Effectively in this situation I am working with the function sem in the package sem I will try this parameter fix.c Thanks a lot
Antra EL MOUSSELLY Date: Mon, 28 Mar 2011 12:42:31 -0700 From: ml-node+3412847-1368787395-225...@n4.nabble.com To: antr...@hotmail.com Subject: Re: Structural equation modeling in R(lavaan,sem) Dear jouba, I think you're using the sem() function in the sem package. I'm not sure that I understand your question, but I think it is why you need to specify the variance of the exogenous variable x1 as a parameter. The answer is that it is a parameter to be estimated from the data, but you can avoid specifying it explicitly by using the fixed.x argument to sem(). I hope this helps, John On Mon, 28 Mar 2011 09:00:05 -0700 (PDT) jouba <[hidden email]> wrote: > > > Dear all , > I am trying to run sem by an example with my data but i have problme with an > exogen variable x1 so my examlpe is below > when i add i the equation we have no pboblem but i donââ¬â¢t know why ?? > > x1 <->x1, sigmma7, NA > for me this an exogen variable and i am not obliged to specify this equation > > model.se<-specify.model() > x1->x2,gamm1,NA > x2->x3,gamm2,NA > x3>x4,gamm3,NA > x4->x5,gamm4,NA > x7->x6,gamm5,NA > x6->x5,gamm6,NA > x2 <->x2 ,sigmma1,NA > x3 <->x3 ,simma2,NA > x4 <->x4 ,sigmma3,NA > x5 <->x5 ,sigmma4,NA > x7 <->x7 ,sigmma5,NA > x6 <->x6 ,sigmma6,NA > > sem.se <- sem(model.se, cov(se), 245) > Erreur dans solve.default(C) : > sous-programme Lapack dgesv : le système est exactement singulier > De plus : Message d'avis : > In sem.default(ram = ram, S = S, N = N, param.names = pars, var.names = vars, > : > The following variables have no variance or error-variance parameter > (double-headed arrow): > x1 > The model is almost surely misspecified; check also for missing covariances. > > Thanks a lot > > > Antra EL MOUSSELLY > > > > > > Date: Mon, 28 Mar 2011 05:40:32 -0700 > From: [hidden email] > To: [hidden email] > Subject: Re: Structural equation modeling in R(lavaan,sem) > > On 03/28/2011 04:18 AM, jouba wrote: > > > > Jeremy thanks a lot for your response I have read sem package help > > and I currently reading the help of lavaan I see that there is also > > an other function called lavaan can do the SEM analysis So I wonder > > what is the difference between this function and the sem function > > The 'sem()' function (in the lavaan package) is more user-friendly, in > the sence that it sets a number of reasonable options by default, before > calling the lower-level 'lavaan()' function (which has the 'feature' of > doing nothing automatically, but expects that you really know what your > are doing). > > Most users should only use the 'sem()' function (or the 'cfa()' > function). For non-standard models, the 'lavaan()' function gives more > control. > > > Also I am wondering in the case where we have categorical variables > > and discreet variables?? > > Currently, the lavaan package (0.4-7) has no support for categorical > variables. > > > calculate the correlation matrix , mainly when we have to calculate > > these between a quantitative and qualitative variables, I wonder if > > polycor package is the best solution for this > > It depends. The 'hetcor()' function in the polycor package may provide a > suitable correlation matrix that can be used with the 'sem' package or > the 'lavaan' package. However, AFAIK, the polycor does not compute the > corresponding asymptotic weight matrix which you need for getting proper > standard errors and test statistics (in a WLS context). > > The OpenMx package (http://openmx.psyc.virginia.edu/) has some support > for categorical (ie binary/ordinal) observed variables (although I'm not > sure if they can handle the joint analysis of ordinal and continuous > variables yet). > > But none of this is needed _if_ the categorical variables are all > exogenous (ie predictor variables only) in which case you can still use > the methods for continuous data. > > Yves. > > -- > Yves Rosseel -- http://www.da.ugent.be > Department of Data Analysis, Ghent University > Henri Dunantlaan 1, B-9000 Gent, Belgium > > ______________________________________________ > [hidden email] 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. > > > > > > > If you reply to this email, your message will be added to the discussion > below:http://r.789695.n4.nabble.com/Structural-equation-modeling-in-R-lavaan-sem-tp3409642p3411579.html > > To unsubscribe from Structural equation modeling in R(lavaan,sem), click > here. > > -- > View this message in context: > http://r.789695.n4.nabble.com/Structural-equation-modeling-in-R-lavaan-sem-tp3409642p3412181.html > Sent from the R help mailing list archive at Nabble.com. > [[alternative HTML version deleted]] > ------------------------------------------------ John Fox Sen. William McMaster Prof. of Social Statistics Department of Sociology McMaster University Hamilton, Ontario, Canada http://socserv.mcmaster.ca/jfox/ ______________________________________________ [hidden email] 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. If you reply to this email, your message will be added to the discussion below:http://r.789695.n4.nabble.com/Structural-equation-modeling-in-R-lavaan-sem-tp3409642p3412847.html To unsubscribe from Structural equation modeling in R(lavaan,sem), click here. -- View this message in context: http://r.789695.n4.nabble.com/Structural-equation-modeling-in-R-lavaan-sem-tp3409642p3413316.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML version deleted]]
______________________________________________ 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.
