New study shows leg flexion less efficient than extension.

[FrankDay]

Re: Re:

...
This is true Jay, notice it only refers to the result under a certain condition, it does not refer to the likelihood of a hypothesis being true or false,
...
He was attempting to use the p-value to assign a probability that the hypothesis is true. This is categorically wrong. This statistic cannot attach probabilities to hypotheses. This is clearly stated in the article:

--------------------------------------------------
I agree, it's a complex and subtle difference (well to me anyhow...) that the
p-value indicates the likelihood of the TEST DATA being obtained WHEN the null hypothesis is TRUE.
And NOT that the p-value (from the test data) indicates the likeliness of the null hypothesis BEING true.

Jay Kosta
Endwell NY USA

We all agree with this although I think you should substitute IF for WHEN.

No. There is no THINK about it. It is ONLY applicable WHEN the null hypothesis is true.

Could you please educate me as to why the word WHEN is correct and the word IF isn't in this context?

 

[JamesCun]

Re: Re:

...
This is true Jay, notice it only refers to the result under a certain condition, it does not refer to the likelihood of a hypothesis being true or false,
...
He was attempting to use the p-value to assign a probability that the hypothesis is true. This is categorically wrong. This statistic cannot attach probabilities to hypotheses. This is clearly stated in the article:

--------------------------------------------------
I agree, it's a complex and subtle difference (well to me anyhow...) that the
p-value indicates the likelihood of the TEST DATA being obtained WHEN the null hypothesis is TRUE.
And NOT that the p-value (from the test data) indicates the likeliness of the null hypothesis BEING true.

Jay Kosta
Endwell NY USA

It's complex, subtle and very straight forward at the same time which is usually the problem. It's the most mis-used statistic in science too probably because it is so easy to calculate and claim it says what you want it to say. It's fine for people to say they don't get it, it's not fine for people to abuse it and think they can get away with it.

So, earlier I posted a link to a study that compared a PowerCranks group to a control group in which they found a difference in power improvement during the study with a p=.125 and a difference in efficiency improvement with a p=0.25. Why don't you tell us all how this should be properly interpreted since you seem to be the only one claiming to truly know but are not telling anyone.

Frank, you have been told numerous times. You just continue to ignore the facts and push your agenda. Go back and read the many, many posts explaining why your interpretation of p-values is wrong.

 

[FrankDay]

Re: Re:

...
This is true Jay, notice it only refers to the result under a certain condition, it does not refer to the likelihood of a hypothesis being true or false,
...
He was attempting to use the p-value to assign a probability that the hypothesis is true. This is categorically wrong. This statistic cannot attach probabilities to hypotheses. This is clearly stated in the article:

--------------------------------------------------
I agree, it's a complex and subtle difference (well to me anyhow...) that the
p-value indicates the likelihood of the TEST DATA being obtained WHEN the null hypothesis is TRUE.
And NOT that the p-value (from the test data) indicates the likeliness of the null hypothesis BEING true.

Jay Kosta
Endwell NY USA

It's complex, subtle and very straight forward at the same time which is usually the problem. It's the most mis-used statistic in science too probably because it is so easy to calculate and claim it says what you want it to say. It's fine for people to say they don't get it, it's not fine for people to abuse it and think they can get away with it.

So, earlier I posted a link to a study that compared a PowerCranks group to a control group in which they found a difference in power improvement during the study with a p=.125 and a difference in efficiency improvement with a p=0.25. Why don't you tell us all how this should be properly interpreted since you seem to be the only one claiming to truly know but are not telling anyone.

Frank, you have been told numerous times. You just continue to ignore the facts and push your agenda. Go back and read the many, many posts explaining why your interpretation of p-values is wrong.

I understand that. I have asked him how to properly interpret that data. He is the one who earlier posted this: "It's complex, subtle and very straight forward at the same time which is usually the problem. It's the most mis-used statistic in science too probably because it is so easy to calculate and claim it says what you want it to say." Let's see how he interprets this data.

 

[FrankDay]

Re:

This is directed towards King Boonen who has consistently demeaned my interpretation of p-values. Below is a post I made on a PowerCranks paper that gave raw p-values. My interpretation of what the p-values given mean is bolded.

So, here is a new study trying to replicate Lutrell. http://www.researchgate.net/publica..._using_uncoupled_cranks?citationList=outgoing

Objectives: Uncoupled cycling cranks are designed to remove the ability of one leg to
assist the other during the cycling action. It has been suggested that training with this
type of crank can increase mechanical efficiency. However, whether these improvements
can confer performance enhancement in already well-trained cyclists has not
been reported. Method: Fourteen well-trained cyclists (13 males, 1 female; 32.4 ± 8.8
y; 74.5 ± 10.3 kg; Vo2max 60.6 ± 5.5 mL·kg−1·min−1; mean ± SD) participated in this
study. Participants were randomized to training on a stationary bicycle using either an
uncoupled (n = 7) or traditional crank (n = 7) system. Training involved 1-h sessions,
3 days per week for 6 weeks, and at a heart rate equivalent to 70% of peak power
output (PPO) substituted into the training schedule in place of other training. Vo2max,
lactate threshold, gross efficiency, and cycling performance were measured before
and following the training intervention. Pre- and posttesting was conducted using
traditional cranks. Results: No differences were observed between the groups for
changes in Vo2max, lactate threshold, gross efficiency, or average power maintained
during a 30-minute time trial. Conclusion: Our results indicate that 6 weeks (18 sessions)
of training using an uncoupled crank system does not result in changes in any
physiological or performance measures in well-trained cyclists.

Many of you will note that they show "no difference". Of course, there are differences but they just don't reach the P<.05 level of significance.
For instance: Gross efficiency in the PC group improved from 19.7 to 20.9 (a 6% improvement) while the control group improved from 19.8 to 20.3 (a 2.5% improvement). This difference only reached the 0.25 level of significance. So, there is a 1 in 4 chance this difference is due to chance or a 3 in 4 chance (75%) the differences are real.
Then, time-trial power. The PC group improved from 284 to 298 watts (5%) while the control group improved from 274 to 281 watts (2.5%). This difference only reached the 0.125 level of significance. So, there is a 1 in 8 chance this difference is due to chance or a 7 in 8 chance (87.5%) the differences are real.

Most of the uncoupled cranks studies that have "failed" to show a difference look about the same, there being a trend to showing a difference but not reaching the scientific standard of 0.05, or a 1 in 20 chance the result is due to chance so the author is forced by convention to say he found no difference.

As the authors of this study wrote in their discussion: "The lack of effect of training using uncoupled cranks on GE is in contrast to that of Luttrell and Potteiger. A potential reason for these disparate results may be related to the participant recruitment criteria."

So, here is the problem with interpreting these studies. Here we have a study in which the PC group shows an increased improvement in efficiency over the control group that has a 75% chance of being a real change. And, the PC group has an increase in power over the control group that has an 87% chance of being real. Yet, because the results don't reach the 95% chance of being real, that scientists have generally agreed is required to be shown before someone can claim their study to have shown a difference, Fergie and others feel free to state that PC's have been "proven" to be a failure and a fraud when, in fact, the data suggests the exact opposite. This scenario is pretty much the case with every study that has looked at the PC's, the trend is there but they don't reach the p<0.05 level so the author concludes, rightly for a scientific paper, the data shows no difference. The problem it seems is it is difficult to show this difference, especially in experienced cyclists, in only 6 weeks.

My guess is if someone were to do a meta-analysis of all the studies out there there is enough data now to demonstrate a difference in both power improvement and efficiency improvement to the scientific standard. Until then, the world will just have to accept that pretty much all of the studies have shown PC's to be effective, just not to the 95% confidence level. This seems more an issue with study design (not enough subjects, not lasting long enough, etc.) than with the concept itself. So, if one is satisfied with evidence to the 70-90% level then it is there. If one needs the 95% level, then you may have to wait a bit.

Here is an examples of some of Kings comments regarding my interpretations of this data (emphasis added).

I didn't say you mentioned the null hypothesis but you don't have to as you are attempting to assign a percentage to the chance of differences being real based on a p-value.
You keep making this false statement that I have bolded, it does nothing of the kind and this has been pointed out to you over and over. Yet more trolling.

And, here is a post about his intentions in criticizing me (emphasis added).

My posts aren't really to educate Frank. I fully believe he is being wilfully deceitful as he keeps referencing a link that proves him wrong. They are for the benefit of people who might get taken in by the rubbish he is talking.

And, what he has said about the p-value (emphasis added).

It's complex, subtle and very straight forward at the same time which is usually the problem. It's the most mis-used statistic in science too probably because it is so easy to calculate and claim it says what you want it to say. It's fine for people to say they don't get it, it's not fine for people to abuse it and think they can get away with it.

The problem here is all he does is criticize without stating what is correct. I consider this behavior a form of academic bullying and intimidation. It doesn't work on me.

I earlier asked him to tell me how to properly interpret the p-values of 0.125 and 0.25 found in a real study involving PowerCranks (see above). This seems like a simple request to a person who has consistently criticized my interpretation and held himself out as an expert in the area and whose stated objective is to educate ("benefit" is used in the way of educate isn't it?) the masses following this thread. How can he educate them (and me) without telling us the proper interpretation?

I can only interpret the silence in this regard as to the proper interpretation of this data is close to my interpretation and goes against his bias so he would rather be silent than admit such. Hopefully, this post will get him to come forward and educate us all. If his silence continues everyone can draw their own conclusion as to what this might imply.

 

[Irondan]

You guys, please keep comments civil. I'll delete any comment that I think is disrespectful to a member, or is specifically designed to create anger and discontent, and possibly hand out a ban. I'm not going to be a judge and decide what information is right and wrong, that's up to you guys. Let's keep it clean fella's.

Cheers!

 

[Alex Simmons/RST]

Re: Re:

This is directed towards King Boonen who has consistently demeaned my interpretation of p-values. Below is a post I made on a PowerCranks paper that gave raw p-values. My interpretation of what the p-values given mean is bolded.

And as has been pointed out numerous times, your interpretation of p-values is wrong. If that hasn't sunk in yet, I'm not sure if it ever will.

 

[FrankDay]

Re: Re:

This is directed towards King Boonen who has consistently demeaned my interpretation of p-values. Below is a post I made on a PowerCranks paper that gave raw p-values. My interpretation of what the p-values given mean is bolded.

And as has been pointed out numerous times, your interpretation of p-values is wrong. If that hasn't sunk in yet, I'm not sure if it ever will.

I acknowledged that in my post that I have been told that many times. What is missing is someone telling me (and everyone else) what the proper interpretation of the data I presented is. You missed your chance so we are still waiting for the King.

 

[JayKosta]

Re: Re:

...
This is true Jay, notice it only refers to the result under a certain condition, it does not refer to the likelihood of a hypothesis being true or false,
...
... trimmed ...

--------------------------------------------------
I agree, it's a complex and subtle difference (well to me anyhow...) that the
p-value indicates the likelihood of the TEST DATA being obtained WHEN the null hypothesis is TRUE.
And NOT that the p-value (from the test data) indicates the likeliness of the null hypothesis BEING true.

Jay Kosta
Endwell NY USA

We all agree with this although I think you should substitute IF for WHEN.

---------------------------------------------------
I agree with Frank that my wording should have used the word 'IF' - because that word more precisely conveys the meaning of "the situation being". Using the word 'WHEN' might incorrectly be understood as "sometimes it is, and sometimes it is not". And in formal 'logical constructions' the typical terms are: IF / THEN / ELSE / NOT / TRUE / FALSE, etc.
I don't recall 'when' being used in a 'formal sense'.

BTW - my understanding of p-value is strictly from the wikipedia article, I DO NOT know whether the information in the article is accurate - so I'm 'trusting' it to be good and complete.

So I rephrase my definition to be:
p-value indicates the likelihood of the TEST DATA being obtained IF the null hypothesis is TRUE.

It's critical to note that the definition SAYS NOTHING about the situation of the the null hypothesis NOT being true.
ONLY that
IF the null hypothesis is TRUE, THEN then p-value indicates the likelihood of the test data being obtained during testing.

So a p-value of 0.125 would indicate that IF the results are due soley to chance, THEN there is a 12.5% likelihood of the observed TEST DATA being obtained by testing.
Or in more common languge -
"Even if it's all due to chance, there's still a 12.5% of getting those test results, because the p-value is 0.125"

Jay Kosta
Endwell NY USA

 

[Alex Simmons/RST]

Re: Re:

This is directed towards King Boonen who has consistently demeaned my interpretation of p-values. Below is a post I made on a PowerCranks paper that gave raw p-values. My interpretation of what the p-values given mean is bolded.

And as has been pointed out numerous times, your interpretation of p-values is wrong. If that hasn't sunk in yet, I'm not sure if it ever will.

I acknowledged that in my post that I have been told that many times. What is missing is someone telling me (and everyone else) what the proper interpretation of the data I presented is. You missed your chance so we are still waiting for the King.

The answer to your question was given perhaps half a dozen times in this thread already. I can't help it if you refuse to accept the actual answer is not the one you wish to falsely perpetuate.

 

[JayKosta]

Re: Re:

...
A p of 0.125 should mean that there is a 1 in 8 chance that this result could have occurred by chance if the null hypothesis were true. And, conversely, it should mean that there is a 7 in 8 chance that the difference seen represents a real difference and the null hypothesis is not true.
...

---------------------------
This is getting to be a discussion of logic and wording.

Look closely at your FIRST sentence - you're saying that -
IF the null hypotheis is TRUE, THEN there's a 1-in-8 chance the results could have occurred by chance.
The trouble is that IF the null hypotheis is TRUE, THEN the results DID occur by chance.
The p-value is only giving the likelihood of those PARTICULAR results occurring IF the results are due to chance.

Your SECOND sentence about the 'converse' can't be derived by formal logic from the definition of p-value.
It would be 'convenient' to make that assumption, but the definition and logic don't allow it.

The key thing about the definition of p-value is that it only applies if the null hypothesis is TRUE.
The p-value doesn't give any direct indication of the results being DUE TO THE HYPOTHESIS.
It only indicates the likelihood of the results occuring if the NULL HYPOTHESIS is true - and apparently having a low p-value is accepted as being satisfactory to indicate the results are 'statisically (edit) significant'.

Jay Kosta
Endwell NY USA

 

[JayKosta]

The p-value ONLY addresses the statistics of the testing.
Having a low p-value ONLY indicates a low likelihood that those results would occur if the results were due to chance.
A low p-value doesn't have anything to do with validating how the authors analyze the data, or the conclusions that they reach.
Only that the data itself is 'statistically (edit) significant' - nothing about the hypothesis, etc.

Jay Kosta
Endwell NY USA

 

[JayKosta]

This Wikipedia article about 'statistical significance' gives a good description of p-value, alpha, statistical significance, and how they are used.
https://en.wikipedia.org/wiki/Statistical_significance

Note that alpha is the level that is 'chosen' to be the cut-off point for 'statistical significance' - there isn't a single particular value that is used in all situations.
Also, it talks about what the author 'may report' or 'may conclude' about the data, and whether he feels that it is appropriate to reject the null hypothesis.
It doesn't say that having a particular p-value PROVES that the null hypothesis is FALSE (or that the hypothesis of the article is true), only that a low p-value can be used as an indicator for rejecting the null hypothesis.
And 'rejecting the null hypothesis' doesn't mean that the specific variables of the test were responsible for the observed differences, only that there is 'statistical significance' that SOMETHING other than chance caused the results. It's the responsibility of the author to design and run the tests in a manner that convinces the reviewers and readers that the author's analysis and conclusions about the data are meaningful.

Jay Kosta
Endwell NY USA

 

[sciguy]

Re:

This Wikipedia article about 'statistical significance' gives a good description of p-value, alpha, statistical significance, and how they are used.
https://en.wikipedia.org/wiki/Statistical_significance


And 'rejecting the null hypothesis' doesn't mean that the specific variables of the test were responsible for the observed differences, only that there is 'statistical significance' that SOMETHING other than chance caused the results. It's the responsibility of the author to design and run the tests in a manner that convinces the reviewers and readers that the author's analysis and conclusions about the data are meaningful.

Jay Kosta
Endwell NY USA

Jay,

Thanks for taking the time to lay this out. The bold part above is definitely important to always consider. Leirdal's first cycling efficiency study comes to mind when considering it.

Hugh

 

[PhitBoy]

Re: Re:

Truly amazing how far off topic this tread goes in order to discredit the main theme of the results:
1. Two studies in the peer reviewed literature have shown that cyclists are less efficient when they follow instructions to pull up more (Korff et al 2007 and Mornieux et al 2008)
2. Another paper shows that pedaling with one leg is less efficient than pedaling with two legs or than pedaling with a counterweight (Burns et a., 2014)
3. FD argues that these are acute interventions and those tested did not have the proper technique that they would get from prolonged training with decoupled cranks. Uncoupled cranks force the rider to pedal as if he was doing single leg cycling with no counterweight.
4. The study mentioned by the OP is a case study of a hip level amputee who has done nothing but single leg non counterweighted cycling for seven years. This should be very nearly the equivalent of long term training with decoupled powercranks. This four time US Paralympic National Champion was more efficient with a counterweight.
5. We know from the abstract by Elmer et al 2015 that cyclists pull up less when doing single leg pedaling with a counterweight (the full paper is in revision and should be accepted soon). Taken together these research findings strongly suggest that pulling up compromises efficiency even when the cyclist is well practiced.
The clear implication is that any time spent trying to learn to pull up is wasted if it is an effort to increase efficiency. The efforts to deny these findings involve convoluted explanations of decoupled systems and creative interpretations of statistical analyses.
Yours Truly,
PhitBoy

This Wikipedia article about 'statistical significance' gives a good description of p-value, alpha, statistical significance, and how they are used.
https://en.wikipedia.org/wiki/Statistical_significance


And 'rejecting the null hypothesis' doesn't mean that the specific variables of the test were responsible for the observed differences, only that there is 'statistical significance' that SOMETHING other than chance caused the results. It's the responsibility of the author to design and run the tests in a manner that convinces the reviewers and readers that the author's analysis and conclusions about the data are meaningful.

Jay Kosta
Endwell NY USA

Jay,

Thanks for taking the time to lay this out. The bold part above is definitely important to always consider. Leirdal's first cycling efficiency study comes to mind when considering it.

Hugh

 

[JayKosta]

Re: Re:

...
5. We know from the abstract by Elmer et al 2015 that cyclists pull up less when doing single leg pedaling with a counterweight (the full paper is in revision and should be accepted soon). Taken together these research findings strongly suggest that pulling up compromises efficiency even when the cyclist is well practiced.
The clear implication is that any time spent trying to learn to pull up is wasted if it is an effort to increase efficiency. The efforts to deny these findings involve convoluted explanations of decoupled systems and creative interpretations of statistical analyses.
Yours Truly,
PhitBoy
...

----------------------------------------
YES, 'excessive' pulling-up is probably not a desireable technique - as is required in non-counterweight single leg pedaling.
But many (most?) of the power analysis graphs for two leg pedaling with conventional cranks show that unweighting is typically done on the upstroke. Sometimes with a slight amount of additional force to produce postive torque, but usually with just enough 'up force' to unweight the pedal, and to avoid producing significant negative torque.

So a possible question is 'how to train the muscles for longterm endurance so the most effective amount of unweighting (or pulling-up) can be maintained during the entire event'.
QUESTION: is there evidence that a rider's 'power production style' remains basically the same as the rider's muscles become fatigued? Do all the muscles fatigue at a similar rate, so the style is the same (but with the power level dropping)? And if some muscles do fatigue more than others, would there be a benefit to 'training' those muscles, as compared to just doing more 'overall training'?

And for those riders who do not naturally perform effective unweighting 'how to train them to do whatever unweighting would be more effective than their current technique'.

YES, this is a lot of speculation about 'technique' - but that's the primary issue that many of us are interested in!

Jay Kosta
Endwell NY USA

 

[backdoor]

Re: Re:

[quote="PhitBoy]

Uncoupled cranks force the rider to pedal as if he was doing single leg cycling with no counterweight.
[/quote]

Uncoupled crank training is worse than single leg pedalling with or without a counterweight because the "pulling up" weakens the muscles involved in the down stroke.

 

[CoachFergie]

Re: Re:

[quote="PhitBoy]

Uncoupled cranks force the rider to pedal as if he was doing single leg cycling with no counterweight.


Uncoupled crank training is worse than single leg pedalling with or without a counterweight because the "pulling up" weakens the muscles involved in the down stroke.

You have data to show this?

 

[backdoor]

Re: Re:

[quote="PhitBoy]

Uncoupled cranks force the rider to pedal as if he was doing single leg cycling with no counterweight.


Uncoupled crank training is worse than single leg pedalling with or without a counterweight because the "pulling up" weakens the muscles involved in the down stroke.

You have data to show this?

No need for data, common sense is all that's required. Try pulling up as you pedal and take note of how it affects your down stroke. Continuous training in this manner over months can have only one effect on down stroke power.

 

[CoachFergie]

Your opinion is insufficient. Do you have data to show that uncoupled pedalling is worse than unweighted single leg pedalling.

 

[backdoor]

Re:

Your opinion is insufficient. Do you have data to show that uncoupled pedalling is worse than unweighted single leg pedalling.

https://www.powercranks.com/Lance.html
See third example, down stroke power uncoupled pedalling v regular pedalling. Down stroke power of unweighted single leg pedalling should not differ from regular down stroke power because there are no distractions, the brain can give total concentration to the application of downward power.

 

[JayKosta]

Re: Re:

...
https://www.powercranks.com/Lance.html
See third example, down stroke power uncoupled pedalling v regular pedalling. Down stroke power of unweighted single leg pedalling should not differ from regular down stroke power because there are no distractions, the brain can give total concentration to the application of downward power.

---
In the text description for that graph -
"The only reason the pushing forces are decreased is because this was obtained at the same power and cadence."

High downstroke power wasn't needed to be produced for the same total watts because power was increased in other sectors of the stroke. It doesn't show or indicate that more downstroke power couldn't be produced - only that it wasn't necessary to do so.

Jay Kosta
Endwell NY USA

 

[backdoor]

Re: Re:

...
https://www.powercranks.com/Lance.html
See third example, down stroke power uncoupled pedalling v regular pedalling. Down stroke power of unweighted single leg pedalling should not differ from regular down stroke power because there are no distractions, the brain can give total concentration to the application of downward power.

---
In the text description for that graph -
"The only reason the pushing forces are decreased is because this was obtained at the same power and cadence."

High downstroke power wasn't needed to be produced for the same total watts because power was increased in other sectors of the stroke. It doesn't show or indicate that more downstroke power couldn't be produced - only that it wasn't necessary to do so.

Jay Kosta
Endwell NY USA

The only reason the pushing forces are decreased is because that's what happens when pulling up torque is being produced with coupled or uncoupled cranks. If pulling up torque could be added to down stroke torque without affecting down stroke power, why are today's TT riders not taking advantage of this extra power.

 

[CoachFergie]

Re: Re:

Your opinion is insufficient. Do you have data to show that uncoupled pedalling is worse than unweighted single leg pedalling.

https://www.powercranks.com/Lance.html
See third example, down stroke power uncoupled pedalling v regular pedalling. Down stroke power of unweighted single leg pedalling should not differ from regular down stroke power because there are no distractions, the brain can give total concentration to the application of downward power.

Real data, not someones delusions. Using the claimed data of Lance Armstrong belongs in the Clinic, not a scientific debate about what is actually happening while pedalling and any potential improvements in performance.

 

[backdoor]

Re: Re:

Your opinion is insufficient. Do you have data to show that uncoupled pedalling is worse than unweighted single leg pedalling.

https://www.powercranks.com/Lance.html
See third example, down stroke power uncoupled pedalling v regular pedalling. Down stroke power of unweighted single leg pedalling should not differ from regular down stroke power because there are no distractions, the brain can give total concentration to the application of downward power.

Real data, not someones delusions. Using the claimed data of Lance Armstrong belongs in the Clinic, not a scientific debate about what is actually happening while pedalling and any potential improvements in performance.

You were only supposed to look at " Pedal Tangential Force Powercranks vs Regular Cranks" , this clearly shows what happens to your down stroke torque when pulling up is used, because it takes maximal pulling up effort to produce this minimal torque.

 

[backdoor]

Re: Re:

...
https://www.powercranks.com/Lance.html
See third example, down stroke power uncoupled pedalling v regular pedalling. Down stroke power of unweighted single leg pedalling should not differ from regular down stroke power because there are no distractions, the brain can give total concentration to the application of downward power.

---
In the text description for that graph -
"The only reason the pushing forces are decreased is because this was obtained at the same power and cadence."

High downstroke power wasn't needed to be produced for the same total watts because power was increased in other sectors of the stroke. It doesn't show or indicate that more downstroke power couldn't be produced - only that it wasn't necessary to do so.

Jay Kosta
Endwell NY USA

Do you believe more (than what we see here) upstroke pulling up torque could be produced if required ?