VOCD manual

Mon Aug 24 21:05:10 UTC 2015

Great, thank you v. much.

On Thursday, 20 August 2015 02:37:54 UTC+1, Spektor, Leonid: CMU wrote:
>
> Yes, it is possible. Just add +d3 option to FREQ command line.
>
> Leonid.
>
>
>
> On Aug 19, 2015, at 17:22, Amber <ambal... at gmail.com <javascript:>> wrote:
>
> I've done it and it is working - thank you. One more question - I wondered 
> if it is possible to have the MATTR output formatted like KIDEVAL is, in a 
> spreadsheet with each transcript listed in a row and the MATTR in the 
> column next to it. This would make it so much easier to copy + paste into 
> my stats software. 
>
> Thanks, 
> Amber 
>
> On Wednesday, 19 August 2015 19:08:15 UTC+1, Amber wrote:
>>
>> Thanks Leonid! Going to download a newer version. 
>>
>> Best
>> Amber 
>>
>> On Wednesday, 19 August 2015 18:56:02 UTC+1, Spektor, Leonid: CMU wrote:
>>>
>>> Amber,
>>>
>>> CHECK does not look at %mor tier. KIDEVAL will check word's one to one 
>>> correspondence between %mor tier and main speaker tier, But, if you have 
>>> already ran KIDEVAL with your current version of CLAN without any errors, 
>>> then the latest version of CLAN will not find errors either. You do not 
>>> need to re-MOR your data to use MATTR analyses, because FREQ is only 
>>> looking at main speaker tiers and is ignoring %mor tiers. But, if you  want 
>>> to get more accurate results from KIDEVAL, for example, then you should get 
>>> new MOR grammar and re-MOR your data. In fact you should do that even if 
>>> you do not update your CLAN, because we constantly improve MOR grammar and 
>>> this will give you more accurate results.
>>>
>>> Leonid. 
>>>
>>> On Aug 19, 2015, at 13:14, Amber <ambal... at gmail.com> wrote:
>>>
>>> Dear Brian
>>>
>>> Thank you. When I have gone to run the +bN command, it is not working. I 
>>> am thinking that I need to download a newer version of CLAN (I can see from 
>>> previous posts that MATTR has only recently been implemented). However, I 
>>> want to avoid having to re-MOR and check all my transcripts to ensure their 
>>> compatibility with the newer version of the software. Is there anyway to 
>>> update my current CLAN software (without downloading the newer version) so 
>>> that will allow me to run +bN? 
>>>
>>> Best wishes
>>> Amber 
>>>
>>> On Wednesday, 19 August 2015 17:22:53 UTC+1, Brian MacWhinney wrote:
>>>>
>>>> Dear Amber,
>>>>
>>>>     Thanks for noting that old link in the manual.  I have removed it 
>>>> and replaced it with a pointer to 
>>>> Malvern, D., Richards, B., Chipere, N., & Purán, P. (2004). *Lexical 
>>>> diversity and language development*. New York: Palgrave Macmillan.
>>>>
>>>> In regards to sample size, VOCD requires 100 utterances.  For smaller 
>>>> samples and more generally, you may wish to consider using MATTR, as 
>>>> described in my previous ChiBolts message on this topic.  There I gave a 
>>>> reference to 
>>>>
>>>> Covington, M. A., & McFall, J. D. (2010). Cutting the Gordian knot: The 
>>>> moving-average type–token ratio (MATTR). Journal of Quantitative 
>>>> Linguistics, 17(2), 94-100. 
>>>>
>>>> and you may wish to read the recent comparison of VOCD, TTR, and MATTR
>>>>
>>>> Fergadiotis, G., Wright, H., & Green, S. (2015). Psychometric 
>>>> evaluation of lexical diversity indices: Assessing length effects. *Journal 
>>>> of Speech, Language, and Hearing Research, 58*, 840. 
>>>>
>>>> My take-home from this is that people should only use TTR when 
>>>> comparing across samples of the same length and even then, VOCD or MATTR 
>>>> would be better.  In general, researchers should prefer MATTR to VOCD.  In 
>>>> CLAN, you run MATTR using this option in FREQ
>>>>
>>>> +bN This option calculates the lexical diversity of a sample using the 
>>>> Moving Average Type-Token Ratio (MATTR). This index is based on a moving 
>>>> window that computes TTRs for each successive window of fixed length (N). 
>>>> Initially, a window length is selected (e.g., 10 words) and the TTR for 
>>>> words 1- 10 is estimated. Then, the TTR is estimated for words 2-11, then 
>>>> 3-12, and so on to the end of the text. For the final score, the estimated 
>>>> TTRs are averaged.
>>>>
>>>>
>>>> —Brian MacWhinney
>>>>
>>>>
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