similar to: SEM interaction

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- I would like to remove the columns of a matrix that contain all zeros. For example, from x<-matrix(c(1,5,3,2,1,4,0,0,0), ncol=3,nrow=3) I would like to remove the third column. However, because this is in a loop I need a way to first determine which columns are all zeros, and only then remove them. I.e., I don't know which column of x contains all zeros until after x is

Hi All, How do i calculate KMO for a dataset? *Dataset:---------------------* m1 m2 m3 m4 m5 m6 m7 m8 1 2 20 20 2 1 4 14 12 2 9 16 3 5 2 5 5 15 3 18 18 18 13 17 9 2 4 4 7 7 2 12 2 11 11 11 5 7 8 5 19 5 2 20 18 6 7 4 7 4 7 9 3 3 7 5 5 5 12 5 13 13 12 8 6 6 4 3 5 17 17 16 9 12 12 4 2 4 4 14 14 10 5 14

Dear colleagues, I've been searching for information on the Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy (MSA). This statistic is generated in SPSS and is often used to determine if a dataset is "appropriate" for factor analysis -- it's true utility seems quite low, but it seems to come up in stats classes a lot. It did in mine, and a glance through the R-help

Hello, I can't find a package which calculates Kendall's tau-c. There is the package Kendall, but it only calcuates Kendall's tau-b. Here is the example from ttp://www2.chass.ncsu.edu/garson/pa765/assocordinal.htm. cityriots <- data.frame(citysize=c(1,1,2,2,3,3), riotsize=c(1,2,1,2,1,2), weight=c(4,2,2,3,0,4)) cityriots <- data.frame(lapply(cityriots,function(x)

Dear R users, I have got two samples: sample A with observation of 223: sample A has five categories: 1,2,3,4,5 (I use the numer 1,2,3,4,5 to define the five differen categories) there are 5 observations in category 1; 81 observations in category 2;110 observations in category 3; 27 observations in category 4; 0 observations in category 5; To present the sample in R: a<-rep(1:5,

Hi all- I am stumped. The code in A. returns errors at lines 14 and 15 and fails to load series1 and series2. However, in B., if temp1 and temp2 are called again (which returns a "Table exists" error; see lines 14-17 in B.) series1 and series2 load correctly. Any ideas? Also-I am open to any suggestions to improve the code as I am a horrific programmer. Thanks A. 1 >

Hello all, I am re-posting my previous question with a simpler, more transparent, commented code. I have been ramming my head against this problem, and I wondered if anyone could lend a hand. I want to make parallel a bootstrap of a linear mixed model on my 8-core mac. Below is the process that I want to make parallel (namely, the boot.out<-boot(dat.res,boot.fun, R = nboot) command).

Hello, I am using the SEM package in R to fit a multigroup latent variable model and ran into some difficulties. I have 2 questions: 1. First, I am getting the following error message and wondering what to do to fix it: Error in solve.default((N[g] - 1) * robustVcov(mod.g, adj.obj = adj.objects[[g]])) : system is computationally singular: reciprocal condition number = 4.52055e-23

Hello, I have access to my database via command line and through workbench, and have access on the grant tables: mysql> SELECT host,user,password,select_priv,insert_priv FROM user; +------+-------+-------------------------------------------+-------------+-------------+ | host | user | password | select_priv | insert_priv |

Hello- I have a script which steps through a series of subjects, and for the subjects I remove outlying values. After removing these outliers, I specify a cutoff, keeping only values over a certain value (e.g., 1.96). I want to populate a matrix with a statistic of the values that make the cutoff (for example, the mean). However, in some subjects, after outliers and the cutoff are specified,

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I have a Suse Linux 10.1 X86_64 server that is destined to work with a mixed bag of OS/2, Windows and Linux clients. For this reason, I have again chosen to use the SMB protocol, which mandates the use of samba. I started with samba 3.0.22, but ran into some glitches so migrated to 3.0.23rc3. My Linux client is running Suse 10.1 X86_32 with samba

People of R(th), I have been ramming my head against this problem, and I wondered if anyone could lend a hand. I want to parallelize a bootstrap of a linear model on my 8-core mac. Below is the process that I want to parallelize (namely, the m2.ph.rlm.boot<-boot(m2.ph,m2.ph.fun, R = nboot) command). This is an extension of the bootstrapping linear models example in Venables and Ripley to

Hello All, I have a question about measurement invariance in a multigroup SEM. I am of the impression that one cannot test the equality of structural paths across groups without demonstrating measurement invariance of latent factors first. At a minimum, this would involve demonstrating that corresponding factor loadings do not differ across groups using, say, a difference in chi-square test. Am

Hello All, Recently, I was asked to help out with an SEM cross-validation analysis. Initially, the project was based on "sample-splitting" where half of cases were randomly assigned to a training sample and half to a testing sample. Attempts to replicate a model developed in the training sample using the testing sample were not entirely successful. A number of parameter estimates were

As the attachement,I wanna draw multi group plot. But I can only use : plot(x,y...) points(...) It's a heavy work to use these command if there're too many groups to be drawn because I have to use point(....) for many times. I wanna know wheter there's command which can draw the multigroup plot directly? Thanks My best.

Hi everyone, I am trying to change some of the default colors in a multipanel-multigroup lattice graphic, but when I change the panel color to white, the only group that is plotted is the last one, as panel.fill overwrites all the previous ones. Is there any way to set the panel background color for the first panel to a color and keep the rest transparent? My code looks like this: #first set

Hey Guus and Ivo, Want to wish you good luck on your conference on VPN on the Expo! Maybe I'll see you there. Greets, Richard - Tinc: Discussion list about the tinc VPN daemon Archive: http://mail.nl.linux.org/lists/ Tinc site: http://ftp.nl.linux.org/pub/linux/tinc/