Re: ISSUE-30 counter-proposal

On Feb 14, 2010, at 12:24 PM, Shelley Powers wrote:

> Maciej Stachowiak wrote:
>> On Feb 14, 2010, at 9:04 AM, Shelley Powers wrote:
>>> Maciej Stachowiak wrote:
>>>> Hi Shelley,
>>>> If you want to argue against the studies Ian cited, please do so  
>>>> by using facts to refute them, instead of just casting vague  
>>>> aspersions on Ian's integrity. Examples of fact-based arguments  
>>>> would be: (1) cite specific methodological flaws; (2) perform or  
>>>> cite a better study that finds different results. That's what a  
>>>> scientist peer reviewing a study would do, they don't just accuse  
>>>> each other "bias".
>>> I'm using the terminology that was established within the  
>>> psychology field when referencing studies of this nature.
>>> The use of "bias" in the field, especially in regards to research  
>>> is based more on a set of assumptions than something 'negative'.  
>>> Every researcher is biased, no matter how much they try to  
>>> approach a research topic in a neutral, "unbiased" manner.
>> Sample bias is a relevant concept in statistics, as is systemic  
>> bias. But we don't usually refer to the investigator being biased.  
>> In science, having a guess what the outcome of an experiment will  
>> be is called a "hypothesis", not "bias".
> I was not talking about statistical bias. I was talking about  
> researcher bias, which is a different thing.
> The real point, though, is that you seem to be interpreting my  
> earlier note to Ian in some arbitrarily negative light, that it was  
> a personal attack of some form, and that was NOT the intention.

Here is a more comprehensive description of different kinds of  
research bias: < 
bias.html> Here is another list: < 
 >. Many of these are only really applicable to studies with human  
subjects, but some could certainly apply to a study that data mines  
Web pages too.

None of these would normally be described in terms such as "you have a  
bias in the results", "...ensure their biases and assumptions do not  
impact on the results" or "your own biases". A research bias is  
normally described as a property of the research study, not of the  
investigator. You also implied that the bias means the research has no  
validity, whereas the usual way of treating various forms of research  
bias is to be aware of and account for them. Also, you tend to refer  
to "bias" a lot in a clearly non-scientific context. For these  
reasons, I assumed your mention of bias was just meant as a personal  
attack -- something along the lines of, "Ian doesn't like longdesc,  
therefore any studies by him on the topic are automatically invalid  
and should be ignored."

Since that is not what you meant, then my apologies for  
misinterpreting you.

If what you meant is that you think Ian's study suffers from one or  
more of the types of research bias mentioned in the above cited links,  
then definitely you should say which types of bias it suffers from,  
and explain how you came to that conclusion. Then the Working Group  
will then know how to take it into account when interpreting the  
results, and we may even be able to come up with a better design for  
future research studies.


Received on Sunday, 14 February 2010 20:35:54 UTC