similar to: Can Package SEM do mean structural analysis?

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

Hi All. I am quite a newbie to R. This is a basic question. I like to modify elements of a vector. For Example: a1 <- c(1,2,3,4,3,5) TThe following program sentence does not work but the intention is; if (a1==3) a1*3 . 3 in the vector should be changed to 9, and the resulted vector is (1,2,9,4,9,5). How can I get the result? Thanks in advance for help. -------========-------- mitsu5

Hi All. I am quite a newbie to R. This is a next basic question. I have a matrix; > x <- matrix(1:10.,5) > x [,1] [,2] [1,] 1 6 [2,] 2 7 [3,] 3 8 [4,] 4 9 [5,] 5 10 I like to get a modified matrix as follows; [,1] [,2] [1,] 1 6 [2,] 2 7 [3,] 3 8 * 5 -> 40 [4,] 4 9 [5,] 5 10 The following expression does not work.

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 all, I am attempting to learn my way through the sem package by constructing a simple structural model for some of my data on bird diversity, abundance, and primary productivity. I have constructed a covariance matrix between these variables as per the following: >S_matrix = matrix(c( >+ 0.003083259, 0, 0, >+ 0.143870284, 89.7648490, 0, >+ 0.276950919,

Dear Helplist, I want to produce forecasts from a structural equation model. With the SEM package the model setup and its estimation is possible. However, I have not figured out how to obtain ex ante forecasts, i.e. applying the Gauss-Seidel algorithm to the estimated structural equations for provided values of the exogenous variables (i.e.: y_t = -inv(A)*B*x_t). Does anyone know if the there is

I truly thank for evrybody to give me many very good answers and suggestions. I like to summarize the replies with their results when excuted on R and with my comments. My question is > x <- matrix(1:10.,5) > x [,1] [,2] [1,] 1 6 [2,] 2 7 [3,] 3 8 [4,] 4 9 [5,] 5 10 there is a matrix. On condition x[? ,1]=3, how to modify the appropriate location to be

I am trying to work my way through the book "Singer, JD and Willett, JB, Applied Longitudinal Data Analysis. Oxford University Press, 2003" using R. I have the SAS code and S-Plus code from the UCLA site (doesn't include chapter 8 or later problems). In chapter 8, there is a structural equation/path model which can be specified for the sem package as follows S <- cov(al2)

Hi R-colleagues. In the sem-package i have a problem to introduce hidden variables. As a simple example I take an ordinary factor analysis. The program: cmat=c(0.14855886, 0.05774635, 0.08003300, 0.04900990, 0.05774635, 0.18042029, 0.11213013, 0.03752475, 0.08003300, 0.11213013, 0.24646337, 0.03609901, 0.04900990, 0.03752475, 0.03609901, 0.31702970)

Hello I am using sem to look at the direct effect of one variable on another but i am uncertain if i am progressing correctly. An example: covar1<-? matrix(c(0.4,-0.2,3,-0.2 , 0.3,-2 , 3 ,-2 , 60), nrow=3,byrow=T) rownames(covar1)<-colnames(covar1)<-c("endo","exo","med") path1<-matrix(c(? ? "exo -> endo",? "g1", NA,

Dear R People: Could someone recommend a "baby book" on path analysis and SEM, please? Or if someone has an example that they use in the classroom setting, that would be very cool too. Thanks in advance, Sincerely, Erin -- Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown mailto: erinm.hodgess at gmail.com

Hello, I use the function sem the following way sem.mod <- sem(model, mod.cov, N=109) where the variables are modelled: Z -> M Z -> I Z -> R M <-> M I <-> I R <-> R Z <-> Z The output is ... Normalized Residuals Min. 1st Qu. Median Mean 3rd Qu. Max. -7.3300 -0.2750 -0.2670 -0.1290 -0.0369 9.0300 Parameter Estimates Estimate Std Error z value Pr(>|z|)

Hi, we are trying to do structural equation modelling on R. However, one of our predictor variables is categorical (smoker/nonsmoker). Now, if we want to run the sem() command (from the sem library), we need to specify a covariance matrix (cov). However, Pearson's correlation does not work on the dichotomous variable, so instead we produced a covariance matrix using the Spearman's (or

Hello, I'd like to know if there is a way to fit a Structural equation model with dichotomous indicators (ex: problem with a phone solved/ or not) having effects on a ordinal variable. How I do that using R? Do you have an example with the code in R that you can send to me? Thanks a lot! Renata Estrella UFRJ, Brasil, Rio de Janeiro Renata Leite Estrella Assistente de

Is it possible to fit a structural equation model with link functions in R? I am trying to build a logistic-regression-like model in sem, because incorporating the dichotomous variables linearly seems inappropriate. Mplus can do something similar by specifying a 'link' parameter, but I would like to be able to do it in R, ofcourse. I have explored the 'sem' package from John Fox,

Hi, I would like to print elements from sem (structural equation modeling) function (e.g., model-reproduced covariance matrix (C); estimated asymptotic covariance matrix of parameter estimates (cov)). How can I do this? Thanks, Andr?? -- Andr?? Tavares Corr??a Dias Laborat??rio de Ecologia Vegetal Universidade Federal do Rio de Janeiro CCS-IB-Departamento de Ecologia Caixa Postal 68020

I have been working through the book "Applied longitudinal data analysis: modeling change and event occurrence" by Judith D. Singer and John B. Willett. I have been working examples using SAS and also using it as an opportunity for learning to use R for statistical analysis. I ran into some difficulties in chapter 8 which deals with using structural equation modeling. I have tried to

Hi there, as a student sociology, I'm starting to learn about SEM. The course I follow is based on LISREL, but I want to use the SEM-package on R parallel to it. Using LISREL, I found it to be very usable to be able to see the total direct and total indirect effects (standardized and unstandardized) in the output. Can I create these effects using R? I know how to calculate them

I feel really dumb for having to ask this, but here I go anyway... I perform structural equation modeling on a survey, using about 25 variables that create a total of 5 latent variables (factors). Applying sem (using the sem package) was a piece of cake, even for an (SEM) layman, thanks for THE excellent work here. I have all the variable/path coefficients, A- and P-matrix etc. But now I am

Dear colleagues, Has anybody any experience using the sem package to fit structural equation models using a fitting function other than ML? I have heard tell that OLS may provide better estimates when using standardized matrices generated from small sample sizes, so I was interested in comparing the two for a few models. However, ML appears to be hard-coded into the source for sem...but maybe