similar to: data.frame error using sem package

Hi there, I just saw your question on the help list and tough you could help me with some start-up info.... I just downloaded the R project software to try running SEM analysis and I also downloaded the SEM package. But it just sits there on the desktop and R does not know where it is...I can¹t figure out how to organize the files...When I type ?sem in R it says object sem not found...I can¹t

Hello everyone, So I ran an anova with aov and then I want to run post-hoc comparisons but keep receiving this message : > no applicable method for "TukeyHSD" Here is my code: > d<-read.table("d.txt") > d > Obs subj Hand Gaze RT > 1 1 s1 1 1 401.4 > 2 2 s2 1 1 363.3...... > summary(ano <-

Does anyone know if the sem package in R can implement a stacked model comparison, for example as in LISREL or AMOS? Thanks, Anthony -- Anthony Steven Dick, Ph.D. Post-Doctoral Fellow Human Neuroscience Laboratory Department of Neurology The University of Chicago 5841 S. Maryland Ave. MC-2030 Chicago, IL 60637 Phone: (773)-834-7770 Email: adick at uchicago.edu Web:

Hello- If I input a variance-covariance matrix and specify NA for start values, how does sem determine the start value? Is there a default? Anthony -- Anthony Steven Dick, Ph.D. Post-Doctoral Fellow Human Neuroscience Laboratory Department of Neurology The University of Chicago 5841 S. Maryland Ave. MC-2030 Chicago, IL 60637 Phone: (773)-834-7770 Email: adick at uchicago.edu Web:

Hello- I am using R to build my initial models, but need to use AMOS to compare the models of two groups (adults vs. kids). The problem is I am getting different results with R and AMOS for the initial models of the separate groups (and the R results make more sense). The parameter estimates (path coefficients and variances) from both programs are nearly identical, but the model chi-squares

Hello all, This is a general stats question--I realize it is an R help list, so tell me to go away if it is inappropriate. I have a 2 X 2 design, and I have specified four identical path models (one for each level of each factor). I want to test for an interaction at each path--essentially (A1 - A2) - (B1 - B2) != 0. I was thinking of computing a contrast for each path of interest, such that

I keep getting this error when I try to use the sem package. I and another person who has successfully used the sem package for similar analysis (fMRI effective connectivity) cannot figure out what is wrong with my code. I would appreciate any suggestions. The error message: Error in data.frame(object$coeff, se, z, 2 * (1 - pnorm(abs(z))), par.code) : arguments imply differing

Dear R-users, I am running a large number of simulations and estimating a structural equation model for each one using the SEM package. Each run of my program has around 8000 simulations. Most of the time the program completes all of them correctly but sometimes I get a segmentation fault in the sem routine and my program stops with the following error message: > *** caught

Dear R users, Jarrett Byrnes and I would like to announce version 2.0-0 of the sem package for fitting observed- and latent-variable structural equation models. This is a general reworking of the original sem package (which is still available on R-Forge as package sem1). Some highlights of sem 2.0-0 include: o More convenient and compact model specification, including the default automatic

Dear R users, Jarrett Byrnes and I would like to announce version 2.0-0 of the sem package for fitting observed- and latent-variable structural equation models. This is a general reworking of the original sem package (which is still available on R-Forge as package sem1). Some highlights of sem 2.0-0 include: o More convenient and compact model specification, including the default automatic

Sorry if this question has been asked previously, I searched but found little. There also doesn't seem to be a dedicated SEM list-serv so hopefully this will find its way to the appropriate audience. In discussing SEM with a colleague I mentioned that a model they were fitting in AMOS was equivalent to a linear regression and that the coefficients would be the same. This of course was the

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've been unsuccessfully trying to reproduce a sem from Grace et al. (2010) published in Ecological Monographs: http://www.esajournals.org/doi/pdf/10.1890/09-0464.1 The model in question is presented in Figure 8, page 81. The errors that I've been getting are: 1. Using a correlation matrix: res.grace <- sem(grace.model, S = grace, N = 190) Warning message: In sem.default(ram

hi, I plot path diagrams with the path.diagram() function of the sem package in combination with the graphviz application. Now I want the graphviz code for a path-plot with the actual standardized coefficients on the arrows (not the names). I tried to add edge.labels="values" as an argument to path.diagram() but it's just ignored. can anyone help me on that? p.s.;

Hello, I have conducted an SEM in which the resultant standardized path coefficients are much higher than would be expected from the raw correlation matrix. To explore further, I stripped the model down to a simple bivariate relationship between two variables (NDVI, and species richness), where it's my understanding that the SEM's standardized path coefficient should equal the correlation

Hi experts, I just started to learn R today, and tried to work with an add-on package sem. I have a version of 2.3.1 on MacOS X 10.4.6 with sem put under /Library/Frameworks/R.framework/Versions/2.3/Resources/library However when I typed library(sem) the following error showed up: Error in library(sem) : 'sem' is not a valid package -- installed < 2.0.0? Why is this? Thank

Hello, It has been found that SEM analysis using polychoric correlations + maximum likelihood estimator produces incorrect test statistics and standard errors (e.g., Flora, D. B., & Curran, P. J. (2004). An Empirical Evaluation of Alternative Methods of Estimation for Con?rmatory Factor Analysis With Ordinal Data. Psychological Methods, 9(4), 466-491). Standard errors can be dealt with by

salutations! i am doing some longitudinal modeling with sem and thought calculating some "simple variables" would make my model more readable. this is the smallest subset of my model that illustrates the resulting problem. i have 2 observed exogenous variables (c1, d2) and 4 observed endogenous variables (dc1, dd1, dc2, dd2). c1 is the observed state at time 1, dc1 is the change in c

Hello, I finally run my measurement model in sem - successfully. Now, I am trying to print out the path diagram that is based on the results - but for some reason it's not working. Below is my script - but the problem is probably in my very last line: # ANALYSIS OF ANXIETY, DEPRESSION, AND FEAR - LISREL P.31 library(sem) # Creating the ANXIETY, DEPRESSION, AND FEAR intercorrelation matrix

Hello, I tried to do a 'sem' analysis for data of how blueberry consumption by birds is influenced by a pollution gradient, using distance and vegetation structural and composition variables, but I got the following error message: Error in sem.default(ram = ram, S = S, N = N, param.names = pars, var.names = vars, : S must be a square triangular or symmetric matrix This may be very