. The system housing the data is a DB2 mainframe, and the DB2 programmers need to have a formula to sort the bad accounts having the highest probability of ending up in collections. Using historical account data, with a binary response, two binary predictors, and several interval predictors, I need to come up with a formula to predict which accounts will ultimately not pay, and end up being sent to collections. In the mean time, perhaps an explanation of what I am needing to do would help.

I ran my model with the output as you have shown above, and I am googling madly to find help in deciphering the results.

Reeza, thank you so much for continuing to answer my newbie questions. The rest of the variables are numeric, and should be treated as such. The two class variables are binary, having either a 1 or 0. However, the parameter estimate of -0.1582 seems to me to indicate this is not the case. If I am trying to predict accounts that will go to collections, it seems to me if this condition were true for any customer, they would be more likely to go to collections if they have already done so in the past. For example, variable 'bad_debt_at_connection' indicates a customer opened a new account when they had an account that at some point in the past went to a collection agency for non-payment. My question is, how does the 'Exp(Est)' affect the parameter estimate with respect to putting it in the regression forumula? I have attached a copy of my log, and sure would appreciate it if anyone would be willing to put some experienced eyes on it. However, if I use this methodology, I seem to get some results that are counter intuitive. Thinking back to multiple regression (and it was several years ago), I could simply take the intercept + (estimate1*variable1) + (extimateN*variableN). I am trying to create my regression forumula from the estimates output from proc logistic.