Whether the data are at the taxon or the element level, the arguments
surrounding NISP and MNE/MAU are still entirely relevant. The only
difference is that when dealing with elements you only have to worry about
one, rather than two, levels of fragmentation of the unit of analysis (the
element)- i.e. only breakage of elements, not disarticulation. You can
restrict the 'NISP' and 'MN*' labels to taxonomic comparisons if you want,
but there's still a fundamental difference between fragment counts and
derived estimates when dealing with elements. Surely? Unless I'm missing
something?
Not that it matters enormously in the present case, because neither group
of measures is really amenable to classical hypothesis testing in any case.
I know that zooarchaeologists frequently use chi-squared etc. with both
forms, but quite simply they shouldn't, especially with raw counts. This is
equally the case whether those counts are of individuals or of elements,
UNLESS there is virtually no breakage. Some form of Watson-style DZ is
probably the best bet, but even then you have to worry about
non-independence between proximal and distal ends etc.
With regard to the use of Kolmogorv-Smirnov tests for element profiles, I'm
not an expert on this stuff either and I have to admit I haven't read that
book in detail, but it sounds like madness to me. Even if one ignores the
quantification/sample inflation issue, K-S is designed for ordinal data,
while element profiles are nominal. The KS test statistic is based on Dmax,
the greatest difference between the cumulative frequency curves of the two
distributions. With element profiles this will differ depending on the
order in which you list the elements - an unscrupulous researcher could
even try a few different orders to get the 'best' result.
I may well be missing something here, in which case I'd be grateful if
someone could explain where I'm off the mark. I'd love to be wrong on this.
David
> The OP can speak for herself, but I took her statement literally:
> "differences in element frequencies between the two units."
>
> If elements have been counted, then issues of NISP versus MNI are not
> relevant to her question.
>
>
>>
>>Subject: Re: [ZOOARCH] Statistics help
>> From: "D.C. Orton" <[log in to unmask]>
>> Date: Thu, 10 Jan 2008 22:25:17 +0000
>> To: [log in to unmask]
>>
>>I think the most important question is what form of quantification you're
>>using.
>>
>> If it's NISP-based, you can basically forget formal hypothesis testing
>> as you're samples are almost certainly subject to sample inflation (see
>> e.g. Grayson 1984, pp.22-23 for a clear explanation of this). The only
>> exception would be if the bones are barely fragmented at all. Of course,
>> if you run the tests (chi-squared would make sense by the sound of it)
>> and find no significant pattern then that's fine, as sample inflation
>> will only ever lower your p values, but you shouldn't trust an
>> apparently significant result from this kind of data.
>>
>>To be honest, if it's minimum-number based the situation isn't great
>>either, since you're then dealing with estimates with a non-random,
>>asymmetrical error term.
>>
>>Frankly, zooarchaeological data is a bit of a nightmare statistically
>>speaking. David
>>
>>> You don't say how many elements you have, but whether it is one or more
>>> then I would have thought Chi-square and Fisher's test are entirely
>>> appropriate. Why are you worried about using them?
>>>
>>>
>>>>
>>>>Subject: [ZOOARCH] Statistics help
>>>> From: Melanie Fillios <[log in to unmask]>
>>>> Date: Thu, 10 Jan 2008 15:39:26 -0600
>>>> To: [log in to unmask]
>>>>
>>>> Dear All, I'm hoping someone may be able to point me in the right
>>>> direction with some statistical analysis of an assemablage. In short,
>>>> I am comparing two stratigraphic units and would like to test whether
>>>> differences in element frequencies between the two units are
>>>> statistically significant. Could anyone tell me what type of test I
>>>> should be using? I've looked a using a Chi-square or Fisher's test,
>>>> but neither seem appropriate. As math is not my strong point, I may be
>>>> missing something.
>>>>
>>>>Thanks for the help!
>>>>
>>>>Melanie
>>>>
>>>>Dr. Melanie Fillios
>>>>University of Sydney
>>>>NSW, Australia 2006
>>>>[log in to unmask]
>>>
>
|