You have a fairly large and complex model there. This sort of model (almost) always causes problems.
I would try fitting one factor at a time. That might help you to narrow down the problem. If one factor doesn't converge, the whole model won't converge. You might also consider joining the structural equation modeling list - semnet. This isn't really a sem (the package) or R problem, it's a more general SEM (the approach) problem. Jeremy Chen, F., Bollen, K., Paxton, P., Curran, P.J., & Kirby, J. (2001). Improper solutions in structural equation models: Causes, consequences, and strategies. Sociological Methods and Research, 29, 468-508. On 14 February 2011 07:34, Felipe Bhering <felipelbher...@gmail.com> wrote: > > Someone can help me? I tried several things and always don't converge > > # Model > library(sem) > dados40.cov <- cov(dados40,method="spearman") > model.dados40 <- specify.model() > F1 -> Item11, lam11, NA > F1 -> Item31, lam31, NA > F1 -> Item36, lam36, NA > F1 -> Item54, lam54, NA > F1 -> Item63, lam63, NA > F1 -> Item65, lam55, NA > F1 -> Item67, lam67, NA > F1 -> Item69, lam69, NA > F1 -> Item73, lam73, NA > F1 -> Item75, lam75, NA > F1 -> Item76, lam76, NA > F1 -> Item78, lam78, NA > F1 -> Item79, lam79, NA > F1 -> Item80, lam80, NA > F1 -> Item83, lam83, NA > F2 -> Item12, lam12, NA > F2 -> Item32, lam32, NA > F2 -> Item42, lam42, NA > F2 -> Item47, lam47, NA > F2 -> Item64, lam64, NA > F2 -> Item66, lam66, NA > F2 -> Item68, lam68, NA > F2 -> Item74, lam74, NA > F3 -> Item3, lam3, NA > F3 -> Item8, lam8, NA > F3 -> Item18, lam18, NA > F3 -> Item23, lam23, NA > F3 -> Item28, lam28, NA > F3 -> Item33, lam33, NA > F3 -> Item38, lam38, NA > F3 -> Item43, lam43, NA > F4 -> Item9, lam9, NA > F4 -> Item39, lam39, NA > F5 -> Item5, lam5, NA > F5 -> Item10, lam10, NA > F5 -> Item20, lam20, NA > F5 -> Item25, lam25, NA > F5 -> Item30, lam30, NA > F5 -> Item35, lam35, NA > F5 -> Item45, lam45, NA > Item3 <-> Item3, e3, NA > Item5 <-> Item5, e5, NA > Item8 <-> Item8, e8, NA > Item9 <-> Item9, e9, NA > Item10 <-> Item10, e10, NA > Item11 <-> Item11, e11, NA > Item12 <-> Item12, e12, NA > Item18 <-> Item18, e18, NA > Item20 <-> Item20, e20, NA > Item23 <-> Item23, e23, NA > Item25 <-> Item25, e25, NA > Item28 <-> Item28, e28, NA > Item30 <-> Item30, e30, NA > Item31 <-> Item31, e31, NA > Item32 <-> Item32, e32, NA > Item33 <-> Item33, e33, NA > Item35 <-> Item35, e35, NA > Item36 <-> Item36, e36, NA > Item38 <-> Item38, e38, NA > Item39 <-> Item39, e39, NA > Item42 <-> Item42, e42, NA > Item43 <-> Item43, e43, NA > Item45 <-> Item45, e45, NA > Item47 <-> Item47, e47, NA > Item54 <-> Item54, e54, NA > Item63 <-> Item63, e63, NA > Item64 <-> Item64, e64, NA > Item65 <-> Item65, e65, NA > Item66 <-> Item66, e66, NA > Item67 <-> Item67, e67, NA > Item68 <-> Item68, e68, NA > Item69 <-> Item69, e69, NA > Item73 <-> Item73, e73, NA > Item74 <-> Item74, e74, NA > Item75 <-> Item75, e75, NA > Item76 <-> Item76, e76, NA > Item78 <-> Item78, e78, NA > Item79 <-> Item79, e79, NA > Item80 <-> Item80, e80, NA > Item83 <-> Item83, e83, NA > F1 <-> F1, NA, 1 > F2 <-> F2, NA, 1 > F3 <-> F3, NA, 1 > F4 <-> F4, NA, 1 > F5 <-> F5, NA, 1 > F1 <-> F2, F1F2, NA > F1 <-> F3, F1F3, NA > F1 <-> F4, F1F4, NA > F1 <-> F5, F1F5, NA > F2 <-> F3, F2F3, NA > F2 <-> F4, F2F4, NA > F2 <-> F5, F2F5, NA > F3 <-> F4, F3F4, NA > F3 <-> F5, F3F5, NA > F4 <-> F5, F4F5, NA > > > ###i tryed several correlations, such as hetcor and polychor of polycor > library > > > hcor <- function(data) hetcor(data, std.err=FALSE)$correlations > hetdados40=hcor(dados40) > > > dados40.sem <- sem(model.dados40, dados40.cov, nrow(dados40)) > Warning message: > In sem.default(ram = ram, S = S, N = N, param.names = pars, var.names = > vars, : > Could not compute QR decomposition of Hessian. > Optimization probably did not converge. > > ##################################################### > > The same happen if i put hetdados40 in the place of dados40.cov > of course hetdados40 has 1 in the diag, but any 0 > > what should i do? i tryed several things... > > all value positive.. > > ##################################################### > >> eigen(hetdados40)$values > [1] 14.7231030 4.3807378 1.6271780 1.4000193 1.0670784 1.0217670 > [7] 0.8792466 0.8103790 0.7397817 0.7279262 0.6909955 0.6589746 > [13] 0.6237204 0.6055884 0.5777750 0.5712017 0.5469284 0.5215437 > [19] 0.5073809 0.4892339 0.4644124 0.4485545 0.4372404 0.4290573 > [25] 0.4270672 0.4071262 0.3947753 0.3763811 0.3680527 0.3560231 > [31] 0.3537934 0.3402836 0.3108977 0.3099143 0.2819351 0.2645035 > [37] 0.2548654 0.2077900 0.2043732 0.1923942 >> eigen(dados40.cov)$values > [1] 884020.98 337855.95 138823.30 126291.58 87915.21 79207.04 73442.71 > [8] 68388.11 60625.26 58356.54 55934.05 54024.00 50505.10 48680.26 > [15] 46836.47 45151.23 43213.65 41465.42 40449.59 37824.73 37622.43 > [22] 36344.34 35794.22 33959.29 33552.64 32189.94 31304.44 30594.85 > [29] 30077.32 29362.66 26928.12 26526.72 26046.47 24264.50 23213.18 > [36] 21503.97 20312.55 18710.97 17093.24 14372.21 > > ##################################################### > > > there are 40 variables and 1004 subjects, should not be a problem the number > of variables also! > -- > View this message in context: > http://r.789695.n4.nabble.com/sem-problem-did-not-converge-tp3305200p3305200.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. > -- Jeremy Miles Psychology Research Methods Wiki: www.researchmethodsinpsychology.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.