bear66
Well-known member
No. They're of three types and are single strand but not enveloped as flu/coronaviruses.Didn't we get the 160 forms through mutations though?
No. They're of three types and are single strand but not enveloped as flu/coronaviruses.Didn't we get the 160 forms through mutations though?
Falling for what?I cannot believe people are still falling for this.
There is only a 0.3% difference in the make up of the variant of concern to the original variant first discovered in Wuhan apparently.
To be fair, it's not that obvious sometimes.Chimps and humans share 98.8% of their DNA. Surprising how often it shows.
To be fair, it's not that obvious sometimes.
Thanks Ziggy.So pleased your operation was successful. Laughing.
The last year or so in a cartoon.Some people on this thread make me think of the below - probably been watching too much BBC.
View attachment 18568
Like it. Unfortunately the models are made by statisticians and are therefore an approximation, so will never give an exact figure.
Thanks Ziggy.
I am suspicious of the group test meta-analysis stuff. It's very convincing till you find out you can get any answer you want!Like it. Unfortunately the models are made by statisticians and are therefore an approximation, so will never give an exact figure.
It is even better when you build a suite of models all using the other models outputs. I used to do this as a job, not in a clinical sense, and you could get the model to say whatever you wanted it to say.
My world was in banking and finance, I hope clinical data is more heavily peer tested.I am suspicious of the group test meta-analysis stuff. It's very convincing till you find out you can get any answer you want!
That's really a more focused multi-variable analysis, but the benefits of multi-variable analysis is the weeding out of variables with weak correlations, so why try to get ahead of the game by making unnecessary assumptions. We'd have stopped all analysis of data to do with covid except that pertaining to old people if you took Bayes to the extreme . . . and learnt nothing.Bear is there no move towards bayes loguc in mainstream statistical analysis? It only works when inputs are inter-dependent, but I would have thought it would have started to find it's way in to mainstream stats
Thats a very good point when looking at the risk facyors. I was more thinking for forecasting infection rates rather than the risk factors which are fairly well understood.That's really a more focused multi-variable analysis, but the benefits of multi-variable analysis is the weeding out of variables with weak correlations, so why try to get ahead of the game by making unnecessary assumptions. We'd have stopped all analysis of data to do with covid except that pertaining to old people if you took Bayes to the extreme . . . and learnt nothing.
I think the difficulty is that the current view is the Indian variant is more transmissible . . but is that due to physics or virology? Bayes could only look at those living in close proximity or those with specific ethnic risk. Or those can be related in which case, don't throw out any data.Thats a very good point when looking at the risk facyors. I was more thinking for forecasting infection rates rather than the risk factors which are fairly well understood.
I would have thought a bayes net would work very well with different levels and aspects of lockdown, for example. I only ever hear about it in machine learning and never in statistical analysis.
When building finance risk models, there were two different schools of thought. The traditional way is to step in the most powerful variables first and then look for uplift for other variables. This would over predict on age and maybe add ethnicity.That's really a more focused multi-variable analysis, but the benefits of multi-variable analysis is the weeding out of variables with weak correlations, so why try to get ahead of the game by making unnecessary assumptions. We'd have stopped all analysis of data to do with covid except that pertaining to old people if you took Bayes to the extreme . . . and learnt nothing.
It's just awful at the end of mental health awareness week that SAGE come out and publish a predictions of 10,000 hospital admissions per day and a peak height prediction higher than the one in January.