Dear Solomon, When I originally programmed the sem() function, I used optim() and experimented with the different methods provided, settling on "BFGS" as the default. Shortly after that, I compared optim() to nlm() for a range of problems and found that the latter performed better. It would not be hard to replace nlm() with optim() in sem(), if you wish to do it.
Regards, John > -----Original Message----- > From: Solomon Messing [mailto:mess...@stanford.edu] > Sent: July-27-09 8:01 PM > To: 'John Fox' > Cc: r-help@r-project.org > Subject: RE: [R] Confirmatory factor analysis problems using sem package > (works in Amos) > > Dear John, > > Would it possible to use a different optimizer with the sem package? > Perhaps optim(..., method = c("Nelder-Mead", "BFGS", "CG", "L-BFGS-B", > "SANN"),...) for example? > > Thank you very much, > > -Solomon > > > -----Original Message----- > > From: John Fox [mailto:j...@mcmaster.ca] > > Sent: Friday, May 22, 2009 6:25 AM > > To: 'S. Messing' > > Cc: r-help@r-project.org > > Subject: RE: [R] Confirmatory factor analysis problems using sem package > > (works in Amos) > > > > Dear Solomon, > > > > > -----Original Message----- > > > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] > > On > > > Behalf Of S. Messing > > > Sent: May-22-09 1:27 AM > > > To: r-help@r-project.org > > > Subject: [R] Confirmatory factor analysis problems using sem package > > (works > > > in Amos) > > > > > > > > > Hello all, > > > > > > I'm trying to replicate a confirmatory factor analysis done in Amos. > > > > Occasionally in an ill-conditioned problem, one program will produce a > > solution and another won't. As a general matter, I'd expect Amos to be > > more > > robust than sem() since Amos is written specifically for SEMs, while sem() > > uses nlm(), a general-purpose optimizer. > > > > > The > > > idea is to compare a one-factor and a two-factor model. I get the > > following > > > warning message when I run either model: > > > > > > "Could not compute QR decomposition of Hessian. > > > Optimization probably did not converge." > > > > > > I have no idea what to do here. > > > > A general strategy is to set debug=TRUE in the call to sem() and see what > > happens in the optimization. Then there are several things that you can do > > to try to get the optimization to converge; see ?sem. In this case, > > however, > > I wasn't able to get a solution. > > > > The one-factor model is equivalent to a one-factor exploratory FA, which > > can > > be fit by ML using factanal(): > > > > > factanal(factors=1, covmat=correl, n.obs=1100) > > > > Call: > > factanal(factors = 1, covmat = correl, n.obs = 1100) > > > > Uniquenesses: > > pvote jmposaff jmnegaff boposaff bonegaff > > obama.therm mccain.therm oddcand.D evencand.D > > 0.100 0.496 0.497 0.277 0.397 > > 0.129 0.312 0.466 0.585 > > > > Loadings: > > Factor1 > > pvote -0.949 > > jmposaff 0.710 > > jmnegaff -0.709 > > boposaff -0.850 > > bonegaff 0.777 > > obama.therm -0.934 > > mccain.therm 0.830 > > oddcand.D 0.731 > > evencand.D 0.645 > > > > Factor1 > > SS loadings 5.744 > > Proportion Var 0.638 > > > > Test of the hypothesis that 1 factor is sufficient. > > The chi square statistic is 1710.03 on 27 degrees of freedom. > > The p-value is 0 > > > > As you can see, the one-factor model fits the data very poorly (as does a > > two-factor EFA); I suspect, but am not sure, that this is the source of > > the > > problem in sem(). I couldn't get a solution from sem() even when I used > > the > > factanal() solution as start values. > > > > > > > I believe posters reported the same > > > problem. > > > > In almost all cases, the models haven't been properly specified, which is > > not the case here. Here, the model just doesn't fit the data. > > > > > It seems that the ability to invert the correlation matrix may > > > have something to do with this error, but solve(correl) yields a > > solution. > > > > No, the input correlation matrix is positive-definite. sem() would have > > complained if it were not: > > > > > eigen(correl, only.values=TRUE) > > $values > > [1] 6.12561630 0.82418329 0.71616585 0.51263750 0.24467315 0.18248909 > > 0.17024374 > > [8] 0.13905585 0.08493524 > > > > > > I'll keep your problem as a test case to see whether I can produce a > > solution, possibly using a different optimizer -- as I mentioned, sem() > > uses > > nlm(). > > > > Regards, > > John > > > > > > > > > > Here are my correlation matrix and model specifications: > > > > > > --------------------------- R CODE BEGIN > > > ------------------------------------------------ > > > > > > library(sem) > > > correl <- matrix( > > > c(1.0000000,-0.6657822,0.6702089,0.7997673,-0.7225454,0.8992372, > > > -0.8026491,-0.6715168,-0.5781565,- > > > 0.6657822,1.0000000,-0.5107568, > > > -0.5030886,0.6971188,- > > > 0.6306937,0.7200848,0.5121227,0.4496810, > > > 0.6702089,-0.5107568,1.0000000,0.7276558,- > > > 0.3893792,0.6043672, > > > -0.7176532,-0.5247434,-0.4670362,0.7997673,- > > > 0.5030886,0.7276558, > > > 1.0000000,-0.6251056,0.8164190,-0.6728515,- > > > 0.6371453,-0.5531964, > > > -0.7225454,0.6971188,-0.3893792,- > > > 0.6251056,1.0000000,-0.7760765, > > > 0.6175124,0.5567924,0.4914176,0.8992372,- > > > 0.6306937,0.6043672, > > > 0.8164190,-0.7760765,1.0000000,-0.7315507,- > > > 0.6625136,-0.5814590, > > > -0.8026491,0.7200848,-0.7176532,- > > > 0.6728515,0.6175124,-0.7315507, > > > > > 1.0000000,0.5910688,0.5096898,-0.6715168,0.5121227,- > > > 0.5247434, > > > -0.6371453,0.5567924,- > > > 0.6625136,0.5910688,1.0000000,0.8106496, > > > -0.5781565,0.4496810,-0.4670362,- > > > 0.5531964,0.4914176,-0.5814590, > > > 0.5096898,0.8106496,1.0000000), > > ,nrow=9,ncol=9) > > > > > > rownames(correl) = c("pvote", "jmposaff", "jmnegaff", > > > "boposaff","bonegaff", > > > "obama.therm", "mccain.therm", > > > "oddcand.D", "evencand.D" ) > > > > > > colnames(correl) = c("pvote", "jmposaff", "jmnegaff", > > > "boposaff","bonegaff", > > > "obama.therm", "mccain.therm", > > > "oddcand.D", "evencand.D" ) > > > > > > #One Factor Model: > > > model.all <- specify.model() > > > allmeasures -> pvote, b1, NA > > > allmeasures -> obama.therm, b2, NA > > > allmeasures -> mccain.therm, b3, NA > > > allmeasures -> jmposaff, b4, NA > > > allmeasures -> jmnegaff, b5, NA > > > allmeasures -> boposaff, b6, NA > > > allmeasures -> bonegaff, b7, NA > > > allmeasures -> oddcand.D, b8, NA > > > allmeasures -> evencand.D, b9, NA > > > allmeasures <-> allmeasures, NA,1 > > > pvote <-> pvote, v1, NA > > > obama.therm <-> obama.therm, v2, NA > > > mccain.therm <-> mccain.therm, v3, NA > > > jmposaff <-> jmposaff, v4, NA > > > jmnegaff <-> jmnegaff, v5, NA > > > boposaff <-> boposaff, v6, NA > > > bonegaff <-> bonegaff, v7, NA > > > oddcand.D <-> oddcand.D, v8, NA > > > evencand.D <-> evencand.D, v9, NA > > > > > > > > > sem.all <- sem(model.all, correl, 1100) > > > > > > summary(sem.all) > > > > > > #Two Factor Model: > > > model.vi <- specify.model() > > > verbal -> pvote, b1, NA > > > verbal -> obama.therm, b2, NA > > > verbal -> mccain.therm, b3, NA > > > verbal -> jmposaff, b4, NA > > > verbal -> jmnegaff, b5, NA > > > verbal -> boposaff, b6, NA > > > verbal -> bonegaff, b7, NA > > > imp -> oddcand.D, b8, NA > > > imp -> evencand.D, b9, NA > > > imp <-> imp, NA, 1 > > > verbal <-> verbal, NA, 1 > > > pvote <-> pvote, v1, NA > > > obama.therm <-> obama.therm, v2, NA > > > mccain.therm <-> mccain.therm, v3, NA > > > jmposaff <-> jmposaff, v4, NA > > > jmnegaff <-> jmnegaff, v5, NA > > > boposaff <-> boposaff, v6, NA > > > bonegaff <-> bonegaff, v7, NA > > > oddcand.D <-> oddcand.D, v8, NA > > > evencand.D <-> evencand.D, v9, NA > > > imp <-> verbal, civ, NA > > > > > > sem.vi <- sem(model.vi, correl, 1100) > > > summary(sem.vi) > > > > > > --------------------------- R CODE END > > > ------------------------------------------------ > > > > > > Thanks very much. > > > > > > -Solomon > > > -- > > > View this message in context: http://www.nabble.com/Confirmatory-factor- > > > analysis-problems-using-sem-package-%28works-in-Amos%29- > > > tp23664618p23664618.html > > > Sent from the R help mailing list archive at Nabble.com. > > > > > > ______________________________________________ > > > R-help@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. > > > ______________________________________________ R-help@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.
