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From |
Cameron McIntosh <cnm100@hotmail.com> |

To |
STATA LIST <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: factor analysis and bootstrapping |

Date |
Wed, 1 Feb 2012 09:21:14 -0500 |

I might also recommend some methodological papers re: resampling in FA and similar contexts: Zhang, G., & Browne, M.W. (2006). Bootstrap fit testing, confidence intervals, and standard error estimation in the factor analysis of polychoric correlation matrices. Behaviormetrika, 33(1), 61-74.http://www.jstage.jst.go.jp/article/bhmk/33/1/61/_pdf Zhang, G., Preacher, K. J., & Luo, S. (2010). Bootstrap confidence intervals for ordinary least squares factor loadings and correlations in exploratory factor analysis. Multivariate Behavioral Research, 45, 104-134. Yuan, K.-H., & Hayashi, K. (2006). Standard errors in covariance structure models: Asymptotics versus bootstrap. British Journal of Mathematical and Statistical Psychology, 59(2), 397–417. Yuan, K.-H., Hayashi, K., & Yanagihara, H. (2007). A Class of Population Covariance Matrices in the Bootstrap Approach to Covariance Structure Analysis. Multivariate Behavioral Research, 42(2), 261-281. Jennrich, R.I. (2008). Nonparametric Estimation of Standard Errors in Covariance Analysis Using the Infinitesimal Jackknife. Psychometrika, 73(4), 579-594. Cam > Date: Wed, 1 Feb 2012 01:45:27 +0000 > Subject: Re: st: factor analysis and bootstrapping > From: njcoxstata@gmail.com > To: statalist@hsphsun2.harvard.edu > > The way -bootstrap- works hinges on taking one or more scalar results > and looking at their distribution(s) under sampling with replacement. > But you are trying to put a series of matrix results into a single > variable. That won't work if only because you can't fit a matrix into > a single value of a variable. > > In addition, I don't understand why you are trying to -bootstrap- > rotation. Where's the stochastic element in that? The same rotation of > the same factor analysis results will give the same rotated results. > It's like rotating from facing N to facing E, but doing it 1000 times. > > I imagine what you want to do is -bootstrap- the whole shebang, i.e. a > -factor- analysis followed by -rotate-, in which there will be > variation because the factor analysis results will differ because of > different samples. In that case, you would need to write a program to > encapsulate both, and -- first point above -- taking each loading from > the matrix and putting it into a separate scalar. > > If you seek comment on Martin Weiss's advice, please give the specific URL. > > Nick > > On Tue, Jan 31, 2012 at 11:37 PM, Jurgen Sidgman <sidgman@uwm.edu> wrote: > > A few months ago a post identical to the one I have here was made and answered by Martin Weiss. The problem is that I have not been able to execute following his advice. So here it goes. > > > > I want to bootstrap the factor loadings that I obtain after executing > > > > factor var1 var2…, pcf > > > > to determine if the loadings are statistically different from zero at conventional levels. Without attempting the bootstrapping all works well. However trying the following commands rotate does not work and I cannot seem to find a solution: > > > > bootstrap, reps(1000): rotate > > bootstrap load:e(L), reps(1000): rotate > > bootstrap e(L), reps(1000): rotate promax > > > > I have also tried: > > > > bootstrap loadings=e(L), reps(1000): rotate promax > > > > * > * 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/

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