The Problem of Bad Research!

Patrick’s Books:

John ioannidis published an essay titled “why most published research findings are false”, where he showed that the results of many medical other researchers. this is obviously a problem! 70% of researchers have tried and failed to reproduce another scientist’s experiments, not only that, but more than half admit

To having during a decade as head of global cancer research at amgen, c. glenn begley identified 53 “landmark” reputable labs — for his team to reproduce. he sought to double-check the findings before trying to build on them for drug development. replicated, causing huge problems for those trying so, what

Might be causing this problem? well, part way through his project to reproduce these landmark cancer studies, begley met with the lead he told the scientist that he had gone through re-did the experiment 50 times and never got that they’d done the experiment six times, such selective publication is just

One is peppered with incorrect results. many blame the hypercompetitive academic diminishing funding. the surest ticket to getting a grant or a good job is getting published in a high-profile journal, and this can lead obviously, this is most concerning in the world of medicine, but the same problem incredibly

Influential and commonly accepted in 2011, joseph simmons, a psychologist at the university of pennsylvania, published a paper in the journal psychological science, where he showed that people who listened to the beatles song “when i’m sixty-four” grew younger, by nearly 18 months. the result was obviously ridiculous but the

Point the paper made was serious. it showed how standard scientific methods, when abused could generate scientists have been shocked to discover that what they used to consider reasonable research practices were flawed and likely to generate labeled the “replication crisis” by the press. campbell harvey,

A professor of finance at duke university argues that at least half of the 400 supposedly market-beating strategies identified in top financial journals over the years are false. with the replication crisis in finance is to accept that there is a crisis. and right now, harvey is the former editor of the journal

Of finance, a former president of the american finance association, and an adviser to investment he has written more than 150 papers on finance, prizes. this is not like a child saying criticism of the rigor of academic research obviously, the stakes of the replication crisis are much higher in medicine, where

People’s health can be at risk than in the world of finance, but flawed financial research is often pitched to the public either through the press or by fund management companies looking to raise assets. people’s portfolios and can affect their while ioannidis’s 2005 paper has been criticized

Over time for its use of dramatic and exaggerated language, most academics do agree with his paper’s conclusions and its recommendations. so, lets in statistics, we don’t try to prove that something is definitely true, instead we show how unlikely it is that we would have found our test results if the underlying process

Was random, this approach is based on the principle of we can never prove that something is definitely true, we can only prove that something is false. statistical hypothesis tests thus, never prove a model is correct, they instead show how unlikely it is that we would have gotten our test results if the

Idea being tested was incorrect. hypothesis testing is the evidence against a null hypothesis. the smaller the p-value, the stronger the evidence is that our results are whether a given drug is actually helpful, or in finance if cheap stocks outperform over time. p-values less than .05 are generally considered they

Tell us that there is a 5% chance that our results can be attributed to randomness. this 5% threshold was picked by ronald fisher – an important statistician in a book he published the term p-hacking, describes the deliberate or accidental manipulation of data in a study until it produces a sufficient p-value. it is

The misuse of data analysis to find patterns in data that can be presented as statistically significant, thus dramatically increasing and understating the risk of false positives. if you took random data and tested enough hypothesizes on it, you would eventually come up with a study that appears to harvey

(The former editor of the journal of finance who we mentioned earlier) attributes the scourge of p-hacking to incentives in academia. finding published in a prestigious journal can earn an ambitious young professor the ultimate academic prize — tenure. wasting months of work on a theory that does not hold up

To scrutiny would frustrate anyone. it is therefore tempting to torture the data until it yields something interesting, even if other researchers are later papers, in fact their careers depend on it; “there is no cost to getting things wrong, but isn’t science supposed to self-correct by having other

Scientists replicate the findings of an initial discovery? it is a lot less glamorous scientists want to find their own breakthrough, additionally, many journals don’t publish replication studies. so, if you’re a scientist the successful strategy is clear, don’t waste your time on replication studies, do the kind

Of work that will get you published, and if you can find a result that is surprising and unusual, maybe it will get picked up in the popular press too. now i don’t want this to be seen as a negative piece on science or the scientific method, because people are more aware of this problem today than in the past and things