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STATA analysis

simple task in stata anaysis 

Homework 5: Non-Linear Regression

(Due: 8:50am CST, Nov 29, 2024)

Let’s suppose you are interested in how life satisfaction is associated with internet use, age, gender, and marital status (i.e., married vs. non-married) for older adults (or how older adults’ internet use, age, gender, and marital status influence life satisfaction).

You set up your research question in the following model:

(Eq. 1)

To examine your research question empirically, you figured out that the Health and Retirement Study (HRS) is the secondary data that best suits your goal. Thus, you want to work with 2018 HRS core data. 

        
1. Please go to the following web: 


        
2. Download the relevant files (e.g., h18sta.zip files… ).


        
3. In 
            Section LB: Leave Behind Questionnaires (Respondent), you want to take the information about life satisfaction. Use the relevant dta file and keep only three variables: 
            hhid, pn, and QLB002C. 
        


        
        
HHID         HOUSEHOLD IDENTIFICATION NUMBER


Section: LB  Level: Respondent      Type: Character  Width: 6   Decimals: 0


        
...........................................................................


  17146           010003-959738. Household Identification Number


        
            
        




        



        
PN           RESPONDENT PERSON IDENTIFICATION NUMBER


Section: LB  Level: Respondent      Type: Character  Width: 3   Decimals: 0


        



        
...........................................................................


          9738         010. Person Identifier


           654         011. Person Identifier


            32         012. Person Identifier


             1         013. Person Identifier


          5480         020. Person Identifier


           180         021. Person Identifier


            21         022. Person Identifier


             1         023. Person Identifier


           353         030. Person Identifier


            44         031. Person Identifier


             3         032. Person Identifier


             1         033. Person Identifier


           586         040. Person Identifier


            47         041. Person Identifier


             4         042. Person Identifier


             1         043. Person Identifier


        



        

        
QLB002C                       Q02C. SATISFIED WITH LIFE


Section: LB  Level: Respondent      Type: Numeric    Width: 1   Decimals: 0


Please say how much you agree or disagree with the following statements. (Mark (X) one box for each line.)


         


         I am satisfied with my life.


        



        
   ....................................................................


           262           1. STRONGLY DISAGREE


           323           2. SOMEWHAT DISAGREE


           348           3. SLIGHTLY DISAGREE


           362           4. NEITHER AGREE OR DISAGREE


           734           5. SLIGHTLY AGREE


          1841           6. SOMEWHAT AGREE


          1774           7. STRONGLY AGREE


         11502       Blank. INAP (Inapplicable); Partial Interview




4. Rename the variable QLB002C to life_sat.  




5. Drop individuals who reported the missing (.) in life_sat variable. 




6. Label the values of life_sat variable


1. STRONGLY DISAGREE


   2. SOMEWHAT DISAGREE


   3. SLIGHTLY DISAGREE


   4. NEITHER AGREE OR DISAGREE


   5. SLIGHTLY AGREE


   6. SOMEWHAT AGREE


   7. STRONGLY AGREE




7. Save the data, temp_lb_2018.dta.




8. In 
            Section W: Event History, Internet Use and Social Security (Respondent), you want to take the information about internet use. Use the relevant dta file and keep only three variables: 
            hhid, pn, and QW303.
        







        
HHID         HOUSEHOLD IDENTIFICATION NUMBER


Section: W   Level: Respondent      Type: Character  Width: 6   Decimals: 0


        



        
 .........................................................................


         17146           010003-959738. Household Identification Number


        



        
        
==========================================================================


            
        




        



        
PN           RESPONDENT PERSON IDENTIFICATION NUMBER


Section: W   Level: Respondent      Type: Character  Width: 3   Decimals: 0


        



        
...........................................................................


          9738         010. Person Identifier


           654         011. Person Identifier


            32         012. Person Identifier


             1         013. Person Identifier


          5480         020. Person Identifier


           180         021. Person Identifier


            21         022. Person Identifier


             1         023. Person Identifier


           353         030. Person Identifier


            44         031. Person Identifier


             3         032. Person Identifier


             1         033. Person Identifier


           586         040. Person Identifier


            47         041. Person Identifier


             4         042. Person Identifier


             1         043. Person Identifier


        



        
QW303        REGULAR USE OF WEB FOR EMAIL


Section: W   Level: Respondent      Type: Numeric    Width: 2   Decimals: 0


         Ref: EventHistory.W303_


        



        
Do you regularly use the Internet (or the World Wide Web) for sending and receiving e-mail or for any other purpose, such as making purchases, searching for information, or making travel reservations?


         User Note:  Interviewer-administered item.


        



        
...........................................................................


            14          -8. Web non-response


         10068           1. YES


          6911           5. NO


             9           8. DK (Don’t Know); NA (Not Ascertained)


            22           9. RF (Refused)


           122       Blank. INAP (Inapplicable); Partial Interview


        



        


        
9. Rename the variable QW303 to internet_use.  


        


        
10. Drop individuals who reported the values -8, 8, and 9 of the “internet_use.”


        


        
11. Replace the value 5 (NO) with 0. 


        


        
12. Save the data, temp_w_2018.dta.


        


        
13. Merge two data files, temp_lb_2018.dta and temp_w_2018.dta.


        


        
14. 
            Keep individuals that are exactly matched (i.e., Keep individuals shown both in the master and using data).
        


        
15. Save the merged data, temp_merged_lb_w_2018.dta.


        


        
16. Please download the 
            h18_trk.dta 
            from Canvas and keep the variables: 
            hhid, pn, qage, gender, and qmarst.
             
        


        


        
        
HHID         HOUSEHOLD IDENTIFICATION NUMBER


Section: W   Level: Respondent      Type: Character  Width: 6   Decimals: 0


        
                010003-959738. Household Identification Number


        
===========================================================================


        
PN           RESPONDENT PERSON IDENTIFICATION NUMBER


Section: W   Level: Respondent      Type: Character  Width: 3   Decimals: 0


        
        
QAGE                     AGE AT 2018 INTERVIEW


         Section: TR    Level: Respondent      Type: Numeric    Width: 3   Decimals: 0


999: Not applicable


GENDER           GENDER


Section: TR  Level: Respondent      Type: Numeric    Width: 1   Decimals: 0


        
...........................................................................


         19180           1.  Male


         24234           2.  Female


           144       Blank.  Unknown


        
        
QMARST       2018 MARITAL STATUS


Section: TR  Level: Respondent      Type: Numeric    Width: 1   Decimals: 0


        
This variable may not be completely consistent with core data. Corrections have been made to this variable based on cross-wave information. See Section 5B1 in the tracker data description for more information.


        
...........................................................................


          9758           1.  Married


          3625           2.  Separated/Divorced


          3024           3.  Widowed


          1343           4.  Never Married


           260           5.  Marital Status Unknown


         25548       Blank.  No core interview from household, or not in sample this wave




17. Rename the variable qage to age. 




18. Drop individuals who reported 999 in the age variable. 




19. Drop individuals who reported missing (.) in the gender variable. 




20. Rename the variable qmarst to marital_st.




21. Drop individuals who reported 5 or missing (.) in the marital_st variable. 




22. Generate an indicator variable for married (i.e., i_married) and code 1 if individuals reported 1 in the marital_st variable and 0 if individuals reported 2, 3, or 4 in the marital_st variable. 




23. Save the data, temp_trk_2018.dta.




24. Merge two data files, temp_trk_2018.dta and temp_merged_lb_w_2018.dta.




25. Keep individuals that are exactly matched (i.e., Keep individuals shown both in the master and using data).




This time, instead of using the OLS method, you want to use

            non-linear regression models.
        




26. Run the ordered probit regression to estimate (Eq. 1) above. 




27. Interpret your estimate for internet_use. 




28. Run the ordered logit regression to estimate (Eq. 1) above, and get the estimates of odds ratio (i.e., use the “or” option in the ologit command).




29. Interpret your estimate for internet_use. 




30. Your null hypothesis: Gender does not affect life satisfaction. Based on your ordered logit estimate for gender in Q28, test your hypothesis

            using the 95% confidence interval.
        




31. Visualize the conditional predicted probability of each response category (1. SDA, … 7. SA) for individuals who are female and aged between 20-80. 





            Submit your 1) do file and 2) MS Word document. 
        


4

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