[R] SEM - singularity error

Thu Sep 20 20:00:11 CEST 2007

Dear Nicolette and Chuck,

I apologize for not seeing Nicolette's original posting.

The model does appear to be correctly specified (though I didn't see
the path diagram) and over-identified. I assume that all of the
variables with lower-case names are observed variables and that "Moist"
and "Hab" are latent variables. (Simply comparing the number of free
parameters to the number of unique covariances among observed variables
provides a necessary but not sufficient condition for identification.
This model is identified because there more than two unique indicators
for each latent variable and because the structural submodel relating
"this" to "Moist" and "Hab" is identified.)

I suspect that the problem here is the restriction that "Moist" and
"Hab" are uncorrelated, which follows from the lack of a double-headed
arrow connecting these variables. You might try adding Moist <-> Hab to
the model.

I hope this helps,
 John

On Thu, 20 Sep 2007 12:40:06 -0400
 Chuck Cleland <ccleland at optonline.net> wrote:
> nicolette.cagle at duke.edu wrote:
> > Good morning,
> > 
> > I am trying to develop a structural equation model of snake
> abundance using
> > habitat variables. In attempting to estimate the model using the
> "sem" package
> > in R version 2.4.0, I receive the following error message:
> > 
> > "Error in solve.default(C) : system is computationally singular:
> reciprocal
> > condition number = 1.75349e-16"
> > 
> > MAIN PROBLEM: I am hoping to discover why I am receiving the
> aforementioned
> > error message and how to successfully estimate the model.
> > 
> > OTHER INFORMATION:
> > 1. I believe the model is over-identified rather than
> under-identified (based on
> > my understanding of the t-rule). I have observed data for 10
> variables (9
> > exogenous, 1 endogenous).
> > 
> > 2. I am not certain that I have used the proper tool to estimate
> the covariance
> > matrix. In this case, I used the "VAR" function.
> > 
> > 3. I am most concerned that I have improperly coded the RAM file.
> For example,
> > in a case where I have three exogenous indicators of one exogenous
> latent
> > variable, I specify a start value of 1 for one of the exogenous
> indicators. I
> > am not sure if this is proper or necessary.
> > 
> > 4. I am new to SEM; this is the first model I have ever tried to
> estimate.
> > 
> > R CODE: Below is the r-code I have used to estimate the structural
> equation
> > model --
> > 
> > # LOADING R PACKAGES
> > library(sem)
> > 
> > # READING IN THE CSV FILES
> > thsi.2006<-read.csv("thsi_ab_env_space_sem.csv")
> > thsi<-thsi.2006
> > 
> > # MAKING "RAM" FILE 2
> > model2.nlc <-specify.model()
> > Moist->slope, NA, 1
> > Moist->sand, lamda21, NA
> > Moist->clay, lamda31, NA
> > Hab->isol, NA, 1
> > Hab->edgedist_a, lamda52, NA
> > Hab->ag10, lamda62, NA
> > Hab->urb10, lamda72, NA
> > Hab->rd10, lamda82, NA
> > Hab->y, lamda92, NA
> > Moist->this, gamma11, NA
> > Hab->this, gamma12, NA
> > slope<->slope, theta11, NA
> > sand<->sand, theta22, NA
> > clay<->clay, theta33, NA
> > isol<->isol, theta44, NA
> > edgedist_a<->edgedist_a, theta55, NA
> > ag10<->ag10, theta66, NA
> > urb10<->urb10, theta77, NA
> > rd10<->rd10, theta88, NA
> > y<->y, the99, NA
> > Moist<->Moist, phi11, NA
> > Hab<->Hab, phi22, NA
> > this<->this, theps11, NA
> > 
> > model2.nlc
> > end
> > 
> > # MAKING S (COVARIANCE MATRIX)
> > thsi.var <- var(thsi)
> > 
> > # MAKING UNSCALED SEM MODEL
> > sem2<-sem(ram=model2.nlc, S=thsi.var, N=22)
> > 
> > I am also attaching a jpeg diagram of the model I am trying to
> estimate. Please
> > let me know if there is any additional information that I should
> add to this
> > posting.
> > 
> > Thank you so much for your time.
> > Nicolette Cagle
> 
>   Your specification of the model seems OK and it is over-identified
> (21
> free parameters and 34 df).  I suspect the problem is that one or
> more
> of your 10 variables is a linear function of the remaining variables.
> If that is the case, then the following should give the same
> singularity
> error:
> 
> factanal(thsi, factors=1)
> 
>   You may be able to drop one or more of the 10 variables from
> consideration and successfully estimate a conceptually similar model.
> 
> hope this helps,
> 
> Chuck Cleland
> 
> >
>
------------------------------------------------------------------------
> > 
> > ______________________________________________
> > R-help at r-project.org 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.
> 
> -- 
> Chuck Cleland, Ph.D.
> NDRI, Inc.
> 71 West 23rd Street, 8th floor
> New York, NY 10010
> tel: (212) 845-4495 (Tu, Th)
> tel: (732) 512-0171 (M, W, F)
> fax: (917) 438-0894
> 
> ______________________________________________
> R-help at r-project.org 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.

--------------------------------
John Fox, Professor
Department of Sociology
McMaster University
Hamilton, Ontario, Canada
http://socserv.mcmaster.ca/jfox/