you may consider a “Letter to the Editor”. It would probably take a couple of more hours of your time, but the potential exposure is much greater and it might get a discussion going (often, authors are asked to rebutt scientific correspondence).

Don’t even grace the “you must be paid to post here” allegations with a reply.

I get payed by the hour, on an actual consulting job that is a little bit flexible fortunately. So not only do I not get payed to blog, it could easily be argued that I lose money for blogging. My wife certainly makes that argument.

Actually, I hope I don’t get hooked on blogging again, although I do have another similar post planned.

You can debate the issues raised in the piece or you can fuck off somewhere where snideness is appreciated. Consider that your last, and only warning. You are both acting like a pair of silly school children and when I decided to start blogging again I also decided not to tolerate idiots annoying me.

So, to summarise: debate issues vs fuck off. Choose now.

“So I did an analysis that took me several hours….... What is the significance of that?”

Money?

and he also said

“There’s no peer review here..”

Exactly – so it’s not worth a diddly-squat!

I can think of many bloggers who would be unhappy if that were the case.

So I did an analysis that took me several hours (didn’t count) to rebutt a paper that I imagine took a lot more time and effort to do. What is the significance of that? I could’ve written a critique without counter-analysis in one hour, and that wouldn’t mean the critique didn’t have points that need to be addressed (specifically the point about the control for population density is obviously unaddressed).

I think people understand that we’re in a blog and not a journal, and that there are differences between the two. There’s no peer review here except for the review of readers who take the time. I think blogs have some good things going for them in terms of enabling scientific debate, but of course they should be taken for what they are.

The correction is that it’s not enough to make the slope zero in order to standardize, but the average standardized prevalence should also be zero. In other words, the “standardized” prevalence is a collection of deltas (positive or negative) from the expected prevalence to the actual prevalence.

There’s a mathematical reason for this, and I will explain, since I don’t want people to think that I’m doing hocus pocus here.

First let me attempt a math-free explanation, which will not be as boring. What matters is how different from expected a county is. For example, San Francisco has a lower prevalence of autism than is expected given its population density. Hence, it should be expected to have a lower than normal mercury concentration. Los Angeles has a higher prevalence of autism than is expected given its density. So it should have a higher mercury concentration than normal.

Now, this can be derived from multivariate analysis, in which prevalence would be modeled as follows:

P = A*d + B*m + C

where d is (log) density and m is mercury concentration. A, B and C are coeficients that need to be calculated.

Mutivariate analysis cannot be graphed in 2 dimensions. This is a problem because in a graph you can see features (like San Francisco, Los Angeles and Orange) which help give a better idea of the merit of the correlation.

But we can do the next best thing. Let’s define P’ as follows:

P’ = P – A*d – C

Then clearly

B*m = P’

If we were to graph m vs. P’, we would see a slope given by B.

Now, consider what would happen if B tends to be zero:

– The graph of m vs. P’ would be a flat line with y = 0.
– P = A*d + C, which means that P’ would tend to be zero. In other words, a graph of d vs. P’ would be a flat line with y = 0 as well.

So we start by assuming that B tends to zero and we try to contradict ourselves. If B is zero, then A*d + C must be the trend we see in the graph of d vs. P. If we then calculate P’ = P – (A*d + C), which we call the standardized prevalence, we should expect that a graph of m vs. P’ should also be a flat line with y = 0.

Now, the graph of m vs. P’ will rarely be an actual flat line. It can be a negative trend (like in this analysis) or a positive trend. The graph vs. P’ won’t tell you the actual coefficients but it will tell you the general direction of the corrected trend. Also, graphically you should expect to see a trend if there’s one.

So you are saying that it is not a rigorous as the original study that you are seeking to discredit? Saying that you were attempting to make a point on a blog implies that it is not up to the same standards are the original research. And if that is the case it isn’t much of a rebuttal, is it?

“Plus my area of formal training is not epidemiology. Would they consider it?”

Only one way to find out.

“Plus I’d prefer not to out myself as an autistic man, as you might understand; and so on.”

No, I don’t understand that. If you feel strongly about it you should attempt to get it published as a rebuttal, this is an important issue.

If you think that you lack the needed skills then attempt to find a co-author who would be willing to help with the process.

Ms. Clark wrote:
“Joseph, I hope you send the link for this blog to Health & Place and to some of the autism epidemiology people, like maybe Irva Hertz-Picciotto from the MIND Institute”

I don’t think the journal would accept a submission via a link to a blog.