similar to: Multiple Groups CFA in Lavaan

Hi Sorry for the rather long message. I am trying to use the cfa command in the lavaan package to run a CFA however I am unsure over a couple of issues. I have @25 dichotomous variables, 300 observations and an EFA on a training dataset suggests a 3 factor model. After defining the model I use the command fit.dat <- cfa(model.1, data=my.dat, std.lv = T, estimator="WLSMV",

Dear R-List, (I am not sure whether this list is the right place for my question...) I have a dataframe df.cfa

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

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

Dear all, I am trying to learn about R. As a Phd student, I would like to use R for Krippendorff s alpha and later for a series of CFA. Is there any good introduction to these kind of analyses, or could you recommend me some tutorials on youtube, for example? I am new to R, so I need something basic , starting from opening the R environment?. Thank you . Martina Hulesova Odesl?no z m?ho Windows

I don't know the right computer science words for this question, I'm afraid. Apology in advance. How do you find your way around in somebody else's code? If the user runs a specific command, and wants to know how the data is managed until the result is returned, what to do ? I've tried this manually with tools like mtrace and browser. This is a bit frustrating because the

I have friendship data which is strong skewed. So it doesn't make sense to use maximum likelihood methods for fa and cfa. But I couldn't find any function for asymptotically distributed data for doing a factor analysis. Only: apca() but there is no possibility to allow for factor correlations. The same problem is with sem() I couldn't get any solutions for my model because of the

Hi, I recently tried to estimate a linear unconditional latent growth curve on 7 repeated measures using lavaan (most recent version): modspec=' alpha =~ 1*read_g0 + 1*read_g1 + 1*read_g2 + 1*read_g3 + 1*read_g4 + 1*read_g5 + 1*read_g6 beta =~ 0*read_g0 + 1*read_g1 + 2*read_g2 + 3*read_g3 + 4*read_g4 + 5*read_g5 + 6*read_g6 ' gmod=lavaan(modspec, data=math, meanstructure=T,

Hello, I am trying to create parcels for a CFA model. I am trying to average 6 sets of 3 variables each into parcels. I don't understand why I am getting an error message as follows: Thanks for your help, Catherine atds1par <- rowMeans(semHW1dat1[, c("atds1", "atds2", "atds3")], na.rm=TRUE) atds2par <- rowMeans(semHW1dat1[, c("atds4",

I performed a CFA using the lavaan package require('lavaan'); HS.model <- 'external_regulation_soc =~ JOBMOTIVATIE_extsoc1 + JOBMOTIVATIE_extsoc2 + JOBMOTIVATIE_extsoc3 external_regulation_mat =~ JOBMOTIVATIE_extmat1 + JOBMOTIVATIE_extmat2 + JOBMOTIVATIE_extmat3 introjected_regulation =~ JOBMOTIVATIE_introj1 +

Hi list members, I saw a couple lavaan posts here so I think I?m sending this to the correct list. I am trying to run a multigroup analysis with lavaan in order to compare behavioural correlations across two populations. I?m following the method suggested in the paper by Dingemanse et al. (2010) in Behavioural Ecology. In one of the groups, lavaan returns negative variance for one path and I?m

Hello R Community, I am using the Lavaan package in R 2.15.0 to analyze data collected from 1200 lakes across North America. My dataset includes 3 continuous independent variables (LOG_NTL, LOG_PTL, and LOG_SR_A_D) and 1 continuous dependent variable (BIOVOL) . I have successfully constructed structural equation models using the Lavaan package (example included below with code), but I have not

Hi Yves lavaan looks like a very nice package. From the tutorial introduction I see you create path diagrams for some of the models you describe. How did you do this? I don't see a function for this in the package. I know there is a path.diagram function in the sem package that uses dot to draw the diagram, but I've always found the layouts from dot somewhat strange for path diagrams

I have been trying to use lavaan (version 0.4-7) for a simple path model, but the program seems to be computing far less degrees of freedom for my model then it should have. I have 7 variables, which should give (7)(8)/2 = 28 covariances, and hence 28 DF. The model seems to only think I have 13 DF. The code to reproduce the problem is below. Have I done something wrong, or is this something I

Hello! I am trying to reproduce (for a publication) analyses that I ran several months ago using lavaan, I'm not sure which version, probably 0.4-12. A sample model is given below: pathmod='mh30days.log.w2 ~ mh30days.log + joingroup + leavegroup + alwaysgroup + grp.partic.w2 + black + age + bivoc + moved.conf + local.noretired + retired + ds + ministrytime + hrswork + nomoralescore.c +

Hello all I'm trying to run some path analysis in either sem or lavaan (preferably lavaan because I find its interface easier to use). Most of my variables are continuously distributed and fairly well-behaved but I have a single exogenous variable (sex) which is not continuously distributed. Preliminary model fitting suggests that there aren't any sex by (anything else) interactions. The

Dear R-users, Does somebody know what does the "Estimate" reported by the Lavaan model tell us? I assume this tells the relative strength of the dyadic relations. Thank you for your help! Regards, Sylvain -- View this message in context: http://r.789695.n4.nabble.com/Lavaan-model-tp4648004.html Sent from the R help mailing list archive at Nabble.com.

Hi r-help, I use lavaan:sem() for structural equation modelling with latent variables. Below is a reproducible example (the code requires a working installation of lavaan) where the latent variable criminality is in focus. Besides criminality in general, I am specifically interested one of the manifest variables that make up the latent variable criminality, namely fire.setting. My question is:

Hi all, I am using package lavaan and have created a structural equation model with two exogenous and seven endogenous variables with the following relationships #specify the model m1 = ' # regressions D ~ ma + hs + b4 + b5 + b15 + b16 ma ~ hs + b4 + b5 + b15 + b16 hs ~ b4 + b5 + b15 + b16 b4 ~ el + la b5 ~ el + la

Dear R-users, A new package called `lavaan' (for latent variable analysis) has been uploaded to CRAN. The current version of lavaan (0.3-1) can be used for path analysis, confirmatory factor analysis, structural equation modeling, and growth curve modeling. More information can be found on the website: http://lavaan.org Some notable features of lavaan: - the 'lavaan model