similar to: Confirmatory Factor Analysis

Hi All, Apologies if this has been answered somewhere else, but I have been searching for an answer all day and not been able to find one. I am trying to plot a path diagram for a CFA I have run, I have installed Rgraphviz and run the following: pathDiagram(cfa, min.rank='item1, item2, item3, item4, item5, item6, item7, item8, item9, item10, item11, item12', max.rank='SMP,

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

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.

In R software,does it have packages about confirmatory factor analysis in R software? 3Q -- View this message in context: http://r.789695.n4.nabble.com/confirmatory-factor-analysis-in-R-tp3347618p3347618.html Sent from the R help mailing list archive at Nabble.com.

Hi Has anyone used R to conduct confirmatory factor analysis? This email pertains to use of SEM. For context consider an example: the basic idea is that there are a bunch of observables variables (say study habbits, amount of time reading in the bus, doing homework, helping other do homework, doing follow-up on errors etc.) and one believes that all these variables maybe measured by two or

Hi: I am doing a confirmatory factor analysis now. In the analysis, I have null hypothesis test which specify some special structure for the loading matrix. And the alternative is there is no such special structure. Then the log likelihood ratio test can be used. The problem I have is my data comes from a questionnaire and all the variables are discrete from 1 to 7, which makes the normality

Hi, I am doing a hierarchical CFA using the sem package. I have 20 items, and I have 2 factors (F3 and F4), and also F1 and F2 are nested within F3. Here is the code that I have, but it is giving me an error message "Warning message: In eval(expr, envir, enclos) : Negative parameter variances. Model may be underidentified." and a further error "Error in summary.objectiveML(cfa,

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

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

Hi R-help, I am using the sem package to run confirmatory factor analysis (cfa) on some questionnaire data collected from 307 participants. I have been running R-2.15.3 in Windows in conjunction with R studio. The model I am using was developed from exploratory factor analysis of a separate dataset (n=439); it includes 18 items that load onto 3 factors. I have used the sem package documentation

I am trying to use Rcmdr 1.5_4 with R-2.11.1 (order to run to run the new version of misdist-0.5.3 which is built under R-2.11.1). however relimp is required for Rcmdr and the version of relimp_1.0.1 downloaded from CRAN will not work with the latest version of Rcmdr (I get error message telling me to reload it). Is there any way round this problem or will there be a new version relimp that is

Hi. I have tried to use Package "SEM". As a learning, I try to convert a program running well of EQS which is as follows to SEM: ### EQS ### /SPECIFICATION CAS=100; VAR=5 MAT=COR; ANA=COR; /EQUATIONS V1=*F1+E1; V2=*F1+E2; V3=*F1+*F2+E3; V4=**F1+*F2*E4; V5=*F2+E5; /VAR E1 TO E5=*; F1*1.0; F2=1.0; /COV E1,E2=*; F1,F2=*: /PRINT FIT ALL; /MATRIX ...... /END This is the converted SEM

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Here's the problem we are having, We are mounting a share from a WinNT 4.0 SP3 box to our redhat 5.0 2.0.32 box using the following command: smbmount //zues/raid1 /ISO/raid1 -I pooh.shellserv.com -u 507 -g 250 - c winterhawk -U sambausr The mount works fine but here is the permissions that I end up with d--------- 1 mspieth root

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

#### I checked through every 3 factor * 3 loading case. #### While, 4 factor * 3 loading failed. #### the data is 6 factor * 3 loading require(sem); cor18<-read.moments(); 1 .68 1 .60 .58 1 .01 .10 .07 1 .12 .04 .06 .29 1 .06 .06 .01 .35 .24 1 .09 .13 .10 .05 .03 .07 1 .04 .08 .16 .10 .12 .06 .25 1 .06 .09 .02 .02 .09 .16 .29 .36 1 .23 .26 .19 .05 .04 .04 .08 .09 .09 1 .11 .13 .12 .03 .05 .03

Hello useRs, I`m running structural equation models with R, but for one of my models the below error message apears. I`m trying to change startvalues but without success. The manual for sem package did not help me. Does anyone knows how to change startvalues for iteration in sem package? Or it can be another problem with the model? Error in startvalues(S, ram, debug = debug, tol = start.tol)

I've just found the lavaan package, and I really appreciate it, as it seems to succeed with models that were failing in sem::sem. I need some clarification, however, in the output, and I was hoping the list could help me. I'll go with the standard example from the help documentation, as my problem is much larger but no more complicated than that. My question is, why is there one latent

Hi list, I'm performing a series of confirmatory factor analysis on different groupings of items from data collected with questionnaires. There are some missing values. For those sets with no missing values I call factanal(datamatrix,factors=n) where datamatrix is a table of all observations for the items under investigation. This call fails when there are missing values. help(factanal)

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 have following data and code; cov <- c (1.670028 ,-1.197685 ,-2.931445,-1.197685,1.765646,3.883839,-2.931445,3.883839,12.050816) cov.matrix <- matrix(cov, 3, 3, dimnames=list(c("y1","x1","x2"), c("y1","x1","x2"))) path.model <- specify.model() x1 -> y1, x1-y1 x2 <-> x1, x2-x1 x2 <->