Hi Team,
I was using your "psych" package for factor analysis and was also
comparing
the results with SAS results. I have some suggestions and/or confusions
regarding the fa() function in the package:
- The fa() function *doesn't account for Heywood cases* (communality
greater than 1) and never ever throws out any error related to that which
other softwares do. This is a serious and common issue in iterative factor
analysis and hence should have been accounted for.
- The fa() function doesn't provide "equamax" rotation in its
rotation
list and still if you specify "*rotation=equamax*", it will run
without
throwing out any error and even mentioning in the result that
"equamax" has
been applied. But I have thoroughly compared results from "
*rotation=none*" and "*rotation=equamax*" options and they are
exactly
same. *That means fa() is not doing the rotation at all and yet telling
that it is doing that!!* I have even mentioned "*rotation=crap*"
option
just to check and surprisingly it ran(without any error) with the result
showing:
*Factor Analysis using method = gls*
* Call: fa(r = cor_mat, nfactors = 4, n.obs = 69576, rotate
"crap", fm = "gls")*
I hope you understand the severity of this bug and hence
request you to correct this.
- To my sense, there might be some problem with "fm=ml" and
"fm=pa"
options since the convergence issue should be with MLE method and not PA
method but while running factor analysis with PA, I am getting the
following warning:
*maximum iteration exceeded*
* The estimated weights for the factor scores are probably
incorrect. Try a different factor extraction method.*
If I compare the results of R and SAS,* I am getting
convergence error for MLE in SAS whereas I am getting the same error for PA
in R *!! I am not being able to understand this mismatch.
- If I call the *loading matrix like efa_pa$loadings, the matrix shown
has many blank cells whereas the final result showing the loadings
doesn't
have so* !!
*Loadings:*
* PA1 PA2 PA3 PA4 *
*Var1 0.401 -0.243*
*Var2 0.336 -0.104 0.710*
*Var3 0.624 0.123 0.170 *
- Could you please explain* what the "com" column means* in the
output:?
* PA1 PA3 PA2 PA4 h2 u2 com*
*Var1 0.44 0.14 -0.03 -0.10 0.22665 0.773 1.3*
*Var2 0.08 0.11 0.02 0.78 0.62951 0.370 1.1*
*Var3 0.62 0.12 0.15 0.14 0.43578 0.564 1.3*
- Request you to add option for *"equamax" rotation* also if
possible.
I have come across the above issues until now. Please do correct me if I am
wrong.
Awaiting your revert which would clear out my confusions,
Thanks for your valuable time,
Sagnik
--
Regards,
*SAGNIK CHAKRAVARTY*
*Mob:* +919972865435
*Email:* sagnik.stats@gmail.com
sagnik.739@gmail.com
[[alternative HTML version deleted]]
Hello, And what about submitting your suggestions directly to the package author/maintainer? And please don't post in HTML. Regards, Pascal On Tue, Apr 8, 2014 at 3:13 PM, sagnik chakravarty <sagnik.stats at gmail.com> wrote:> Hi Team, > > I was using your "psych" package for factor analysis and was also comparing > the results with SAS results. I have some suggestions and/or confusions > regarding the fa() function in the package: > > - The fa() function *doesn't account for Heywood cases* (communality > greater than 1) and never ever throws out any error related to that which > other softwares do. This is a serious and common issue in iterative factor > analysis and hence should have been accounted for. > > > - The fa() function doesn't provide "equamax" rotation in its rotation > list and still if you specify "*rotation=equamax*", it will run without > throwing out any error and even mentioning in the result that "equamax" has > been applied. But I have thoroughly compared results from " > *rotation=none*" and "*rotation=equamax*" options and they are exactly > same. *That means fa() is not doing the rotation at all and yet telling > that it is doing that!!* I have even mentioned "*rotation=crap*" option > just to check and surprisingly it ran(without any error) with the result > showing: > > *Factor Analysis using method = gls* > * Call: fa(r = cor_mat, nfactors = 4, n.obs = 69576, rotate > "crap", fm = "gls")* > > I hope you understand the severity of this bug and hence > request you to correct this. > > - To my sense, there might be some problem with "fm=ml" and "fm=pa" > options since the convergence issue should be with MLE method and not PA > method but while running factor analysis with PA, I am getting the > following warning: > > *maximum iteration exceeded* > * The estimated weights for the factor scores are probably > incorrect. Try a different factor extraction method.* > > If I compare the results of R and SAS,* I am getting > convergence error for MLE in SAS whereas I am getting the same error for PA > in R *!! I am not being able to understand this mismatch. > > - If I call the *loading matrix like efa_pa$loadings, the matrix shown > has many blank cells whereas the final result showing the loadings doesn't > have so* !! > > *Loadings:* > * PA1 PA2 PA3 PA4 * > *Var1 0.401 -0.243* > *Var2 0.336 -0.104 0.710* > *Var3 0.624 0.123 0.170 * > > > - Could you please explain* what the "com" column means* in the output:? > > > * PA1 PA3 PA2 PA4 h2 u2 com* > *Var1 0.44 0.14 -0.03 -0.10 0.22665 0.773 1.3* > *Var2 0.08 0.11 0.02 0.78 0.62951 0.370 1.1* > *Var3 0.62 0.12 0.15 0.14 0.43578 0.564 1.3* > > - Request you to add option for *"equamax" rotation* also if possible. > > > I have come across the above issues until now. Please do correct me if I am > wrong. > > Awaiting your revert which would clear out my confusions, > > Thanks for your valuable time, > > Sagnik > > -- > Regards, > > *SAGNIK CHAKRAVARTY* > > *Mob:* +919972865435 > *Email:* sagnik.stats at gmail.com > sagnik.739 at gmail.com > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.-- Pascal Oettli Project Scientist JAMSTEC Yokohama, Japan
Hi Sagnik, sagnik chakravarty wrote> - Request you to add option for *"equamax" rotation* also if possible.As GPApackage doesn't provide an explicit function termed "Equamax" you may want to use Crawford-Ferguson rotation from the GPApackage ( "cfT"). With the additional argument kappa=m*/(2*p), where m is the number of factors and p the number of variables/items, you'll be able to achieve a Equamax rotation. On the equivalence of orthogonal CF with Orthomax family please refer to Browne, 2001, An overview fo Analytic Rotation in Exploratory Factor Analysis, Multivariate Behavioural Research, 36 (1), 111-150 Cheers, Gunter -- View this message in context: http://r.789695.n4.nabble.com/Issues-with-fa-function-in-psych-tp4688378p4690511.html Sent from the R help mailing list archive at Nabble.com.