Hi! Thanks for this video. I really want to know how I can do this in SPSS after I made up a GLMM. I want to know the joint significance of some variables, but don't know how to do it in SPSS. Can you help me with that?
Nice and clear video! I am wondering though, I have it where the p-value is 0.4322, meaning we fail to reject the null hypothesis. However when I do test variable1 variable2 I get the exact same results. Does this mean the variables are jointly statistically significant or not? How does the p-value come into it?
Dan, The p-value will give you the level of significance at which you can just exactly reject the null. So regardless of the test, a p-value greater than 0.10 indicates that the calculated test statistic does not surpass the 10% critical value.
If I fail to reject the null hypothesis (which in my case, is linearity), does that mean I can conclude that my restricted model is more valid/better than the unrestricted model?
Hi, is it possible to test the joint significance of the intercept = 3 and beta1 = -2 (for example) ? How do you test an intercept with the "test" command ?
You can combine two test commands with the 'accumulate' option: "test _cons=3" "test beta1=-2, accumulate" The resulting F-test will include both restrictions. Interesting question!
It is not an error. The p-value may appear to be zero, but if you go out enough decimal points you will always see a positive value. It means you can reject the null at well beyond 1% significance.
Yes, the implicit assumption is a homoskedastic error, but I should have mentioned it, - thank you! I try to focus on one task at a time for the purposes of the tutorial, but in reality, there are many issues that have to be dealt with before we can 'believe' the results.
I was looking for such an explanation all over youtube. As said by others, clear and concise. Thanks
Great stuff Mike, I like how you recapped the maths before showing the STATA commands. Thanks.
This was really good, the concept is completely clear for me
Thank you - glad it was helpful!
Super helpful for understanding how to test joint hypothesis! Thx a lot!
Glad it was helpful!
You legend. God bless you. Love all your stata videos.
Very helpful and clear interpretation!
Amazing and easy to understand, thank you! Just what I was looking for
You're very welcome!
This was clear and concise. Thank you for the video!
I would like to thank you for your precious and cristal clear work! Amazing help
thx! amazing! grettings from Perú
thanks for saving with my coursework
You’re welcome - glad it helped!
Thank you so much!
Excellent explanation! what it’s the meaning of q next to the F ?
Another great video. Thanks.
Hi! Thanks for this video. I really want to know how I can do this in SPSS after I made up a GLMM. I want to know the joint significance of some variables, but don't know how to do it in SPSS. Can you help me with that?
Thank you so much
Please help with the Wald Test in Stata for structural break
Great video, big help
Lo quiero mucho sr que explica stata
Love you man, very helpful
very clear explanation!
So great!!!!
Nice and clear video! I am wondering though, I have it where the p-value is 0.4322, meaning we fail to reject the null hypothesis. However when I do test variable1 variable2 I get the exact same results. Does this mean the variables are jointly statistically significant or not? How does the p-value come into it?
Dan, The p-value will give you the level of significance at which you can just exactly reject the null. So regardless of the test, a p-value greater than 0.10 indicates that the calculated test statistic does not surpass the 10% critical value.
Thanks bro! keep it up
Thanks. It was so useful
If I fail to reject the null hypothesis (which in my case, is linearity), does that mean I can conclude that my restricted model is more valid/better than the unrestricted model?
Hi, is it possible to test the joint significance of the intercept = 3 and beta1 = -2 (for example) ? How do you test an intercept with the "test" command ?
You can combine two test commands with the 'accumulate' option:
"test _cons=3"
"test beta1=-2, accumulate"
The resulting F-test will include both restrictions. Interesting question!
@@mikejonaseconometrics1886 Thank you very much!
thanks a lot!
You’re welcome - hope it was helpful!
Thank you!!!
Thanks a lot. Just a little question : If we want to test (beta1+beta2)=0, how to do that in stata ?
You can use the F-test here as well. If your regression is 'regress y x1 x2', the test command will simply be 'test x1+x2=0'
Cool !!
5.12 > 2.30. Where do we get the 2.30 value from?
how do you do this for mlogit
Sir Is there a way to resolve stata r(950) error...
It's so helpful!!!!!!!!! thxxxxx
if you get a p value of 0, does that mean there is an error or that those variables have high joint significance?
It is not an error. The p-value may appear to be zero, but if you go out enough decimal points you will always see a positive value. It means you can reject the null at well beyond 1% significance.
are you assuming homoskedasticity? Wouldn't it be more correct to write the regression model with " , r " in the end before doing the F test?
Yes, the implicit assumption is a homoskedastic error, but I should have mentioned it, - thank you! I try to focus on one task at a time for the purposes of the tutorial, but in reality, there are many issues that have to be dealt with before we can 'believe' the results.
thanks a lot !!!