BREAKING: Editor-in-chief of Remote Sensing resigns over Spencer & Braswell paper

What I see is a troubling sign for the warmists – a random selection of three respected scientists in another field went 3 for 3 against their agenda. I wonder if there were 9 reviewers what the ratio would be?

A new desperate AGW tactic – the Kamikaze Warmist? They fall on their own knife.

reply to: Beesaman says: September 3, 2011 at 5:34 am

Looks like Joe Romm is accusing Dr Spencer of stacking the deck!

•Joe Romm says: September 3, 2011 at 8:21 am
The “more to this story” is that Spencer probably got to name his reviewers (not uncommon) and the editors weren’t sophisticated enough to figure out they weren’t representative of the full spectrum of scientific understanding (that is uncommon).

http://thinkprogress.org/romm/2011/09/02/310889/editor-denier-bunk-resigns-spencer/?replytocom=345562#respond

ROFLM-you-know-what-O!!!
How’s that saying go? Point one finger at me, and 4 [of your own] are pointing back at you!
Does Romm not even realise that he’s slamming “The Team,” himself, and every AGW positive article in existence here? I guess he must honestly believe that his second parenthetical really does let ’em off the hook, but seems to me that if anything it hooks them all the more solidly. Conformation Bias, Significance Chasing, Selective Reporting, Publication Bias, Flawed Experimental Design, etc., and human nature are all strange and powerful things (well, ok, they’re actually common sense, but far far too often discounted, accepted, ignored, or unrecognized) – and ‘climate scientists’ haven’t somehow magically avoided all these problems any better than any other field (and frankly I suspect far less than those that are less complex, not spread across multiple fields, etc).
Folks who go on about conspiracies (either to embrace or ridicule the very idea), simply don’t recognize that in a group of humans, especially when it comes to something new and ‘hot,’ it doesn’t take some secret skulking conspiracy – just the above factors that our very natures are prone to. Next time you run across someone who says AGW must be true because there’s no way a global conspiracy could exist, just point ’em to the articles I’ve linked below. Sure, conspiracies do occur, but they’re not necessary to wind up with widely held mistaken impressions supported by supposedly solid research.
If Romm is really this dense but is sincere (giving the benefit of the doubt), then he desperately needs to read Ioannidis and similar papers. Someone ought to giftwrap him copies of all related Ioannidis papers, and deliver them to him as an early Christmas present.
my apologies for this being such a long post!
http://www.plosmedicine.org/article/info%3Adoi%2F10.1371%2Fjournal.pmed.0020124

Why Most Published Research Findings Are False John P. A. Ioannidis
There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.

From http://www.newyorker.com/reporting/2010/12/13/101213fa_fact_lehrer?currentPage=all [emphasis added]
[quoting Ioannidis] ….“It’d be really great if the initial studies gave us an accurate summary of things. But they don’t. And so what happens is we waste a lot of money treating millions of patients and doing lots of follow-up studies on other themes based on results that are misleading.” In 2005, Ioannidis published an article in the Journal of the American Medical Association that looked at the forty-nine most cited clinical-research studies in three major medical journals. Forty-five of these studies reported positive results, suggesting that the intervention being tested was effective. Because most of these studies were randomized controlled trials—the “gold standard” of medical evidence—they tended to have a significant impact on clinical practice, and led to the spread of treatments such as hormone replacement therapy for menopausal women and daily low-dose aspirin to prevent heart attacks and strokes. Nevertheless, the data Ioannidis found were disturbing: of the thirty-four claims that had been subject to replication, forty-one per cent had either been directly contradicted or had their effect sizes significantly downgraded. [bears repeating: 49 of the MOST CITED & influential studies, yet only 34 had been replicated, with poor results in 41% of those! That’s in medicine, where apparently replicability studies are ‘the thing’ right now – the impression I get is that there is very little in the way of replicability studies done in ‘climate science’ leaving the door wide open to far worse problems than even medicine is seeing.]
The situation is even worse when a subject is fashionable. In recent years, for instance, there have been hundreds of studies on the various genes that control the differences in disease risk between men and women. These findings have included everything from the mutations responsible for the increased risk of schizophrenia to the genes underlying hypertension. Ioannidis and his colleagues looked at four hundred and thirty-two of these claims. They quickly discovered that the vast majority had serious flaws. But the most troubling fact emerged when he looked at the test of replication: out of four hundred and thirty-two claims, only a single one was consistently replicable. “This doesn’t mean that none of these claims will turn out to be true,” he says. “But, given that most of them were done badly, I wouldn’t hold my breath.”
According to Ioannidis, the main problem is that too many researchers engage in what he calls “significance chasing,” or finding ways to interpret the data so that it passes the statistical test of significance—the ninety-five-per-cent boundary invented by Ronald Fisher. “The scientists are so eager to pass this magical test that they start playing around with the numbers, trying to find anything that seems worthy,” Ioannidis says. In recent years, Ioannidis has become increasingly blunt about the pervasiveness of the problem. One of his most cited papers has a deliberately provocative title: “Why Most Published Research Findings Are False.”
The problem of selective reporting is rooted in a fundamental cognitive flaw, which is that we like proving ourselves right and hate being wrong. “It feels good to validate a hypothesis,” Ioannidis said. “It feels even better when you’ve got a financial interest in the idea or your career depends upon it. And that’s why, even after a claim has been systematically disproven”—he cites, for instance, the early work on hormone replacement therapy, or claims involving various vitamins—“you still see some stubborn researchers citing the first few studies that show a strong effect. They really want to believe that it’s true.”
That’s why Schooler argues that scientists need to become more rigorous about data collection before they publish. “We’re wasting too much time chasing after bad studies and underpowered experiments,” he says. The current “obsession” with replicability distracts from the real problem, which is faulty design. He notes that nobody even tries to replicate most science papers—there are simply too many. (According to Nature, a third of all studies never even get cited, let alone repeated.) (continued online)