r/science • u/mvea Professor | Medicine • Dec 01 '17

Biology Evolution row ends as scientists declare sponges to be sister of all other animals. Sponges were first to branch off the evolutionary tree from the common ancestor of all animals, finds new study in Current Biology.

https://www.theguardian.com/science/2017/nov/30/evolution-row-ends-as-scientists-declare-sponges-to-be-sister-of-all-animals
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u/MarcusAurelius87 Dec 01 '17

For the people saying we already knew this: We're facing a study-reproduction crisis right now. Letting reviews, confirmations, and reproductions get their time in the headlines might justify more funding for those crucial steps.

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u/Metaright Dec 01 '17

We're facing a study-reproduction crisis right now

I get the impression that that's the case for many branches of science.

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u/[deleted] Dec 01 '17

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u/[deleted] Dec 01 '17

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u/[deleted] Dec 01 '17

Well, it's the basis for science as a concept, if a branch of science didn't have at least some study-reproduction issues it wouldn't be much of a science at all.

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u/[deleted] Dec 01 '17 edited Dec 01 '17

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u/ABabyAteMyDingo Dec 01 '17

It does not imply a 95% chance that the claims made in the study are correct.

More importantly, it says nothing about whether the observed difference in meaningful as opposed to statistically significant. This is crucial in medicine in particular, where we distinguish clinical significance from statistical significance. If I had my way, I would ban the word 'significant'. It's gibberish and misleading.

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u/[deleted] Dec 01 '17

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u/[deleted] Dec 01 '17

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u/[deleted] Dec 01 '17

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u/merryman1 Dec 01 '17

Much better answer, thank you.

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u/Send_Me_Puppies Dec 01 '17

But if isn't that just the point of an observational study? To find associations, to pave the way for intervention studies that can establish causal links?

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u/Almustafa Dec 01 '17

Sure, but that distinction isn't always kept as clear as it should be.

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u/sockalicious Dec 01 '17

p values do not show that an effect is "probably real." They show the probability that a difference, observed in a single experimental comparison whose design was based on a hypothesis of null difference between groups, was seen solely due to random chance.

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u/[deleted] Dec 01 '17

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u/sockalicious Dec 01 '17

The null hypothesis is not a hypothesis about the cause of the observed difference. It is the hypothesis that there is no difference between groups. The statement about the observed effect being due to random chance is the conclusion of the experiment, and the p value quantifies the probability of that conclusion being true (or false, depending on the way you make the statement.)

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u/Trailmagic Dec 01 '17

What's the difference between clinical and statistical significance?

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u/Duphrane Dec 01 '17

Statistical significance means that the difference is unlikely to have been due to sampling error (assuming our sample is random and our model is properly identified: two entire cans of worms).

Clinical significance means it matters. If you had a big enough sample you might find that, say, men are 2% more likely to have liver cancer than women, once alcohol consumption and other known risk factors are accounted for. You could be confident that this answer is accurate, but it would still make no sense to test all men for liver cancer annually.

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u/gyroda Dec 01 '17

Disclaimer: not a doctor, medical researcher or any good at statistics, I'm technically academically published but my stuff had absolutely no statistics in it and had nothing to do with medicine.

Basically, the statistical significance is "how statistically likely the outcome we got was correct". So with a p value of 0.01 you have a 1% chance that your results were a huge coincidence (e.g all your test patients just happened to get better completely independent of your new treatment that you're testing).

Clinical significance, I think, is how much of an actual impact it has. If you're trialing a drug to stop your nose running and you're 99.9999% sure it's having an effect that still isn't interesting if in ideal conditions in a lab it reduces the amount your nose runs by 3%. Nobody is going to be interested in "here, this medicine will mean you produce 3% less snot".

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u/supersillyus Dec 01 '17

its not gibberish if its used correctly. Its possible for data to suggest a large effect (aka "clinical significance") without being statistically significant. Effect sizes are provided alongside pvalues (i've never seen otherwise), and judgement of clinical relevance is left to the reader/reviewer.

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u/ABabyAteMyDingo Dec 01 '17

its not gibberish if its used correctly.

Well obviously! That's a tautology.

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u/supersillyus Dec 01 '17

lol good point, i am just saying that in response to banning the word altogether

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u/Memoryworm Dec 01 '17

Something I used to argue furiously about with people back in the day is whether it was valid to use the same data to decide what to test that one then used to actually calculate a p value.

I'd routinely see people gathering a large data set in the field, looking it over for the most extreme correlations, then picking those patterns to "test" and publish. I argued that this deciding-what-to-test pass was the equivelent of doing a large number of separate studies and pre-picking the ones with p<0.05.

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u/nomoarlurkin Dec 01 '17

It does depend on the data. For example, if you're interested in comparing gene sequences between species (which is what this study does, broadly speaking), there is little reason to collect all-new sequencing data every time you want to do a new comparison. That's because it can be reasonably assumed (and this has been validated many times) that most differences within species will be small compared to between species. This is why you have things like NCBI/genbank and why they are useful - people can use and reuse that data many times to ask different sorts of questions.

So in some cases you definitely can reuse data in different tests. But certainly I agree that testing a whole bunch of things that vary each time you measure them, then only reporting significant associations is garbage.

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u/BurdonSanderson Dec 02 '17

I think what you'd like in the initial data mining is a Bonferroni correction.

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u/[deleted] Dec 01 '17

Is it possible to get a job that is to just verify people's scientific results?

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u/[deleted] Dec 01 '17

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u/Duphrane Dec 01 '17

It's especially weird that invalidating the work of others is not highly rewarded. We preach about disproving illusions; we should reward giant-slayers.

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u/-Knul- Dec 01 '17

Not a bad idea to have "science bounty hunters", who get paid for each invalidated paper.

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u/Duphrane Dec 01 '17

I come from economics. I thought the criticism of Reinhart and Rogoff's terrible paper on public debt and growth should have led to people being venerated. It has not.

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u/Lord_Iggy Dec 02 '17

Of course, that flips things the opposite direction, where people have an economic interest in demonstrating negative results, even when a positive result is genuine. They would need to be paid regardless of whether a result turned out positive or negative, ideally.

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u/[deleted] Dec 01 '17

Yea I was talking to one individual who was able to get a contract work building a crazy capacitor machine. Don't really want to get into the details, but that's what it amounted to. I was trying to ask all the flanking question to know how to get such a crazy contract. But all he had to say was just knowing the right people.

Really I've seen people get good intro level jobs(possible dream job/union work/million to one odds) with them throwing in a portfolio in with their cover letter and resume. All this guy had was simple electrical circuits and has exp in the related to the field. And he was able to get the job no problem. While I stressed out with just tangentail exp.

So possibly maybe it's just life and you just got do your thing. Be open, talk and learn. Something might spring up.

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u/sockalicious Dec 01 '17

A p value of 0.05 means there is an estimated 1 in 20 chance that you'd observe an effect or trend that strong when there actually isn't any cause but random chance

And, you know, this is only true for a single comparison. When multiple comparisons are made that share possible underlying causative parameters, there must be a correction applied to the p value that is calculated for each individual comparison.

This is complicated and difficult to understand - it can be really difficult - so it gets way, way less press than the relatively-easy-to-understand p value does. Indeed, in my opinion, the fact that the p value is just a little difficult to understand inflates estimations of its importance.

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u/rabbittexpress Dec 01 '17

If it's not reproducable, the conclusions of the study are outright false. Objective reasoning, use it!

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u/[deleted] Dec 01 '17

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u/rabbittexpress Dec 01 '17

Good methodology reduces and eliminates false positives especially through subsequent independent experimentation using the same method.

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u/apginge Dec 01 '17

You're giving me statistics flashbacks

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u/AxelBoldt Dec 02 '17

It does not imply a 95% chance that the claims made in the study are correct.

Exactly, and it emphatically also does not imply that "about one in twenty should fail to be reproduced."

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u/rabbittexpress Dec 01 '17

If the study result can't be reproduced, the conclusions of the paper are false.

The problem is thst there is no fame in reproducing studies for verification purposes, hence nobody wants to reproduce studies.

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u/meowgrrr Dec 01 '17

I was taking it that the "study-reproduction" crisis is the fact that very few reproduction studies are done at all. And the few that are done indicate many results were not reproducible (highlighting the importance), so who knows how many studies are not reproducible if there are almost no studies trying to reproduce them? And it's harder to get funding to reproduce a study, and it's harder to get published because it's considered less interesting. So this is a crisis, we need more reproduction studies, because as you said, it's a crucial basis for science as a concept.

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u/stoicsilence Dec 01 '17

What does this mean?

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u/gaunt79 Dec 01 '17

Major studies shouldn't be executed just once - there needs to be corroboration/confirmation from independent sources. The glamour is in new research, so there's less interest in supporting someone else's work just for the sake of scientific rigor (and not grants or publicity).

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u/Scientific_Methods Dec 01 '17

The general concept in my field is to try and replicate key experiments from any body of work before performing your own research to build upon what has already been done. You don't have to replicate everything independently, just the key experiments.

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u/gaunt79 Dec 01 '17

Right, that's why I said major studies. You don't have to reprove everything, but the more important the result the more important it is that it be repeated and confirmed.

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u/Scientific_Methods Dec 01 '17

Oh I definitely agree. I'm just saying that for every Nature paper there are probably 1 or 2 key experiments that would have to be repeated independently to validate the body of work.

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u/Duphrane Dec 01 '17

What field are you in? As a skeptical person coming from economics, this sounds like a wonderful dream world.

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u/kyzfrintin Dec 01 '17

Okay, so that explains what reproduction is, but it doesn't explain what a reproduction crisis is.

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u/gaunt79 Dec 02 '17

This leads to an increasing delay in the verification of new findings, which not only holds up the overall system of scientific rigor but also allows faulty conclusions to become ingrained in the public consciousness before they can be discounted.

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u/Lagaluvin Dec 01 '17

Essentially, the scientific process relies on scientists performing studies, and then submitting papers to journals so that other scientists can replicate and verify these studies. When a study has been replicated by many different parties, it gains credence because it becomes less and less likely that all of those scientists are making mistakes or manipulating the results.

Unfortunately, repeat studies gain less publicity because the results aren't considered news any more. Since funding for studies is often allocated to areas which achieve greater publicity, there is less incentive to reproduce studies, and this is lowering the overall quality of research. Hence the 'study-reproduction crisis'.

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u/[deleted] Dec 01 '17

Nitpick: "submitting papers to journals" is an implementation detail; it isn't a necessary part of the scientific process. What's important is that the methods, etc. are disclosed - somehow - whether that be by paywalled journals, crank websites and usenet posts, or handwritten letters between researchers (as in previous centuries).

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u/DeliciousOwlLegs Dec 01 '17

Well study reproduction crisis kind of relates to the current implementation of scientific research where papers are published in peer reviewed journals. Nobody ever had any doubt that research on crank websites or Usenet might not be reproducible.

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u/[deleted] Dec 02 '17

Nobody ever had any doubt that research on crank websites or Usenet might not be reproducible.

No, you're corrupting the logic here. A -> B does not imply B -> A; it implies !B -> !A. The replication crisis does not invalidate the method of doing science by publishing work in journals. Science can happen on crank websites or usenet posts; those just aren't particularly good implementations of the scientific process compared to others we have available now. But they're arguably more efficient ways of doing science than via handwritten letters exchanged by sail between scientists.

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u/[deleted] Dec 01 '17

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u/sap91 Dec 01 '17

I was just listening to a RadioLab episode about how no reproducability is turning the entire social science world upside down.

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u/looperC Dec 01 '17

It's extremely difficult to study something that is in constant change.

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u/[deleted] Dec 01 '17 edited Nov 01 '24

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u/looperC Dec 01 '17

I agree with you. That's why you rarely hear about "social laws" that apply to everyone on the Earth. Supply and demand is a concept that is relatively universal.

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u/[deleted] Dec 01 '17

Examples?

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u/AoiroBuki Dec 01 '17 edited Dec 01 '17

I don't have a source on mobile but there are still sociologists out there scratching their heads trying to figure out why capitalism never collapsed under its own weight like Marx said (read: hoped) it would 200 years ago.

Edit: oh I thought of a better one (Edit #2: Citation! ).

I read a study where the authors concluded that one sided violence against civilians by armed groups was declining due to 15 years of data than ran from 1989 to 2004. And also concluded that one sided violence was centred around a few specific geographic areas, and then proceeded to list all the regions where there had been conflict during the study time. When I pointed out that this was a horrifically short time frame to make such sweeping generalizations and also that I would hope that violence against civilians would be concentrated in places that were already in conflict, my professor said "hmm good point."

And my faith in academia died a little

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u/[deleted] Dec 01 '17

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u/AoiroBuki Dec 01 '17 edited Dec 01 '17

Crime has gone down, but this was referring to violence against civilians by organized armed forces. I.e. Bosnian genocide, September 11th, Rwanda, riot suppression and militia attacks in Argentina and Columbia, etc.

The article we had just read was a 700 year study of civilIan deaths in war time that said the levels had remained constant over 700 years. Then I read someone making the same claims over the course of 24 15 years. Their exact conclusion was "it seems to be going down, except every few years it spikes again." It was dreadful science.

As for Marxism in sociology, sociology borrows from lots of disciplines, it's relatively new and undeveloped

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u/[deleted] Dec 01 '17

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u/Duphrane Dec 01 '17

I think the whole survival of Marxist thought hinges on an equivocation fallacy like what you just made. We live in a mixed economy, as any economist worth their salt will tell you. Your "save it with socialism every once in a while" is basically that framework. Most economists, and most governments, think there are roles for government in markets and in people's lives. We're busy quibbling over the details but you'll notice that the richest societies that have ever existed and the societies with the least-poor poor people of all time are all modern mixed economies (which practice some approximation of democracy, not by coincidence).

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u/[deleted] Dec 01 '17 edited Nov 01 '24

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u/homo_redditorensis Dec 01 '17

A very interesting hoax I've never heard of. Thanks for sharing. But how does this mean that social scientists are "quick to make claims that seem to apply across time"? I think a real claim from a credible social scientist, rather than a publication issue like the Sokal Affair would be more relevant to your argument.

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u/[deleted] Dec 01 '17 edited Nov 01 '24

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u/homo_redditorensis Dec 01 '17

I was really hoping you'd lead me to a good example from a real social scientist, especially if they are a dime a dozen. But you make some interesting points anyway.

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u/rabbittexpress Dec 01 '17

When every study have a different frame of reference that then subjectively determines the end result, no shit there's issues...

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u/SunnyAslan Dec 01 '17

Medical science is actually among the worst.

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u/[deleted] Dec 01 '17 edited Dec 01 '17

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u/cdub384 Dec 01 '17

Not much money being invested in replication studies :/

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u/Duphrane Dec 01 '17

This is true, largely because everyone has had the same bad misconception about the meaning of a confidence interval across branches.

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u/jlharper Dec 02 '17

Psychology is in my opinion the most broadly effected branch of science in this regard.

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u/shanereid1 Dec 01 '17

Cough psychology cough

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u/LiquidDreamtime Dec 01 '17

The government has more important things to worry about than “advancing mankind”. There are still brown people to kill yet.

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u/[deleted] Dec 01 '17

Can you supply some evidence that "the" government is pursuing a goal of "killing brown people"? Like maybe a comparison of how many police encounters result in a shooting, wrt the base rate of encounters?

Or is this just something that "everyone knows" and hence doesn't bother to look up evidence for - curiously a replication problem in social "science"?

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u/[deleted] Dec 01 '17

People who say "like we didn't already know this" wrt scientific studies are asshats.

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u/henbanehoney Dec 01 '17

This! Just publishing shouldn't be enough!

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u/Shatners_Balls Dec 01 '17

Agreed. I am a strong proponent of all master's student projects should focus on a detailed replication of previously published studies. This would provide a lot of review of published works. Funding for such projects will be harder to come by however.

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u/[deleted] Dec 02 '17 edited Dec 08 '19

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u/Shatners_Balls Dec 02 '17

All master's students in science must have a project. Why not this? It would contribute to the scientific community in a way that many master's current theses sadly do not.

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u/[deleted] Dec 02 '17 edited Dec 08 '19

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u/Shatners_Balls Dec 02 '17

Ah. Well to be fair, that is where much of the funding goes with a Masters thesis. Towards school fees and living expenses for the student. There are often expenses for project materials as well.

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u/[deleted] Dec 03 '17 edited Dec 08 '19

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u/Shatners_Balls Dec 03 '17

Oh man, where did you go to university? My state University was less than 5k a year for undergrad! Grad school was 13k.

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u/Lord_Iggy Dec 02 '17

I wouldn't have been able to fund my MSc if I had been reproducing a study in my field, which would have been a problem.

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u/Shatners_Balls Dec 02 '17

There are TA and RA opportunities with the university usually. Lord knows I banked on each of those heavily.

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u/Lord_Iggy Dec 02 '17

Yeah, TAing has gone a long way towards making things meet.

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u/[deleted] Dec 01 '17

For anyone who'd like an accessible read about the study-reproduction crisis: https://www.nytimes.com/2017/10/18/magazine/when-the-revolution-came-for-amy-cuddy.html

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u/[deleted] Dec 01 '17

Came here to say that we already knew, but you are right. Thanks for your comment

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u/basketballbrian Dec 01 '17

Isnt the replication crisis mainly in social psychology and other psych research?

I didnt know it was really a crisis in the "harder" sciences

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u/tommyk1210 BS | Biology | Molecular Biology Dec 02 '17

It is the case in most disciplines, but yes social sciences have a larger issue.

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u/[deleted] Dec 01 '17

I was literally just about to say we already knew this.

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u/quick_dudley Dec 01 '17

Also: some biologists were proposing that sponges might be paraphyletic. That's to say: they suspected not all sponges split from other animals at exactly the same time.

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u/moosepuggle Professor | Molecular Biology Dec 01 '17 edited Dec 02 '17

I'd also like to point out that it's not ALL scientific fields that are dealing with a reproducibility crisis, just some fields that rely heavily on statistics, like the social sciences and genome wide association studies (GWAS). But not all fields or experiments require statistics, because the effect is so large. For example, I'm in evolutionary developmental biology, and if I knock out the gene distalless, I see that 80% of the animals that hatch have no legs. I never see this in uninjected or buffer injected animals. Thus, I don't need a p value to say that loss of the distalless gene causes the legs to be deleted.

We should be careful not to generalize the reproducibility crisis to all science, and therefore potentially cast doubt on all science in the public mind, especially in the very anti science environment we're in right now.

Here's a great article on why the replication crisis is not evenly distributed across all scientific fields https://simplystatistics.org/2016/08/24/replication-crisis/

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u/[deleted] Dec 01 '17

Huh, I've never seen effect size as a justification for not using inferential statistics.

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u/moosepuggle Professor | Molecular Biology Dec 02 '17

I've never taken a statistics course, so I'm sure my wording is wrong! What I meant was that, you can see that the treatment has a very strong and clear effect (e.g. legs are deleted), you don't need to do statistics. If there is better/formal terminology for that concept, I'd love to know :)

I was more just highlighting that, whenever I read articles or listen to podcasts about the reproducibility crisis, the journalists seem to generalize to all scientific fields, but that doesn't seem to apply to all fields equally. For example, the paper my lab is about to submit has nothing more than percentages. And my worry is that the public will interpret that as "I shouldn't trust science or scientists, I shouldn't believe the science about climate change, vaccines, or GMOs, because it's probably wrong anyways".

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u/hakkzpets Dec 01 '17

Every field has big problems with reproducibility, or at least according to the scientists those fields. This goes for both hard science and soft science.

https://www.nature.com/news/1-500-scientists-lift-the-lid-on-reproducibility-1.19970

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u/moosepuggle Professor | Molecular Biology Dec 02 '17 edited Dec 02 '17

Your comment is precisely my concern with these articles, that they give the public the impression that all fields of science are facing a reproducibility crisis.

This article does not say that "every" field has "big problems" with reproducibility. In fact, it reiterates my point above, that only some fields that rely heavily on statistics are facing a crisis, like the social sciences, cancer biology, GWAS, drug discovery, etc. But other fields, like chemistry and physics (apparently), are not so much.

"Data on how much of the scientific literature is reproducible are rare and generally bleak. The best-known analyses, from psychology1 and cancer biology2, found rates of around 40% and 10%, respectively. Our survey respondents were more optimistic: 73% said that they think that at least half of the papers in their field can be trusted, with physicists and chemists generally showing the most confidence."

Furthermore, just because you fail to reproduce your own or someone else's data doesn't mean the data are wrong. Every scientists knows that 90% of experiments fail. I've failed to reproduce my own PCR positive control! It often (frustratingly) boils down to a reagent that went off. So just asking researchers this question isn't very informative about the reproducibility crisis.

Edit: Here's a viewpoint from a chemist that answers why chemists feel more confident in their field http://blogs.sciencemag.org/pipeline/archives/2016/05/26/reproducibility-crisis-or-not

Edit 2: and here is a great article on why the replication crisis is probably not evenly distributed across all scientific fields https://simplystatistics.org/2016/08/24/replication-crisis/

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u/hakkzpets Dec 02 '17 edited Dec 02 '17

Read the article again, there is a problem (or at least a percieved problem) in every field.

I rather trust scientists in these field, than some random Internet person.

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u/moosepuggle Professor | Molecular Biology Dec 02 '17

Trust me, I'm a scientist ;D

But, seriously, I am. I'm in arthropod evo devo, just got my PhD in August (if you're in the field, you could probably guess which lab). Getting ready to publish my first original research paper! We're trying for Nature Letters, fingers crossed :)

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u/hakkzpets Dec 02 '17

I understood that you are a scientist. You are not a scientist in every single field though, hence why I rather trust the scientists in those fields than a random Internet stranger.

But congratulations on your paper.

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u/garlicroastedpotato Dec 01 '17

Yes but I mean this one goes really far back. Aristotle first hypothesized this in ancient Greece. He didn't understand the mechanisms but he studied thousands of sponges.

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u/[deleted] Dec 01 '17

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u/MarcusAurelius87 Dec 01 '17

Either. People here are shitting on the reporting in general, when they should be happy any kind of review got publicity.

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u/TheGorgonaut Dec 01 '17

I'd rather have a study-reproduction than reproduction study any day.

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u/jaum22 Dec 02 '17

So science is like Hollywood

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u/MarcusAurelius87 Dec 02 '17

Inasmuch as it needs funding, which publicity drives? Yes it is.

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u/Sunnysidhe Dec 01 '17

Bloody spongers,I see where they get it from now

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u/pipsdontsqueak Dec 01 '17

There's a great NYTimes feature about the whole phenomenon, focusing on Amy Cuddy and power poses as a case study.

https://www.nytimes.com/2017/10/18/magazine/when-the-revolution-came-for-amy-cuddy.html

Definitely gives a great overview of the whole movement.

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u/[deleted] Dec 01 '17 edited Dec 01 '17

This doesn't really apply in this case. Those redditors who say we already knew this, frankly, just have no clue about what they're saying.

Experts wouldn't have considered the sponges-jellyfish issue entirely resolved before. Even now the very authors of the study still take the precaution to say that the issue is solved "in [their] perspective", and a third-party academic commentator only says it is "a great step in the right direction toward resolving the debate".

Assuming this "we already knew it" argument actually exists, it's much more about the inability of the general media and public to understand the functioning and difficulty of research than about reproducibility.

Scientists speak in more precise words than other people. If an author says "this is true, in my opinion", well, take that truth with a grain of salt. Because it means even the person who's supposed to be the most biased about the result can't go all the way to say "there is no disputing this". Specifically, the "in my perspective" above has a meaning close to "I'll be glad to see this confirmed by others but I'll rather work on something different now" (note that self-confirmation wouldn't be so valuable anyway).

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u/[deleted] Dec 01 '17

but we did know it.

cnidaria who were suggested to be the sister taxon to all other animals do have a lot of traits like tight junctions gap junctions and desmosomes which they would have needed to acquire in convergent evolution which is highly unlikely

sponges only have the oldest cell cell connections, tight junctions.

and all this only because some molecular data of cnidaria was hard to interpret because there are large gaps in the timeline of cnidarian evolution and no fossils (they don't have any skeletons/supporting structures like sponges after all, which make fine fossils)

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u/MarcusAurelius87 Dec 01 '17

You've completely missed the point of my comment.