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From | Cameron McIntosh <cnm100@hotmail.com> |
To | STATA LIST <statalist@hsphsun2.harvard.edu> |
Subject | RE: st: Identifying the best scale without a "gold standard" |
Date | Thu, 17 Nov 2011 13:04:41 -0500 |
What does the goodness-of-fit chi-square test say about the tenability of a one- or two-factor solution?Cam > From: paul.seed@kcl.ac.uk > To: statalist@hsphsun2.harvard.edu > Date: Thu, 17 Nov 2011 14:21:11 +0000 > Subject: Re: st: Identifying the best scale without a "gold standard" > > Thank you Ronan (and Nick) for pointing me to some useful software. > And Jean-Benoit for writing it. > > I agree about -clv- . It identified a single factor as the best > representation, but also suggested a possible second > factor, based on two scales with a higher than average > correlation. All with the simplest possible format. > > BW > > > Paul Seed > > > Ronan Conroy <rconroy@rcsi.ie> wrote: > > Date Thu, 17 Nov 2011 10:48:26 +0000 > > >>On 2011 Samh 16, at 18:15, Cameron McIntosh wrote: > >> Hayton, J.C., Allen, D.G., & Scarpello, V. (2004). Factor Retention Decisions in Exploratory Factor Analysis: a Tutorial on Parallel Analysis. Organizational >>Research Methods, 7(2), 191-205.http://orm.sagepub.com/content/7/2/191.full.pdf+html > > >A very well worthwhile article. The authors make the point that "Specifying too few factors results in the loss of important information by ignoring a factor or >combining it with another (Zwick & Velicer, 1986). This can result in measured variables that actually load on factors not included in the model, falsely loading >on the factors that are included, and distorted loadings for measured variables that do load on included factors. Furthermore, these errors can obscure the true >factor structure and result in complex solutions that are difficult to interpret (Fabrigar et al., 1999; Wood, Tataryn, & Gorsuch, 1996)." > > > >I really like Jean-Benoit Hardouin's -clv- command in this context, giving a splendid visual display of the structure of the items. It has revealed important >features of data, such as factors-within-factors, that would have been far harder to spot in the output of any factor analytic command. > > > > Ronán Conroy > rconroy@rcsi.ie > Associate Professor > Division of Population Health Sciences > Royal College of Surgeons in Ireland > Beaux Lane House > Dublin 2 > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/