I was supposed to be running my next post on correlations today (my goal is to run one such post a week until the series is finished), but recent political developments have left me in a foul mood. If you don't know what I'm referring to, you can see my previous post here. I don't trust myself to put the final touches on a technical post while in a foul mood, so instead, I'd like to discuss a different, but somewhat related, matter.
I am interested in paleoclimatology. I am no Steve McIntyre (who runs Climate Audit), as has been pointed out by several of my critics, but I like to think I am reasonably knowledgeable on the field. I certainly know more about it than the average person, and when it comes to fine technical details of individual proxies/reconstructions, I might even be more knowledgeable than a number of "experts." SO today, I'd like to discuss a problem in the field.
People familiar with my writing know I have discussed work by a man named Stephan Lewandowsky quite a bit. The short version of the discussion is he has behaved unethically, published false statements and, most importantly generated bogus results by misusing what is relatively simple mathematics.
I'm not the only person to say such, but the discussion has been spread out across many locations over several years. Today, I'd like to start working on collecting the information into a single resource by beginning with a discussion of the gross misuse of simple statistics.
Whatever one may believe about Lewandowsky and his behavior, the indisputable truth is the methodology he relied upon to publish several papers fabricates results because f how he misused it. Results he published are completely and utterly without merit.
My last couple posts have examined how it appears data used in two scientific papers, making up a significant portion of a PhD dissertation by Kirsti Jylha, has been tampered with. I don't want that issue to dominate the discussion though. While data tampering would obviously be a serious problem, I want to remind people this work was complete nonsense even without concerns of data tampering.
In my last post, I asked for help explaining correlations between Rater IDs for people who took a survey and the responses they gave to that survey. The order in which people take a survey should not affect how they respond to the survey, yet according to a data set I was examining, they do.
Today I'd like to go further and show even more inexplicable results. I don't like accusing people of fraud or tampering with data, but I can't come up with any other explanation. Perhaps someone else can help me come up with one.
I do not like making accusations of dishonesty. I have done so plenty of times, but each time I did, I first put significant effort into trying to find an alternative explanation. Today's post is for that. I have encountered data with properties I cannot explain. I am hoping someone can find an explanation for me that isn't, "Someone fabricated data."
I've owed you guys a post for a little while now, and I apologize for how long it's taken. I just can't get past a certain problem. As you may recall, I recently discussed how "correlation is meaningless" in relation to a paper which claimed to demonstrate climate change "deniers" possess certain characteristics. For a quick refresher:
The reason the authors can claim there is a "statistically significant" correlation between these two traits is they collected almost no data from anyone who "denies" climate change. The approach the authors have taken is to draw a line through their data, which is how you normally calculate the relationship between two variables, then extrapolate it out far beyond where their data extends.
There are a lot of ways of describing this approach. When I've previously said correlation is meaningless, I used an example in which I demonstrated a "statistically significant" correlation between belief in global warming and support for genocide. It was completely bogus. I was able to do it because I used the same approach the authors used. Namely:
1) Collect data for any group of people.
2) Determine views that group holds.
3) Find a group which is "opposite" the group you study.
4) Assume they must hold the opposite view of the group you studied on every issue.
This will work with literally any subject and any group of people. You can reach basically any conclusion you want because this approach doesn't require you have any data for the group of people you're drawing conclusions about.
Today I want to move beyond simple correlation coefficients and get into some of the more complex modeling the authors performed. There's a problem though. You see, the results the authors published are impossible to achieve.
I've written a post titled, "Correlation is Meaningless" once before. It makes the same basic point I made in a recent post discussing the PhD dissertation by one Kirsti Jylhä. I'm going to continue my discussion of Jylha's work today to examine more of a phenomenon where people misuse simple statistics to come up with all sorts of bogus results. In Jylha's case, it undercuts much of the value of her PhD.
A couple months ago I contacted a scientist asking to examine the data used in three papers which made up the bulk of her PhD dissertation. The initial response contained this:
Thank you very much for your email and interest in our publications.
We follow ethical guidelines from the American Psychological Association, and we are happy to share our data to other competent researchers. Would you please indicate your background and outline how you plan to use the data?
Which struck me as odd as I have no idea how one would determine which people are "competent researchers." I was pessimistic about this response as it seemed like this might be used as an excuse for not sharing data with me, but fortunately, the issue of whether or not I am a "competent" researcher never came up again.
After examining the data for these three papers, I came to the conclusion the papers were fundamentally flawed in a way which invalidated their analysis and conclusions. I informed the author of this thesis of my concerns and tried to give her time to examine the issue privately. I believe several months was long enough so now I'd like to discuss the matter in public. Hopefully, this will demonstrate I am in fact competent.
I don't use the word "fraud" lightly. I've long criticized people who do. Not only do I think it is wrong in principle, I think it is wrong from a strategic perspective. If you cry, "Fraud!" over every little thing, nobody will listen when you point out real fraud. It's called a sense of proportion. One's rhetoric should ramp up with the severity of what is being criticized.
I bring this up because I want to follow up on my last post which discussed a case of fraud involving $100,000. Or rather, it was a case of fraud where a person used the false promise of $100,000 to cheat people out of money. You can read that post for the details. It's a long post so I won't re-hash the details here. I'll just give a short summary.
Last year, a man named Douglas Keenan announced he would give $100,000 to anyone who could win a contest he had created. There were tons of red flags which should have made people suspect this was bogus, but despite that, several big names in the global warming "skeptic" movement promoted the contest. After people spent some time publicly discussing how they might try to win the contest, Keenan switched out the data set used in the contest for one the proposed methodologies would be less effective on.
This contest involved a $10 entrance fee. That makes what he did fraud. I've been pointing that out for the last year. Just 24 hours ago, Keenan admitted it. Continue reading
Something which has long bothered me about the global warming debate is how "skeptics" are so quick to cry, "Fraud!" about... well, practically anything. I discussed this recently where an organization made a list of hundreds of pieces of work they took (partial or full) credit for as part of applying for a grant. The list included over 500 items, and it turns out approximately 25 of those items should not have been included. "Skeptics" yelled and screamed about how this was criminal fraud that should be prosecuted.
That's nonsense of course. Nobody was able to show any evidence the inclusion of those extra items was done with the intent to mislead as opposed to having been a simple mistake. Nobody was able to show the inclusion of a small number of extra items in one document submitted along with an application could have had any effect on whether or not the grant was awarded. In other words, nobody was able to show this was anything more than an embarassing mistake.
At the same time, these same "skeptics" are happy to either overlook, promote or even defend criminal fraud when it suits their purposes. I'd like to discuss that today because I find it offensive these "skeptics" have robbed me of $100,000.