Re: [R] solving a structural equation model using sem or other package
This is an extract from the sem help page, which deals with your situation: S covariance matrix among observed variables; may be input as a symmetric matrix, or as a lower- or upper-triangular matrix. S may also be a raw (i.e., ``uncorrected'') moment matrix — that is, a sum-of-squares-and-products matrix divided by N. This form of input is useful for fitting models with intercepts, in which case the moment matrix should include the mean square and cross-products for a unit variable all of whose entries are 1; of course, the raw mean square for the unit variable is 1. Raw-moment matrices may be computed by raw.moments. On 24/01/07, Daniel Nordlund [EMAIL PROTECTED] wrote: 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) #al2 contains the variables alc1, alc2, alc3, and cons N - 1122 modelA.ram - specify.model() f1- alc1, NA, 1 f1- alc2, NA, 1 f1- alc3, NA, 1 f2- alc1, NA, 0 f2- alc2, NA, .75 f2- alc3, NA, 1.75 cons - f1,p0, 1 cons - f2,p1, 1 alc1 - alc1, u1, 1 alc2 - alc2, u2, 1 alc3 - alc3, u3, 1 cons - cons, u4, 1 f1 - f1,s1, 1 f2 - f2,s2, 1 f1 - f2,s3, 1 modelA - sem(modelA.ram, S, N, analytic.gradient=FALSE) An equivalent specification in SAS produces the solution presented in the book. The variable cons is a constant vector of 1's. The problem with the sem package is that the covariance matrix which includes the variable cons is singular and sem says so and will not continue. Is there an alternative way to specify this problem for sem to obtain a solution? If not, is there another package that would produce a solution? Thanks, Dan Nordlund Bothell, WA __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- = David Barron Said Business School University of Oxford Park End Street Oxford OX1 1HP __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] solving a structural equation model using sem or other package
David, Thanks for the help. I missed the significance of the section you quoted below from the help. That does indeed solve the problem. Dan Dan Nordlund Bothell, WA USA -Original Message- From: David Barron [mailto:[EMAIL PROTECTED] Sent: Wednesday, January 24, 2007 3:32 AM To: Daniel Nordlund; r-help Subject: Re: [R] solving a structural equation model using sem or other package This is an extract from the sem help page, which deals with your situation: S covariance matrix among observed variables; may be input as a symmetric matrix, or as a lower- or upper-triangular matrix. S may also be a raw (i.e., ``uncorrected'') moment matrix — that is, a sum-of-squares-and-products matrix divided by N. This form of input is useful for fitting models with intercepts, in which case the moment matrix should include the mean square and cross-products for a unit variable all of whose entries are 1; of course, the raw mean square for the unit variable is 1. Raw-moment matrices may be computed by raw.moments. On 24/01/07, Daniel Nordlund [EMAIL PROTECTED] wrote: 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 snip An equivalent specification in SAS produces the solution presented in the book. The variable cons is a constant vector of 1's. The problem with the sem package is that the covariance matrix which includes the variable cons is singular and sem says so and will not continue. Is there an alternative way to specify this problem for sem to obtain a solution? If not, is there another package that would produce a solution? Thanks, Dan Nordlund Bothell, WA __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- = David Barron Said Business School University of Oxford Park End Street Oxford OX1 1HP __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] solving a structural equation model using sem or other package
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) #al2 contains the variables alc1, alc2, alc3, and cons N - 1122 modelA.ram - specify.model() f1- alc1, NA, 1 f1- alc2, NA, 1 f1- alc3, NA, 1 f2- alc1, NA, 0 f2- alc2, NA, .75 f2- alc3, NA, 1.75 cons - f1,p0, 1 cons - f2,p1, 1 alc1 - alc1, u1, 1 alc2 - alc2, u2, 1 alc3 - alc3, u3, 1 cons - cons, u4, 1 f1 - f1,s1, 1 f2 - f2,s2, 1 f1 - f2,s3, 1 modelA - sem(modelA.ram, S, N, analytic.gradient=FALSE) An equivalent specification in SAS produces the solution presented in the book. The variable cons is a constant vector of 1's. The problem with the sem package is that the covariance matrix which includes the variable cons is singular and sem says so and will not continue. Is there an alternative way to specify this problem for sem to obtain a solution? If not, is there another package that would produce a solution? Thanks, Dan Nordlund Bothell, WA __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
