Stat Modeling; (sorry about the code glitch)
The point is that I shouldn’t be so shocked to hear that Columbia medical school has prominent faculty who’ve been involved in research fraud. If you’re a medical researcher and a cheater, then research fraud is a natural step. Just as if you’re a storekeeper and a cheater, then ripping off your customers and employees is a natural step; or if you’re a statistician and a cheater, then it makes sense to hire yourself out as a data manipulator; or if you’re a CEO and a cheater, then it makes sense to fake your corporate reports; or if you sell used cars and you’re a cheater, then you’ll hide the flaws in your cars; or if you’re a university administrator and a cheater, then it makes sense to fake your U.S. News statistics . . . ulp! In all these examples, there’s a clear incentive to cheat: if you play honest, it’s easy to fall behind your competitors who could be cheating too. Indeed, you could argue that, if you play by the rules, you’d be letting the side down . . . it’s arguably unethical not to cheat. You’re developing treatments what will save lives, after all!
Via Steve McIntyre: Gelman didn’t mention the following famous statement by climate scientist Stephen Schneider
Trust:
https://modernity.news/2025/11/12/believe-a-dane-not-an-albanian-these-are-the-worlds-most-trusting-societies/
Fraud seems to be a trend with those who hold Doctorates, whether Medical or Philosophical.
An EMT talked about getting a call for a patient transfer. The MD had ordered tests for the patient. The EMTs looked at the patient and realised he was room temperature and rigor was starting. He told the MD that the patient was deceased and there would be no transfer for tests. The MD became furious demanding the transfer take place. The MD wanted the government payment for ordering the tests and likely very well knew the patient was already deceased. This was during Wretched Knothead’s reign of error.
Wanted the patient to not have died in their facility to keep their numbers good.
That too. Good stats means more money.
I think you have to look at “motivation.” Take the example of curing cancer as a baseline. IS the primary motivation of those researchers taking on this disease to find a cure? Or, has that original purpose been bastardized by other motivations? Getting grant money for the party which employs the medical researcher. Solidifying and holding an employment position in search of a cure for cancer. Like it or not, medical research had become and industry that has diluted what should be the primary focus (finding the cure). This is understandable. Research is expensive. Excluding the truly altruistic mentality, pragmatism requires such divergent. It’s not efficient. But, it is reality. That doesn’t even get into the “for profit” pharmaceutical companies who take it to another level. We’re seeing that facet in real time with all the held back warnings relative to something as simple as Tylenol.
I use the cancer example because, on the surface, you’d be hard pressed to find anyone who hasn’t been touched in some way by the disease. I think we can all agree that cancer exists, and is bad. Curing it has confounded humanity for generations. The primary treatments remain barbaric to some extent in that chemotherapy or radiation treatment may result in a hiatus from suffering, but it is at the cost of damage done to other facets of the human body in an indiscrete way.
Now, consider all the diverging motivations that relate to Climate Change or something else similarly politicized. The parties in all facets of research are motivated by different stimulus. Some (perhaps a significant number) are motivated by the wrong things. Some are outright political hacks. Others are self-interested career minded posers. Then there are those motivated in a balanced healthy pursuit of curiosity and understanding. The latter seems to be more rare these days.
Cancer is a constellation of diseases that fall under one broad umbrella, and thus curing “cancer” is a false premise to begin with. Big pharma execs and scientists die of cancer, too, so I’m on the side of “depressingly hard to solve” over the grand conspiracy argument that they refuse to find cures so that dying pharma execs (and their dead relatives and children and friends) can become richer.
That isn’t what I said. I merely pointed out that it has become such an industry as opposed to a singular goal, that the motivation to cure cancer is diluted by other motivating factors. I see that as a failing in the grant process among other things. Innovation in cures is curbed by overzealous and pre-established outlines of exactly how that money will be used. It leave less room for innovative approach. And, while cancer can present itself in a wide spectrum, it, ultimately comes down to uncontrolled growth and expansion of abnormal cells.
I certainly don’t fall under the conspiracy theories that suggest that a cure exists for select people. I just think there is a better, more efficient, and focused way to attack disease.
There’s a lot of motivation NOT to cheat as well.
In research, bogus results will likely be overturned by later studies. People may not be able to prove you cheated, but they will know your research can’t be duplicated.
Further, much medical research is done in groups — often very large groups. The lone researcher is rare. This means that you have people constantly looking over your shoulder, usually very smart people. And given that the average researcher does have integrity, someone may well tattle.
My parents both died from cancer. Both said under no uncertain terms was anyone to donate to the Canadian Cancer Society in their memory. Their main beef was the amount of money spent on administration and executive salaries as opposed to actual research.
Let me paraphrase: “The beatings will continue until morality improves.”
From John Fund posted on May 8 2020 at Columbia edu
John had a look at the history of epidemic predictions from Neil Ferguson, the Neil Ferguson whose models and predictions had been instrumental for the COVID lockdowns that caused great harm to society. In the stellar carrier as epidemiologist he made many predictions that had been wrong by several orders of magnitude, but read for yourself.
https://statmodeling.stat.columbia.edu/2020/05/08/so-the-real-scandal-is-why-did-anyone-ever-listen-to-this-guy/