[R] Poly Correlations

[John Fox]

Dear Michael,

Please see comments below, interspersed with your questions:

On Wed, 4 Sep 2013 22:18:57 -0400
 "Michael Hacker" <mhacker at nycap.rr.com> wrote:
> Dear Colleagues,
> 
>  
> 
> I'm working on a Delphi study comparing perceptions of high school
> technology teachers and university engineering educators about the
> importance of concepts about engineering for HS students to learn as part of
> their fundamental education. I'm actually doing this as part of my Ph.D.
> 
> The survey items (n=37) are categorized into five scales: design, human
> values, modeling, resources, and systems thinking. I'm seeking to determine
> the reliability of these scales and of the overall survey instrument. Since
> I'm working with ordinal data, Chronbach's Alpha probably isn't the best
> statistical tool to use.
> 
>  
> 
> I've literally spent several days learning my way around R-project but am
> struggling with procedures and interpretations. 
> 
>  
> 
> I'm aware that there is now a plug-in for R for SPSS that can be downloaded
> ( <http://www-01.ibm.com/support/docview.wss?uid=swg21477550>
> http://www-01.ibm.com/support/docview.wss?uid=swg21477550 and
> <http://gruener.userpage.fu-berlin.de/Essentials%20for%20R%20Installation%20
> Instructions_21.pdf>
> http://gruener.userpage.fu-berlin.de/Essentials%20for%20R%20Installation%20I
> nstructions_21.pdf). Just learned that today and I downloaded
> PolyCorrelations.zip from
> https://www.ibm.com/developerworks/community/files/app?lang=en#/file/9f47f9a
> 0-7793-4ad5-8bb7-d3fd1a028e44 
> 
>  
> 
> I've gotten as far as loading Rcmdr and running some analyses - (Statistics,
> dimensional analysis, scale reliability) and I've generated this output:
> 
>  
> 
> Reliability deleting each item in turn:
> 
>                         Alpha   Std.Alpha   r(item, total)
> 
> design              0.8445    0.8490         0.7629
> 
> humanvalues   0.8526    0.8541         0.7170
> 
> modeling          0.8511    0.8546         0.7271
> 
> resources        0.8712    0.8757         0.6328
> 
> systems           0.8461    0.8498         0.7488
> 
>  
> 
> I now would sincerely appreciate some help. At the age of 70, never having
> studied programming, the meaning of these statistics is not apparent.
> 
> For example, I'm not clear if either of these three statistics are Ordinal
> Alpha. Since I'm working with Likert scale items, my advisor suggested that
> I seek an alternative to Chronbach's Alpha to determine reliability.

The table seems self-explanatory to me: it includes Chronbach's alpha and alpha for standardized items with each item deleted in turn, along with the correlation of each item with the total of the other items. All of this is described if you press the Help button in the Reliability dialog for the Rcmdr.

The computation isn't really appropriate for ordinal items (unless you plan to treat the ordinal items as numeric).

> 
>  
> 
> So far, here are the steps I have taken:
> 
> I've searched the FAQs
> 
> Searched specifically for answers on the Web
> 
> Played with the software for hours
> 
> Read the accompanying documentation.
> 
> Downloaded and installed Rcmdr
> 
> Downloaded and installed PolyCorrelations. 
> 
>  
> 
> I tried running PolyCorrelations  but I get a message that states that this
> requires the Polychor and Gclus libraries. I tried to install them into the
> R console, but no luck. 

As far as I know, this is no Polychor package on CRAN, though there is a polycor package, which will compute polychoric and polyserial correlations. These could be used to calculate reliability for ordinal items, I suppose, though not, to my knowledge, with the Rcmdr.

> 
>  
> 
> I'd also be pleased to work with someone-on-one on a consulting basis if
> someone has the time and inclination.  Hoping to find an individual who
> knows SPSS and R.

It's unclear to me what SPSS has to do with all this.

Best,
 John

------------------------------------------------
John Fox
McMaster University
Hamilton, Ontario, Canada
http://socserv.mcmaster.ca/jfox/
	

> 
>  
> 
> Thanks very sincerely for considering this request.
> 
>  
> 
> Michael
> 
>  
> 
>  
> 
> -------------------------------- 
> 
> END OF MESSAGE  
> 
> -------------------------------- 
> 
> Michael Hacker, Co-Director
> 
> Hofstra University Center for STEM Education Research
> 
> Ph: 518-724-6437
> 
> Cell: 518-229-7300
> 
> Fax: 518-434-6783
> 
> URL: www.Hofstra.edu/CSR
> 
>  
> 
> 
> 	[[alternative HTML version deleted]]
> 
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