similar to: version 3.0-0 of the sem now on CRAN

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

Dear R users, Version 2.1-1 of the sem package, for structural equation modeling, is now on CRAN. Unlike version 2.0-0, which was a major overhaul of the package, version 2.1-1 just sprinkles some syntactic sugar on it, introducing the specifyEquations() and cfa() functions; specifyEquations() supports model specification in equation (rather than path) format, and cfa() facilitates compact

Dear R users, Version 2.1-1 of the sem package, for structural equation modeling, is now on CRAN. Unlike version 2.0-0, which was a major overhaul of the package, version 2.1-1 just sprinkles some syntactic sugar on it, introducing the specifyEquations() and cfa() functions; specifyEquations() supports model specification in equation (rather than path) format, and cfa() facilitates compact

Dear all, I try to conduct a SEM / two stage least squares regression with the following equations: First: X ~ IV1 + IV2 * Y Second: Y ~ a + b X therein, IV1 and IV2 are the two instruments I would like to use. the structure I would like to maintain as the model is derived from economic theory. My problem here is that I have trouble solving the equations to get the reduced form so I can run

Hi, I am trying to obtain the heteroskedasticity consitent standard errors (HCSE) after apply 2SLS. I obtain 2SLS through tsls from package sem or systemfit: #### tsls #### library (sem) Reg2SLS <-tsls(LnP~Sc+Ag+Ag2+Var+R+D,~I2+Ag+Ag2+Var+R+D) summary (Reg2SLS) #### systemfit #### library (systemfit) RS <- LnP~Sc+Ag+Ag2+Var+R+D Inst <- ~I2+Ag+Ag2+Var+R+D labels

Hi, I am using tsls function from sem package to estimate a model which includes large number of data. Among its predictors, it has a nominal data which has about 10 possible values. So I expand this parameter into 9-binary-value predictors with the coefficient of base value equals 0. I also have another continuous predictor. The problem is that, whenever I run the tsls, I will get 'System

Dear Kurt, I've uploaded a new version (0.9-4) of the sem package to CRAN. I hope that everything is well with you. John -------------------------------- John Fox Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox _______________________________________________ R-packages mailing list R-packages at

Dear friends, I am trying to understand and implement instrumental variables regression using R. I found a small (simple) example here which purportedly illustrates the mechanics (using 2-stage least-squares): http://www.r-bloggers.com/a-simple-instrumental-variables-problem/ Basically, here are the R commands (reproducible example) from that site: # ------ begin R library(AER)

Dear R users, The OpenMx developer team takes great pride in announcing the availability of OpenMx 1.0. The team would like to express its gratitude to the large number of beta-testers who have helped us improve the code. Thank you. OpenMx is a free suite of R functions and a estimation back-end that supports fitting a wide variety of structural equation models including multiple groups, full

Dear R users, The OpenMx developer team takes great pride in announcing the availability of OpenMx 1.0. The team would like to express its gratitude to the large number of beta-testers who have helped us improve the code. Thank you. OpenMx is a free suite of R functions and a estimation back-end that supports fitting a wide variety of structural equation models including multiple groups, full

Dear James, I've been away and reading email at intervals, and also not following the r-help list during my trip. I've taken the liberty of copying this response to the r-help list along with your original posting. My apologies for the delay. The short answer to your question is "no," I'm afraid. sem() distinguishes between fixed and free parameters by the fact that the

I am trying to run a confirmatory factor analysis using the SEM package. My data are ordinal. I have read http://socserv.mcmaster.ca/jfox/Misc/sem/SEM-paper.pdf. When I apply the hetcor function, I receive the following error: Error in checkmvArgs(lower = lower, upper = upper, mean = mean, corr = corr, : at least one element of 'lower' is larger than 'upper' Example:

Dear list members, In sem, std.coef() will give me standardized coefficients from a sem model. But is there a trick so that path.diagram can use these coefficients rather than unstandardized ones? Thanks Steve Powell From: John Fox <jfox_at_mcmaster.ca> Date: Wed 28 Feb 2007 - 14:37:22 GMT Dear Tim, See ?standardized.coefficients (after loading the sem package). Regards, John John

Subject: Re: [R] Problems with R Commander version 1.8-3 Many thanks for your kindly replay. I just use a At this time I use an earlier version of the package. I try to install the Rcmdr from R-Forge. Many tanks again Message: 21 Date: Wed, 28 Mar 2012 08:04:09 -0400 From: "John Fox" <jfox at mcmaster.ca> To: <petretta at unina.it> Cc: r-help at r-project.org

I'm working on a program that loads several large data files. I'm using ddply (plyr is really awesome) but I want to minimize the amount of times a large data file is read in. One solution is to keep track of which data file is open with a global variable and then change the currently open data file globally as needed. However, I'm unclear on how to alter a global variable

Dear all, Sandy Weisberg and I would like to announce version 2.0-0 of the car package, now on CRAN. We've released this major revision of the package in anticipation of the publication of An R Companion to Applied Regression, Second Edition (Sage, in press), co-authored by us, which should be available before the end of the year. The new version of the car package has a number of new

Dear all, Sandy Weisberg and I would like to announce version 2.0-0 of the car package, now on CRAN. We've released this major revision of the package in anticipation of the publication of An R Companion to Applied Regression, Second Edition (Sage, in press), co-authored by us, which should be available before the end of the year. The new version of the car package has a number of new

Dear R users, I'd like to announce a new version, 1.8-1, of the Rcmdr package. The Rcmdr ("R Commander") package provides a basic-statistics graphical user interface (GUI) to R, implemented in Tcl/Tk via the standard R tcltk package. Beyond small changes and additions, the new version of the Rcmdr package uniformly implements a feature, first available in version 1.7-0, that

Dear R users, I'd like to announce a new version, 1.8-1, of the Rcmdr package. The Rcmdr ("R Commander") package provides a basic-statistics graphical user interface (GUI) to R, implemented in Tcl/Tk via the standard R tcltk package. Beyond small changes and additions, the new version of the Rcmdr package uniformly implements a feature, first available in version 1.7-0, that