similar to: Help with factanal and missing values

I am a new user of the function sem in package sem and lavaan for structural equation modeling 1. I don?t know what is the difference between this function and CFA function, I know that cfa for confirmatory analysis but I don?t know what is the difference between confirmatory analysis and structural equation modeling in the package lavaan. 2. I have data that I want to analyse but I have some

Hi, I'm new to R so please fogive if I write someting silly ... I need to recode a series of responses from a number of questionnaires. The data is read via ODBC from a database where all responses are coded as tables of the form (id, question, score). After dealing with recoding of missing values, I need to "invert" the scores of some questionnaire's item in the form x <-

Hello all, I'm trying to replicate a confirmatory factor analysis done in Amos. 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. I believe posters reported the same problem. It seems

Hi, I'm trying to perform a hierachical, second order CFA. That's the thing that I need to leave AMOS. I found some sim.hierarchical and omega stuff, but nothing clear enough. Can anyone help me? I just need a simple and clear manual. Best, Pablo. [[alternative HTML version deleted]]

Does someone have confirmatory factor analysis program in R,which includes factor loading and some tests?thank you! -- View this message in context: http://r.789695.n4.nabble.com/confirmatory-factor-analysis-program-in-R-tp3386133p3386133.html Sent from the R help mailing list archive at Nabble.com.

Hello, I'm trying to fit a pretty simple confirmatory factor analysis using the sem package. There's a CFA example in the examples, which is helpful, but the output for my (failing) model is hard to understand. I'd be interested in any other ways to do a CFA in R, if this proves troublesome. The CFA is replicating a 5 uncorrelated-factor structure (for those interested, it is a

I'm using specify.model for the sem package. I can't figure out how to represent the residual errors for the observed variables for a CFA model. (Once I get this working I need to add some further constraints.) Here is what I've tried: model.sa <- specify.model() F1 -> X1,l11, NA F1 -> X2,l21, NA F1 -> X3,l31, NA F1 -> X4,l41, NA F1 -> X5, NA, 0.20

Hi Can anybody please suggest me about the documentation of "factanal.fit.mle()" (Not factanal()------ searching factanal.fit.mle() in R always leads to factanal()). Is there any function for doing principal component factor analysis in R. Regards Souvik Bandyopadhyay JRF, Dept Of Statistics Calcutta University [[alternative HTML version deleted]]

Hi. It seems that nearly every time I try to use factanal I get the following response: >faa2db1<-factanal(mretdb1,factors=2,method="mle",control=list(nstart=25)) Error in factanal(mretdb1, factors = 2, method = "mle", control = list(nstart = 25)) : unable to optimize from these starting value(s) > In the case cited above, mretdb1 is synthetic data created

Dear R users: I'm wondering if it's possible to get the residual correlation matrix when using factanal. Since factanal assumes that the errors are normally distributed and independent (provided the factor model fits the data) this would be useful. Of course you would need to submit the data to the function to get the residuals (not just their correlation matrix), but it should be possible

Hello! I have a question about the factanal function. This function returns at the end test statistics like this: Test of the hypothesis that 4 factors are sufficient. The chi square statistic is 4.63 on 2 degrees of freedom. The p-value is 0.0988 Is it possible to get the chi square statistic and the p-value as variables, not the text on the screen? An object of class "factanal"

I wonder if someone could explain why, when I perform confirmatory factor-analysis model using polychoric correlations why I do not get an estimated confidence interval for the RMSEA. My experience with these type models is that I would obtain a confidence interval estimate. I did not get any warning messages with the output. RESULTS: Model Chisquare = 1374 Df = 185 Pr(>Chisq) = 0

Dear friends, I'm using R to produce the following Factor Analysis: > matriz.cor<-hetcor(matrix(as.factor(data), ncol=variables, byrow=T))$correlations > factanal(x=data, factors=2, covmat=matriz.cor, scores='regression') Then the screen output shows the following message: Error en factanal(x = data, factors = 2, covmat = matrix, : requested scores without

Hi, I am currently trying to execute the following command: f<-factanal(factors=k$Components$nparallel,covmat=m,n.obs=2287,rotation="varimax",control=list(opt=list(method=c("BFGS")))) but keep getting the error: L-BFGS-B needs finite values of 'fn' I can't figure out what I am doing wrong here, why isn't optim being told to use BFGS instead of L-BFGS-B...

Dear R developers, Would it be possible to make `factanal` to also accept functions and not just function names for its `rotation` parameter? If I understand correctly, `do.call` also supports this. Best greetings, Stefan -------------- next part -------------- A non-text attachment was scrubbed... Name: patch.diff Type: text/x-patch Size: 568 bytes Desc: patch.diff URL:

Dear list members, Could any expert on factor analysis be so kind to explain how to calculate AIC on the output of factanal. Do I calculate AIC wrong or is factanal$criteria["objective"] not a negative log-likelihood? Best regards Jens Oehlschl?gel The AIC calculated using summary.factanal below don't appear correct to me: n items factors total.df rest.df model.df

Dear list members, Could any expert on factor analysis be so kind to explain how to calculate AIC on the output of factanal. Do I calculate AIC wrong or is factanal$criteria["objective"] not a negative log-likelihood? Best regards Jens Oehlschl?gel The AIC calculated using summary.factanal below don't appear correct to me: n items factors total.df rest.df model.df

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Hi, I have a set of covariance matrices but not the original data. I want to carry out some exploratory factor analysis. So, I am trying to construct a covariance matrix list as the input for factanal. I can construct a list which includes the cov, the centers, and the n.obs. But it doesn't work. I get an error that says "Error in sqrt(diag(cv)) : Non-numeric argument to mathematical

In R factanal output, I can't find a function to give me residuals e. I mannually got it by using x -lamda1*f1 -lamda2*f2 - ... -lamdan*fn, but the e I got are not uncorrelated with all the f's. What did I do wrong? Please help. Yijun ____________________________________________________________________________________ Be a better friend, newshound, and