Very interesting presentation Sir. I just completed a survey on consumer tipping behaviors in the tourism and hospitality industry in Cameroon for my Ph.D. thesis dissertation. The first part looks at the determinants that influence people to tip or not tip (dependent variable; binary=tip or not). Here, I have no issues implementing a probability approach. But in the second part, the objective is to see the factors that influence people to tip more (tip size/amount), and the dependent variable is continuous. In this second part, the focus is solely on those who tip. My worries are: 1. After running the OLS, Simple Tobit model, and truncated Tobit, I need to carry out the Heckman selection bias test, and when I do this test: a) By including twostep at the end of Heckman's command, Lamda isn't significant b) When two-step is not included at the end of the Heckman selection command, the model is very significant and good 2. What do I need to do? do I retain the (b) for interpretations by considering lnsigma or what do I do with (a) to have consistent results? I will really appreciate your help at this point Prof
Hey Shishir, great video! Thanks so much for detailed explanation. I would like to ask a question about using Heckman selection correction to control for self-selection bias. I have been doing a survey study with participants from social media sites (e.g., Twitter/ Facebook). I reached out to 500 people on social media and only received 200 responses. Because of the low response rate, I would need to correct the selection bias introduced by the low response rate. I tried to use SPSS and STATA to do the test. In the first stage of the analysis, a probit regression needs to be used to estimate the likelihood of users not participating in the survey. However, I do not have data for non-participants (as they did not respond to my invitation). Thus, the selection model is of no use because the selection dependent variable is participation status, a binary variable that accounts for participation vs. non-participation. My questions are as follows: 1) Can I use the Heckman selection correction to control for self-selection bias? If so, how do I run the selection model when the data for non-participants are unavailable? 2) Are there any other ways to address self-selection bias in an online survey study such as mine? 3) Does Heckman's correction apply to logistic regression or ordinal logistic regression? I realised its second step model is a linear regression but my dependent variable is a binary one (hence logistic regression). Many thanks for answering my questions. Much appreciated!
1.you can't use Heckman model because in order to apply probit model you need participants as well as non participants. 2.you can use censored model 3. I think Heckman model is advancement of Tobit and Tobit is nothing but Tobin's probit...here we assumed normality assumption censored dependent variable through manipulation...
Can I use this model for categorical dependent variable? Let me explain briefly, One dependent variable is whether people consume or not (consume =1, not consume =0) and Another one variable is how frequently they eat in a year (consume daily or weekly =1, consume once a month =2, consume rarely=3). Independent variables are demographic factors, psychological factors, social factors and product related factors.
hi Mr Shishir really i am enjoyed on your presentation and i am going to carry study on farmers perceptions of and adaptation to climate change. would you recommend any,,,,,,,,,,,
@@shishirroy8497 Two dependent variables 1 perception to climate change 2. Adoption of adaptation strategies Independent variables 1. Sex of household head 2. Age of house hold head 3. Family size 4. Total agriculture land 5. Livestock ownership 6. Farming Experience in year 7. Livelihood diversification(migration) 8. Access to extension services 9. Access climate information 10. Concerned about losses due to CC 11. Awareness of CC 12. Access to communication device 13. Access to local market 14. Membership to community-based organizations
@@danielaamarikplimdalle4505 @ Thank you. Can you say the nature of dependent variable . i means the minimum and maximum value of the dependent variable . If you share your mail id then I can mail you my whatsapp number and you can directly meet with me .
Hi, Thankyou for this lecture. Can you please guide on how to estimate/predict the value of wages in this model if we take dependent variable as logWage.
Very interesting presentation Sir. I just completed a survey on consumer tipping behaviors in the tourism and hospitality industry in Cameroon for my Ph.D. thesis dissertation. The first part looks at the determinants that influence people to tip or not tip (dependent variable; binary=tip or not). Here, I have no issues implementing a probability approach. But in the second part, the objective is to see the factors that influence people to tip more (tip size/amount), and the dependent variable is continuous. In this second part, the focus is solely on those who tip. My worries are:
1. After running the OLS, Simple Tobit model, and truncated Tobit, I need to carry out the Heckman selection bias test, and when I do this test:
a) By including twostep at the end of Heckman's command, Lamda isn't significant
b) When two-step is not included at the end of the Heckman selection command, the model is very significant and good
2. What do I need to do? do I retain the (b) for interpretations by considering lnsigma or what do I do with (a) to have consistent results?
I will really appreciate your help at this point Prof
Many thanks for your clear explanation,
Hey Shishir, great video! Thanks so much for detailed explanation. I would like to ask a question about using Heckman selection correction to control for self-selection bias.
I have been doing a survey study with participants from social media sites (e.g., Twitter/ Facebook). I reached out to 500 people on social media and only received 200 responses. Because of the low response rate, I would need to correct the selection bias introduced by the low response rate.
I tried to use SPSS and STATA to do the test. In the first stage of the analysis, a probit regression needs to be used to estimate the likelihood of users not participating in the survey. However, I do not have data for non-participants (as they did not respond to my invitation). Thus, the selection model is of no use because the selection dependent variable is participation status, a binary variable that accounts for participation vs. non-participation.
My questions are as follows:
1) Can I use the Heckman selection correction to control for self-selection bias? If so, how do I run the selection model when the data for non-participants are unavailable?
2) Are there any other ways to address self-selection bias in an online survey study such as mine?
3) Does Heckman's correction apply to logistic regression or ordinal logistic regression? I realised its second step model is a linear regression but my dependent variable is a binary one (hence logistic regression).
Many thanks for answering my questions. Much appreciated!
1.you can't use Heckman model because in order to apply probit model you need participants as well as non participants.
2.you can use censored model
3. I think Heckman model is advancement of Tobit and Tobit is nothing but Tobin's probit...here we assumed normality assumption censored dependent variable through manipulation...
Can I use this model for categorical dependent variable? Let me explain briefly,
One dependent variable is whether people consume or not (consume =1, not consume =0) and
Another one variable is how frequently they eat in a year (consume daily or weekly =1, consume once a month =2, consume rarely=3).
Independent variables are demographic factors, psychological factors, social factors and product related factors.
hi Mr Shishir really i am enjoyed on your presentation and i am going to carry study on farmers perceptions of and adaptation to climate change. would you recommend any,,,,,,,,,,,
Thank you ...please provide the detail information of your model such as your dependent variable and independent variables ....
@@shishirroy8497 Two dependent variables
1 perception to climate change
2. Adoption of adaptation strategies
Independent variables
1. Sex of household head
2. Age of house hold head
3. Family size
4. Total agriculture land
5. Livestock ownership
6. Farming Experience in year
7. Livelihood diversification(migration)
8. Access to extension services
9. Access climate information
10. Concerned about losses due to CC
11. Awareness of CC
12. Access to communication device
13. Access to local market
14. Membership to community-based organizations
@@danielaamarikplimdalle4505 @ Thank you. Can you say the nature of dependent variable . i means the minimum and maximum value of the dependent variable . If you share your mail id then I can mail you my whatsapp number and you can directly meet with me .
Hi,
Thankyou for this lecture.
Can you please guide on how to estimate/predict the value of wages in this model if we take dependent variable as logWage.
please mail me shishir@apccollege.ac.in
the explanation depends on the nature of independent variables .......so if u send me the smcl file then it may easier to give answer.
nice explanation
but How can I get your address please?