Hi,
That's OK, I understand that you are busy.
Do you have any idea on when will you be able to work on this? I ask mainly to know if it will be ready for the beginning of the next spring semester.
Thanks.
Linear Regression - Robust standard error
Re: Linear Regression - Robust standard error
Hi, Jorge.
Pay attention to the possible times of the year, for Jonathon the spring period begins today...
Cheers,
Maurizio
----------------
Sorry if Off-Topic
Pay attention to the possible times of the year, for Jonathon the spring period begins today...
Cheers,
Maurizio
----------------
Sorry if Off-Topic
Re: Linear Regression - Robust standard error
Fair enough.MAgojam wrote:Hi, Jorge.
Pay attention to the possible times of the year, for Jonathon the spring period begins today...
Cheers,
Maurizio
----------------
Sorry if Off-Topic
For me, the beginning of the spring semester means february. So, shall we expect this feature in jamovi by february 2022?
Re: Linear Regression - Robust standard error
hard to say. scrape together some sponsorship, and i'm sure we can have it by then.
cheers
jonathon
cheers
jonathon
Re: Linear Regression - Robust standard error
I would strongly support the inclusion of robust standard errors. They allow researchers to work with data that are heterogeneous, even when the underlying factors that cause the clustering cannot be measured or even specified. That is, they allow us to work with the messy reality of real world data.
Robust standard errors are now part of safe statistical practice, and even on teaching courses we teach students to switch them on at all times.
Robust standard errors are now part of safe statistical practice, and even on teaching courses we teach students to switch them on at all times.
Re: Linear Regression - Robust standard error
Thanks, that's exactly my point. Regression analysis without robust standard errors is pointless and we always tell our students to don't forget to include it in their analysis.rconroy wrote:I would strongly support the inclusion of robust standard errors. They allow researchers to work with data that are heterogeneous, even when the underlying factors that cause the clustering cannot be measured or even specified. That is, they allow us to work with the messy reality of real world data.
Robust standard errors are now part of safe statistical practice, and even on teaching courses we teach students to switch them on at all times.
Re: Linear Regression - Robust standard error
sure. scrape together some sponsorship, and we'll take it from there.
cheers
jonathon
cheers
jonathon
Re: Linear Regression - Robust standard error
Hi Jonathon:
Can I chime in and say that I too would really appreciate the addition of robust standard errors in JAMOVI. Since reading the now classic paper titled, On the Unnecessary Ubiquity of Hierarchical Linear Modeling" (https://pubmed.ncbi.nlm.nih.gov/27149401/), I have to come to appreciate the use of robust standard errors. The article makes a strong case that in psychology we overuse MLM, when all we need with clustered data (for most questions) is robust standard errors. I would be happy to throw some money at this if that will expedite this. Seems like something relatively easy to program...
Please help!
Michael Inzlicht
Can I chime in and say that I too would really appreciate the addition of robust standard errors in JAMOVI. Since reading the now classic paper titled, On the Unnecessary Ubiquity of Hierarchical Linear Modeling" (https://pubmed.ncbi.nlm.nih.gov/27149401/), I have to come to appreciate the use of robust standard errors. The article makes a strong case that in psychology we overuse MLM, when all we need with clustered data (for most questions) is robust standard errors. I would be happy to throw some money at this if that will expedite this. Seems like something relatively easy to program...
Please help!
Michael Inzlicht
Re: Linear Regression - Robust standard error
Hi Jonathon.mickeyi wrote:Hi Jonathon:
Can I chime in and say that I too would really appreciate the addition of robust standard errors in JAMOVI. Since reading the now classic paper titled, On the Unnecessary Ubiquity of Hierarchical Linear Modeling" (https://pubmed.ncbi.nlm.nih.gov/27149401/), I have to come to appreciate the use of robust standard errors. The article makes a strong case that in psychology we overuse MLM, when all we need with clustered data (for most questions) is robust standard errors. I would be happy to throw some money at this if that will expedite this. Seems like something relatively easy to program...
Please help!
Michael Inzlicht
I hope you are well.
Given the interesting message from Michael Inzlicht, do you think it would be possible to move on with the robust standard error feature in jamovi?
Thank you,
Jorge