you are correct. In case anyone wonders—the comment has been removed.

Which means they recognised what they were, or that they at least existed – even if only theorectically. It’s one of the signs of a well-researched paper.

Remember – my post was in reply to a person who thinks raw numbers are the be all and end all in themselves. You should not have expected each and every caveat to have been explained to them.

“Studies with known limitations including potential confounding effects are written, published, and provide valuaable insight all of the time, if you don’t understand that, the notion that you have a clue how science works is pretty funny.”

Indeed I do know that and there’s nothing in my comment that indicates otherwise, you contradict me by mentioning the very thing I was getting on at. The post was in response to a simplistic assertion and was thus written simplistically. I may have confused you by using the term ‘accounts’, although I expected the context to indicate that it was being used in it’s broader meaning (i.e. the meaning likely to be understood by the person I was writing to).

“The idea that we’ve done all we can in terms of vaccine research demonstrates a lack of critical analysis of the issue.”

Indeed, and at no point did I say we should stop researching.

Although your reply is not incorrect – it’s ‘correcting mistakes’ that weren’t even made. When reading replies, please read the post they were in reply to. This helps avoid mistakes by providing context which informs correct interpretation.

I do not disagree with the points you have made, nor did my comment indicate such. I hope you agree that this is the end of this exchange as there is no purpose responding to a person who it appears I may not actually disagree with.

Not making a study that accounts for all confounders would be pointless, as the numbers would certianly not speak for themselves, but would be grotesquely misquoted, as already happens with IDEA and VAERS data.

Haha. No study ever takes into consideration all confouning effects, and in fact, many studies go to great lengths to detail the limitations of the studiy, up to and including confounding effects which could not be controlled for.

Perfect is the enemy of very good.

So far all of the scientific discussion about ‘how to put on a study’ has been completely originating from people other than the movement to ‘put on astudy’ – this is the total opposite to how science usually works.

Studies with known limitations including potential confounding effects are written, published, and provide valuaable insight all of the time, if you don’t understand that, the notion that you have a clue how science works is pretty funny.

Until we get some actual data and ideas from the ‘put on a study’ people they’re just voices in the wind

How about more direct analysis of immunological markers other that seriopositivity How about analysis that takes into consideration time dependent effects of vaccination? What about studies that analyze immunological impact on children genetic markers known to associate with immune function, autism and/or autoimmunity?

The idea that we’ve done all we can in terms of vaccine research demonstrates a lack of critical analysis of the issue.

– pD

If we didn’t account for confounders, the data would be useless as we would have no way on knowing whether it’s vaccines or better access to healthcare or poorer diet or living in cities or….....and so on and so on, that would account for the difference (if any).

So far all of the scientific discussion about ‘how to put on a study’ has been completely originating from people other than the movement to ‘put on astudy’ – this is the total opposite to how science usually works. Until we get some actual data and ideas from the ‘put on a study’ people they’re just voices in the wind.

Why would we NOT want to have information such as the number of children in the hospital for cancer who had received vaccines vs. the number of children in for cancer who were never vaccinated? You don’t even have to make an excellent study! Just let the numbers speak for themselves!!

Yesterday I found Kev’s original article about the phone survey and read all the comments. Several people wrote that Kev was wrong when he wrote that the difference is 1% or 2% and they explained (as jefflegweak in this thread) that the risk is respectively 100% or 200%. But Kev is right! Obviously many people are used to see the way in which newspapers report study-results. They very often indicate the RELATIVE risk as this sounds much more sensational than the ABSOLUTE risk. Jharris2004 explained the difference between the relative and the absolute risk perfectly! Generation Rescue has an interest to impress with a high percentage, but this is just sand in the eyes, and doesn’t reflect the reality. Obviously in this case the “dates” of the survey itself are worthless…