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Here's where I'm at dude. You are quoting at me the guy who talks about science for Nerdist.com (a nice guy but someone with a bachelor's in civil and environmental engineering and a masters in science communication) to disprove the conclusions made by a professor of psychology at University of Washington who's published 50 publications within the last ten years, been cited more than 4000 times, and has a plethora of awards including a genius grant. Take this from a scientist, this lady is a rising star in her field and I would need quite a bit of evidence before I believe she's just a dipshit who doesn't know how to analyze her own data.
I mean just look at this shit: https://scholar.google.com/citations?hl=en&user=4hwc6fwAAAAJ
This is a person that lives and breathes this kind of analysis every second of every day. To think you or I can come into her field and assume we know better than her and the peers in her field that reviewed her manuscript and approved it for a reputable journal is just nuts.



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Torillian said:

Here's where I'm at dude. You are quoting at me the guy who talks about science for Nerdist.com (a nice guy but someone with a bachelor's in civil and environmental engineering and a masters in science communication) to disprove the conclusions made by a professor of psychology at University of Washington who's published 50 publications within the last ten years, been cited more than 4000 times, and has a plethora of awards including a genius grant. Take this from a scientist, this lady is a rising star in her field and I would need quite a bit of evidence before I believe she's just a dipshit who doesn't know how to analyze her own data.
I mean just look at this shit: https://scholar.google.com/citations?hl=en&user=4hwc6fwAAAAJ
This is a person that lives and breathes this kind of analysis every second of every day. To think you or I can come into her field and assume we know better than her and the peers in her field that reviewed her manuscript and approved it for a reputable journal is just nuts.

I'll just chime in real quick to say that you are in fact, very right about all of this.

P value is not "margin of error" it is a statistical test of a hypothesis. When the p value is greater than 0.05, that indicates that the results found would not be unsurprising if the null hypothesis were true. That fact is the very fact that the paper that I posted is highlighting: That there is no statistically significant difference between transgender (with social transitioning) and non-transgender populations in relation to certain highlighted factors. A confirmation of a null hypothesis is just a scientifically important as a confirmation of a hypothesis. 



Torillian said:

Here's where I'm at dude. You are quoting at me the guy who talks about science for Nerdist.com (a nice guy but someone with a bachelor's in civil and environmental engineering and a masters in science communication) to disprove the conclusions made by a professor of psychology at University of Washington who's published 50 publications within the last ten years, been cited more than 4000 times, and has a plethora of awards including a genius grant. Take this from a scientist, this lady is a rising star in her field and I would need quite a bit of evidence before I believe she's just a dipshit who doesn't know how to analyze her own data.
I mean just look at this shit: https://scholar.google.com/citations?hl=en&user=4hwc6fwAAAAJ
This is a person that lives and breathes this kind of analysis every second of every day. To think you or I can come into her field and assume we know better than her and the peers in her field that reviewed her manuscript and approved it for a reputable journal is just nuts.

I think he has a valid reason to be skeptical

the social sciences have recently been shown to be overrun with leftist ideology to the point where nonsense like this is seen as valid

https://www.barstoolsports.com/chicago/fake-study-saying-dog-parks-are-cesspool-for-rape-culture-earns-real-award-and-now-author-is-in-real-trouble

the tilt further and further left has been documented by even left leaning sources

https://www.insidehighered.com/news/2017/02/27/research-confirms-professors-lean-left-questions-assumptions-about-what-means

and I suppose for people who lean left to begin with this may not be seen as an issue but it obviously is because what is researched and how much certain conclusions are challenged is obviously going to be adversely impacted



o_O.Q said:

I think he has a valid reason to be skeptical

the social sciences have recently been shown to be overrun with leftist ideology to the point where nonsense like this is seen as valid

https://www.barstoolsports.com/chicago/fake-study-saying-dog-parks-are-cesspool-for-rape-culture-earns-real-award-and-now-author-is-in-real-trouble

the tilt further and further left has been documented by even left leaning sources

https://www.insidehighered.com/news/2017/02/27/research-confirms-professors-lean-left-questions-assumptions-about-what-means

and I suppose for people who lean left to begin with this may not be seen as an issue but it obviously is because what is researched and how much certain conclusions are challenged is obviously going to be adversely impacted

Bad journals exist everywhere.

They are not evidence that the social sciences as a whole are worthless.

This argument is bad.

EDIT: Yeahhhhh...



Torillian said:
DarkD said:

The P-value means the margin for error in the conclusions drawn.  So a .05 means it's acceptable as scientific evidence.  Anything above that makes it unacceptable.  You can still draw conclusions from it, but it will not be taken as scientific evidence unless the p-value is lower than .05.  

The study has such a bad p-value because the sample size is so small.  Only like 50 patients.  Even a sample of 1000 patients would be iffy by these standards and may not pass the p-value test.  So yea, the study doesn't mean anything.  

In fact, the conclusions with the best p-value are the conclusions that favor the conservative point of view.  "Trans reported marginally higher anxiety compared to the control group p=0.076" and "trans reported marginally higher anxiety than the national average =0.096" and finally, the only scientifically relevant fact present "parents reported their children had more anxiety than children in the control groups =0.002"

So the only facts this study brought to the table are that trans children have anxiety problems.  

Alright I'll try this once more. The P-value in these studies is an attempt to show a statistically significant difference between the groups investigated. Larger p-values mean there are not statistically significant differences for that value. There is no way that the statement "these two groups have similar depression levels" could be proven by a low p-value because a low p-value would show a difference between the two groups. The fact that the two groups had high p-values for the measured value of depression is the reason they conclude the two groups have the same level of depression. If the p-value had been low then they would conclude that the two groups are different. There is no way to conclude the two groups are the same with a low p-value, it's just not how the analysis works.

That is my reading on how the studies are designed, if you have more information on this than I I'd be interested in hearing it, but simply repeating the idea that only conclusions with low p-values are valid is meaningless. p-value is not "the error in the conclusions drawn", but a means of showing whether a null hypothesis has been disproven. If the null hypothesis is that the two groups are the same, and your p-value is high this means that the two groups are not different to a statistically significant degree. This is what the study stated. 

So, given my reading of the study, what are your credentials to be discrediting the analysis of experts in their field? Because I'm pretty sure these guys understand P-values much better than you or I. 

Here's some info to back up my interpretation:

https://www.biochemia-medica.com/assets/images/upload/xml_tif/Marusteri_M_-_Comparing_groups_for_statistical_differences.pdf

You're right in that a high p-value validates the null hypothesis.  But the value in that study isn't high enough to validate the null hypothesis either.  Just do 1-P and you are back to proving how worthless the study is. In your case, you'd have to prove p>=0.95 to validate the claims.  

  



o_O.Q said:
Torillian said:

Here's where I'm at dude. You are quoting at me the guy who talks about science for Nerdist.com (a nice guy but someone with a bachelor's in civil and environmental engineering and a masters in science communication) to disprove the conclusions made by a professor of psychology at University of Washington who's published 50 publications within the last ten years, been cited more than 4000 times, and has a plethora of awards including a genius grant. Take this from a scientist, this lady is a rising star in her field and I would need quite a bit of evidence before I believe she's just a dipshit who doesn't know how to analyze her own data.
I mean just look at this shit: https://scholar.google.com/citations?hl=en&user=4hwc6fwAAAAJ
This is a person that lives and breathes this kind of analysis every second of every day. To think you or I can come into her field and assume we know better than her and the peers in her field that reviewed her manuscript and approved it for a reputable journal is just nuts.

I think he has a valid reason to be skeptical

the social sciences have recently been shown to be overrun with leftist ideology to the point where nonsense like this is seen as valid

https://www.barstoolsports.com/chicago/fake-study-saying-dog-parks-are-cesspool-for-rape-culture-earns-real-award-and-now-author-is-in-real-trouble

the tilt further and further left has been documented by even left leaning sources

https://www.insidehighered.com/news/2017/02/27/research-confirms-professors-lean-left-questions-assumptions-about-what-means

and I suppose for people who lean left to begin with this may not be seen as an issue but it obviously is because what is researched and how much certain conclusions are challenged is obviously going to be adversely impacted

Political leanings have nothing to do with this. He is wrong about how P-values are used. Doesn't matter if this lady is the sjw queen of the blue haired screechers or a pundent for Fox News, she is not wrong because her P-values are too high. If there are other concerns I'm happy to hear them but "P-values are too high" is just crap. 



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sundin13 said:
o_O.Q said:

I think he has a valid reason to be skeptical

the social sciences have recently been shown to be overrun with leftist ideology to the point where nonsense like this is seen as valid

https://www.barstoolsports.com/chicago/fake-study-saying-dog-parks-are-cesspool-for-rape-culture-earns-real-award-and-now-author-is-in-real-trouble

the tilt further and further left has been documented by even left leaning sources

https://www.insidehighered.com/news/2017/02/27/research-confirms-professors-lean-left-questions-assumptions-about-what-means

and I suppose for people who lean left to begin with this may not be seen as an issue but it obviously is because what is researched and how much certain conclusions are challenged is obviously going to be adversely impacted

Bad journals exist everywhere.

They are not evidence that the social sciences as a whole are worthless.

This argument is bad.

EDIT: Yeahhhhh...

the men who wrote that journal apparently got 20 or so journals through

the thing is that they were trolling, but there are several journals floating around out there that are proposing things that are just as fucking retarded from people who apparently are sincere and happen to be toeing the line with the dominant ideology

IT IS a massive problem in the social sciences now

does it mean as you have strawmanned me as saying that the social sciences are worthless as a whole? not necessarily, but it does mean that conclusions in my opinion should be taken with a grain of salt and for individual people when it comes to topics like this where clearly there are MASSIVE GLARING INCONSISTENCIES then perhaps should take their time before accepting things blindly(especially when those things in some respects do not logically fit together)



sundin13 said:
Torillian said:

Here's where I'm at dude. You are quoting at me the guy who talks about science for Nerdist.com (a nice guy but someone with a bachelor's in civil and environmental engineering and a masters in science communication) to disprove the conclusions made by a professor of psychology at University of Washington who's published 50 publications within the last ten years, been cited more than 4000 times, and has a plethora of awards including a genius grant. Take this from a scientist, this lady is a rising star in her field and I would need quite a bit of evidence before I believe she's just a dipshit who doesn't know how to analyze her own data.
I mean just look at this shit: https://scholar.google.com/citations?hl=en&user=4hwc6fwAAAAJ
This is a person that lives and breathes this kind of analysis every second of every day. To think you or I can come into her field and assume we know better than her and the peers in her field that reviewed her manuscript and approved it for a reputable journal is just nuts.

I'll just chime in real quick to say that you are in fact, very right about all of this.

P value is not "margin of error" it is a statistical test of a hypothesis. When the p value is greater than 0.05, that indicates that the results found would not be unsurprising if the null hypothesis were true. That fact is the very fact that the paper that I posted is highlighting: That there is no statistically significant difference between transgender (with social transitioning) and non-transgender populations in relation to certain highlighted factors. A confirmation of a null hypothesis is just a scientifically important as a confirmation of a hypothesis. 

The p-value has two tails.  It either has to be above .95 to validate the null hypothesis or below .05 to validate the alternate hypothesis.  Your study simply put isn't large enough to achieve either of the two goals.  All it's doing it stoking politics.  It's simply something for the news magazines to write about and claim they're right with.  It doesn't prove anything.  

The intention of posting a study like this is to show other scientists "interesting things" they may wanna perform larger studies on.  I don't even think this should be visible to the public as all it's doing is showing us some very early results.  

And @Torillian No one is claiming this scientist is a nut job.  I'm just stating that this isn't something you can shove at someone and say "this proves I'm right".  Because that's not what it's supposed to do.  Its meant for other researchers who wanna perform larger studies on transgenders.  



DarkD said:
Torillian said:

Alright I'll try this once more. The P-value in these studies is an attempt to show a statistically significant difference between the groups investigated. Larger p-values mean there are not statistically significant differences for that value. There is no way that the statement "these two groups have similar depression levels" could be proven by a low p-value because a low p-value would show a difference between the two groups. The fact that the two groups had high p-values for the measured value of depression is the reason they conclude the two groups have the same level of depression. If the p-value had been low then they would conclude that the two groups are different. There is no way to conclude the two groups are the same with a low p-value, it's just not how the analysis works.

That is my reading on how the studies are designed, if you have more information on this than I I'd be interested in hearing it, but simply repeating the idea that only conclusions with low p-values are valid is meaningless. p-value is not "the error in the conclusions drawn", but a means of showing whether a null hypothesis has been disproven. If the null hypothesis is that the two groups are the same, and your p-value is high this means that the two groups are not different to a statistically significant degree. This is what the study stated. 

So, given my reading of the study, what are your credentials to be discrediting the analysis of experts in their field? Because I'm pretty sure these guys understand P-values much better than you or I. 

Here's some info to back up my interpretation:

https://www.biochemia-medica.com/assets/images/upload/xml_tif/Marusteri_M_-_Comparing_groups_for_statistical_differences.pdf

You're right in that a high p-value validates the null hypothesis.  But the value in that study isn't high enough to validate the null hypothesis either.  Just do 1-P and you are back to proving how worthless the study is. In your case, you'd have to prove p>=0.95 to validate the claims.  

  

That doesn't really make sense. To restate what a p-value indicates: P values indicate the odds of seeing the results given the alternate hypothesis being true. A large p-value would require an almost entirely uniform sample and would not exist in circumstances where you have natural variability. As such, the "1-p" calculation is not really something that is done except perhaps in some fringe scenarios where you are trying to prove some uniformity. Further, you talk about "validating the null hypothesis". That also doesn't really make sense, as the null hypothesis exists as a rejection of the alternate hypothesis. To try to assert that something is statistically significantly insignificant is kind of nonsense.

To quote this study: https://www.ncbi.nlm.nih.gov/pubmed/15080563

"In randomized controlled trials, main endpoint p-values larger than p=0.95 will be rare, because they would indicate similarities closer than compatible with a normal distribution of random data samples."



Torillian said:
o_O.Q said:

I think he has a valid reason to be skeptical

the social sciences have recently been shown to be overrun with leftist ideology to the point where nonsense like this is seen as valid

https://www.barstoolsports.com/chicago/fake-study-saying-dog-parks-are-cesspool-for-rape-culture-earns-real-award-and-now-author-is-in-real-trouble

the tilt further and further left has been documented by even left leaning sources

https://www.insidehighered.com/news/2017/02/27/research-confirms-professors-lean-left-questions-assumptions-about-what-means

and I suppose for people who lean left to begin with this may not be seen as an issue but it obviously is because what is researched and how much certain conclusions are challenged is obviously going to be adversely impacted

Political leanings have nothing to do with this. He is wrong about how P-values are used. Doesn't matter if this lady is the sjw queen of the blue haired screechers or a pundent for Fox News, she is not wrong because her P-values are too high. If there are other concerns I'm happy to hear them but "P-values are too high" is just crap. 

you misunderstand me, i'm simply offering a reason for why he's skeptical of the research conclusions to begin with

he may very well be wrong when it comes to pee values, but what i'm saying is that he's trying to justify a lack of trust in social sciences that is to some extent valid

the social sciences are losing credibility right now and he's right to be wary when it comes to conclusions coming out of that field