//  Task 1 routine setup
 
    capture log close 
    set more off 
    estimates clear 
   
    log using cda04b-ex4.log, replace text
    version 9.2
    set scheme s2mono 
    
//  pgm:        cda04b-ex4.do
//  task:       4 - Binary Regression - Excercise
//  project:    CDA Lab Guide
//  author:     your name
//  date:       today's date

    use science3, clear

//  Task 2: Keep jobclass, female, enrol and phd, Examine the variables
//  drop missing cases.

//  Step 2.1 keep the four variables and summarize them.


//  Step 2.2 drop missing cases


//  Step 2.3 verify the last step.


//  Task 3: Create a binary dependent variable hijob from jobclass.
//
//      hijob=1 if jobclass>2, else 0. Missing values remain missing.
//
//  Verify your transformation. Add variable and values labels.

//  Step 3.1 Create a binary dependent variable hijob, from jobclass.


//  Step 3.2 Add variable and values labels.


//  Step 3.3 verify variable creation


//  Task 4: Estimate a probit of hijob on female, enrol and phd.
//  List coefficients and compute predict probabilities for each observation.
//  Label the variables created by predict.

//  Step 4.1 Estimate the probit model.


//  Step 4.2 List coefficients.


//  Step 4.3 Predict probabilities.


//  Step 4.4 Label the variable created by predict.


//  Task 5: Do the same with a logit model.

//  Step 5.1 Estimate the logit model.


//  List coefficients.


//  Step 5.3 Predict probabilities.


//  Step 5.4 Label the variable created by predict


//  Task 6: Compare logit and probit predictions with a graph.


//  Task 7: Interpret the logit regression


//  Task 7a: compute predicted probability with variables at their means


//  Task 7b: predicted probability for males with other variables at mean


//  Task 7c: for females


//  Task 7d: differences for males and females


//  Task 7e: discrete and marginal change


//  Task 7f: discrete and marginal change for females with other
//  variables at the mean.


//  Task 7g: compute predictions as phd varies, first for feamle=1
//  with other variables held at mean; then for males.


//  Task 8: [Optional] Compare the logit and probit coefficients.
//  a) Why are the unstandardized coefficients so different?
//  b) How different are they?
//  c) Why are the standardized coefficients similar?
//  d) Why aren't they exactly the same?

/*  Type your answer here

*/

//  Task 9: [Optional] Use foreach to make transformations.
//
//      Example: There are 3 variables (jobclass, felclass, phdclass)
//      that have the similar coding. Suppose that we want to turn all
//      of these variables into dummy variables with 3 and 4 recoded to 1
//      and 1 and 2 recoded to 0. Then run a logit regressions.

//  Method 1: Without looping

    use science3, clear
    
//  Method 2: With looping using the foreach command

    use science3, clear
    
log close
exit