My job is in clinical trial issues. You can tell me about psychoacoustics but please refrain from teaching me about trials.
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Four Speaker Blind Listening Test Results (Kef, JBL, Revel, OSD)
- Thread starter MatthewS
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I’m sure that you know how much work is necessary for validation of results, why the FDA requires two large and well controlled studies, etc.
My point is that you have to be careful when interpreting smaller and poorly controlled experiments. I did find this one interesting but not overwhelming to me.
It is still PREFERENCE.
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...within the confines of a bell curve. Don't make it sound like it's wildly all over the map. The research shows people mostly like the same attributes in sound - that is, neutral and uncolored.
Semla
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The sample size needed for a given test is related to both the size of the effect and the variability of the outcome. The sample size for this particular outcome in this study is not small - more than 200 observations made by 10 listeners (the effective sample size is a bit smaller due to the grouping structure). That's why there is a statistically significant different score between certain speaker pairs.
In addition this is not the first experiment in this field - it builds on and confirms the results from all those earlier studies at Harman.
@Semla. Glad you commented. How did you calculate the scores per speaker? Did you use the 50 observations per speaker or you used the average per person?
You also know that you want to have a stat plan BEFORE the experiment to make sure that you don't find the results you want by peeling the onion.
Again, I am pleased with the results. But they are not conclusive to me.
Harman/Toole's work is also interesting. The premise was that a speaker with a flat frequency response in an anechoic chamber and with certain dispersion characteristics when placed in a simulated living room would be preferred by a set of "educated" listeners. A preference score is reached by scoring various different attributes. I don't know if Toole used step wise regression or whatever. But he states that certain characteristics contribute to the preference score and that the score is not "perfect". It gives a pretty good number.
I FOLLOW that preference in my speaker choice because I (hope) think that in the recording process they will use speakers with those characteristics to produce it. Thereby, I will get in my room the sound that the "musicians and producers" chose for their recordings.
But to follow those guidelines doesn't mean that I am not aware of the potential limitations of the work.
You also know that you want to have a stat plan BEFORE the experiment to make sure that you don't find the results you want by peeling the onion.
Again, I am pleased with the results. But they are not conclusive to me.
Harman/Toole's work is also interesting. The premise was that a speaker with a flat frequency response in an anechoic chamber and with certain dispersion characteristics when placed in a simulated living room would be preferred by a set of "educated" listeners. A preference score is reached by scoring various different attributes. I don't know if Toole used step wise regression or whatever. But he states that certain characteristics contribute to the preference score and that the score is not "perfect". It gives a pretty good number.
I FOLLOW that preference in my speaker choice because I (hope) think that in the recording process they will use speakers with those characteristics to produce it. Thereby, I will get in my room the sound that the "musicians and producers" chose for their recordings.
But to follow those guidelines doesn't mean that I am not aware of the potential limitations of the work.
Who said it was a bell curve?
And no, most people do NOT like the same attributes. This is why Toole published the different curves.
Certain speaker manufacturers make their speakers sound like the "uneducated" preference curve because of commercial reasons. There are probably more uneducated listeners in the world...
Well, if you work for a drug company, you have a stat plan before the experiment to make sure that the results you want are guaranteed.
Nope. That is not the reason you do this. ANY experiment will have a stat plan BEFORE you initiate it. You can never "guarantee" the results. This is one more reason you want the stat pan. You want to make sure that you are doing the proper analysis. How many times have you seen publications when the primary outcome failed and then state that any other analysis is speculative because it is secondary and the primary failed? It happens a lot. Look at studies in lupus. Most fail.
Semla
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See post #64 for a full description of the model.
Ideally, yes. But in reality even late-stage and other confirmatory studies are designed for a limited number of primary outcomes. Despite the regulated context lots of ad-hoc analyses are performed both on primary and secondary outcomes, even though from a purely theoretical point of view they should be considered worthless. That is clearly not the case.
In an ideal world every experiment would be properly designed and planned for every single outcome. But one needs to recognize that this is not the reality. Interesting things have been learned from badly designed experimental setups, studies without a formal statistical analysis plan, even from weird lab accidents etc. At the very least new hypotheses will be generated. The goal of a statistical analysis is to enable a decision under uncertainty - it needs to be good enough, it does not need to be perfect (and it will never be perfect).
Experiments are always performed in a context, in this case the Harman studies. One needs to look at evidence in this wider context, maybe perform a meta-analysis if you want to be quantitative. If you're still not convinced you can now design your own confirmatory experiment thanks to @MatthewS's hard work. He has shared all the data you need to come up with an appropriate design, model and sample size requirements. I hope that this work serves as an inspiration for other members.
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It's all summarized in the book:
https://smile.amazon.com/dp/113892136X/ref=cm_sw_r_cp_apa_glt_fabc_NXP9XQP23JAHTQH7Y37H
Agreed. The results of this small study follows previous ones perhaps with some exceptions, and while a correctly made meta-study is of highest value, there are also logical factors involved having speakers with a smooth frequency response. Comparisons are not without complications though since speakers may be designed with different room placement requirements. For example, comparison of Carlsson speaker with a conventional speaker would not be fair if the prerequisite is that the speakers must be placed in the same position.
@Semla. I agree with what you have stated. No worries. As I said many times, this is an interesting observation. I have seen many studies that had no p[lan and found new things, of course. I also know of studies that have been called milestone and were never able to be replicated. I am sure you are aware of Amgen's project to replicate many cancer studies and found that too many could not be replicated.
Dom Purpura, who was the Dean of the Albert Einstein School of Medicine told me this joke.
God sent an application for a grant to the NIH. After three years he gets a letter back from the NIH that states.
"Your proposal was fascinating, the advisory groups really like what you proposed but after careful consideration, unfortunately, we will not support your work for three reasons.
1. You published your work but it was not in a peer review journal.
2. Your work was done a very long time ago.
3. No one has replicated your results."
It encompasses a lot of real criticism of scientific work.
Dom Purpura, who was the Dean of the Albert Einstein School of Medicine told me this joke.
God sent an application for a grant to the NIH. After three years he gets a letter back from the NIH that states.
"Your proposal was fascinating, the advisory groups really like what you proposed but after careful consideration, unfortunately, we will not support your work for three reasons.
1. You published your work but it was not in a peer review journal.
2. Your work was done a very long time ago.
3. No one has replicated your results."
It encompasses a lot of real criticism of scientific work.
KEFCarver
Active Member
Sounds Like you had a fun time doing this and thanks for sharing your process and results. I have no complaints with how you did it or your results, but I only took one course in statistics and probability in college, and that was many, many moons ago. Hopefully you will try it again with some larger speakers 
OP
- Thread Starter
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The level of "thumbing the scales" that occurs in drug trials during cohort selection is not to be underestimated.
Anyone that wants to learn a lot about how to review medical studies might want to start here: Studying Studies: Part I – relative risk vs. absolute risk
@MatthewS , funny you bring this up. I had a huge issue with one company because they were designing a study using relative risk and I was trying to convince them that the absolute risk made the study unlikely to be successful. Too many patients with low absolute risk. So even if they reached the relative risk reduction it wasn’t going to work. They were unhappy with me. The study failed because of this. They didn’t want to enter “riskier” patients, those with a higher absolute risk as it would have delayed enrollment.
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Couldn't agree more!
Psychoacoustics science is created using listening tests. Since you don't seem to know that I suggest not making remarks like that. Your work has little in common with this research.
What do you want it to be? Distaste?
For the third time, no. People from every background have been part of this research which well predates Harman.
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