Creating a logit model to run logistic regression?

hello, I am trying to construct a logit model to estimate the probability but I'm having trouble in doing so.


I know how to do the right hand side (RHS) for a logit model, but I am having trouble with the left hand side (LHS) of the equation.





am I correct in saying that a logistic function looks like this: Pi = 1/1+e^-(z) where in my case


z= beta + beta1(residence) + beta2(sex) + beta3(education) + u-error term





Is this what the logit model looks:


Pi = E(Y=1|Xi) = 1/1 + e -(z) ... or is it


Li = ln(Pi/1-Pi) = Zi = beta + beta1(residence) + beta2(sex) + beta3(education) + u-error term





in my case, I have binary outcome variable namely, whether a person suffers from heart disease or not... my independent variables are residence (1= rural or 0 =urban), sex (m=1 or f=0), education (primary=1, secondary=2 and highereduc=3).. can someone please show me how to write an actual logit model to predict the probability whether a person will suffer from heart disease.. for the left hand side, what should the exact notation look like? i hope this makes sense.. any help will be greatly appreciated.. thanks


Mike|||Logistic Regression: Statnotes, from North Carolina State ...


Logistic regression has many analogies to OLS regression: logit ..... The logistic regression model is run against the dependent for the full model with ...... After this, PASW/SPSS will automatically create dummy variables based on the